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METHOD:PUBLISH
X-WR-CALNAME:WASP
X-ORIGINAL-URL:https://wasp-sweden.org
X-WR-CALDESC:Events for WASP
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X-Robots-Tag:noindex
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BEGIN:VTIMEZONE
TZID:+01:00
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BEGIN:VEVENT
DTSTART;TZID=+01:00:20210609T133000
DTEND;TZID=+01:00:20210609T235900
DTSTAMP:20260602T130620
CREATED:20210528T112344Z
LAST-MODIFIED:20260601T083903Z
UID:10000305-1623245400-1623283140@wasp-sweden.org
SUMMARY:PhD Defense: Designing Trustworthy Autonomous Systems
DESCRIPTION:Welcome to Doctoral Defense of Piergiuseppe Mallozzi\nDate and Time: June 9th\, 13:30\n \nLocation: Room 473\, Jupiter Building \nTitel: Designing Trustworthy Autonomous Systems \nDoctoral student: Piergiuseppe Mallozzi\, PhD Software Engineering\, Chalmers University of Technology \nSupervisor: Patrizio Pelliccione\, Chalmers University of Technology \nOpponent:  Cristina Seceleanu\, Mälardalen University\, Sweden \nOriginal location: Chalmers Universtity of Technology
URL:https://wasp-sweden.org/event/phd-defense-designing-trustworthy-autonomous-systems/
LOCATION:Chalmers University of Technology\, Chalmers University of Technology\, Göteborg\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210608T150000
DTEND;TZID=+01:00:20210608T235900
DTSTAMP:20260602T130620
CREATED:20210525T105130Z
LAST-MODIFIED:20260601T083904Z
UID:10000307-1623164400-1623196740@wasp-sweden.org
SUMMARY:PhD Defense: Motion Planning and Control of Automated Vehicles in Critical Situations
DESCRIPTION:Welcome to Doctoral Defense of Lars Svensson\nDate and time: June 8\, 15:00 \nLocation: Online \nTitel: Motion Planning and Control of Automated Vehicles in Critical Situations\n \nDoctoral student:  Lars Svensson\, Department of Machine Design\, KTH \nSupervisor:  Professor Martin Törngren\, Department of Machine Design\, KTH \nOpponent:  Professor Christian Gerdes\, Stanford University \nOriginal location: KTH
URL:https://wasp-sweden.org/event/phd-defense-motion-planning-and-control-of-automated-vehicles-in-critical-situations/
LOCATION:KTH Royal Institute of Technology\, KTH Royal Institute of Technology\, Stockholm\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210608T140000
DTEND;TZID=+01:00:20210608T235900
DTSTAMP:20260602T130620
CREATED:20210525T104503Z
LAST-MODIFIED:20260601T083904Z
UID:10000308-1623160800-1623196740@wasp-sweden.org
SUMMARY:PhD Defense: Model Predictive Control for Cooperative Rendezvous of Autonomous Unmanned Vehicles
DESCRIPTION:Welcome to Doctoral Defense of Linnea Persson\n\nDate and time: June 8\, 14:00\n \nLocation: Online \nDoctoral student:  Linnea Persson\, Division of Decision and Control Systems\, KTH \nTitel: Model Predictive Control for Cooperative Rendezvous of Autonomous Unmanned Vehicles \nSupervisor:  Professor Bo Wahlberg\, Division of Decision and Control Systems\, KTH \nOpponent:  Professor Jonathan How\, Massachusetts Institute of Technology \nOriginal location: KTH
URL:https://wasp-sweden.org/event/phd-defense-model-predictive-control-for-cooperative-rendezvous-of-autonomous-unmanned-vehicles/
LOCATION:KTH Royal Institute of Technology\, KTH Royal Institute of Technology\, Stockholm\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210608T100000
DTEND;TZID=+01:00:20210608T235900
DTSTAMP:20260602T130620
CREATED:20210525T103635Z
LAST-MODIFIED:20260601T083904Z
UID:10000309-1623146400-1623196740@wasp-sweden.org
SUMMARY:PhD Defense: On the Foundations of Practical Language-Based Security
DESCRIPTION:Title: On the Foundations of Practical Language-Based Security \nRespondent: Maximilian Algehed \nOpponent: Frank Piessens \nDate & Time: June 8\, 10:00 – 13:00 \nLink to thesis and to the online disputation \n\n\nAbstract\nTeoretiska Grundvalar för Praktiska IT-Säkerhetsverktyg\nModerna datorprogram är de mest komplexa artefakter som människan någonsin\nhar skapat. För att samhället ska kunna lita på att ingenjörer och programmerare\ninte utsätter oss alla för stora risker med dessa komplexa system behöver vi\ntillgång till verktyg som hjälper oss att förebygga säkerhetsluckor. Den här\navhandligen handlar om hur vi kan säkerställa att sådana verktyg faktiskt\nfungerar och inte ger ett falskt intryck om säkerhet där ingen finns.\nVerktyg av den här typen kan i grova tag uppdelas i två kategorier. I den första\nkategorin faller verktyg som programmeraren använder under utvecklingstiden\nför att hitta problem innan programmet färdigställts och i den andra kategorin\nfinner vi verktyg som agerar huvudsakligen efter att ett program redan användsi praktiken för att hindra säkerhetshål som inte upptäcks under utvecklingsperi-\noden från att skapa problem. I den här avhandlingen finns nya resultat för bådadessa kategorier av verktyg.\nI den första kategorin bidrar den här avhandlingen med en ny metod för att\nbevisa att programmeringsspråk kan garantera att alla program i språket är\nsäkra. I den andra kategorin bidrar den här avhandlingen med en ny förenande\nteori och ett bevis att det inte existerar några perfekta mekanismer för att ge\nsäkerhet. Sammanfattningsvis ger den här avhandlingen stöd till inställningen att\ndatasäkerhet är någonting som bör finnas med från början i utvecklingsprocessen\ndå det är förhållandevis mer tekniskt komplicerat att anpassa system för att\nuppnå datasäkerhet a posteriori.
URL:https://wasp-sweden.org/event/phd-defense-on-the-foundations-of-practical-language-based-security/
LOCATION:Online\, Online\, Other
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210604T091500
DTEND;TZID=+01:00:20210604T235900
DTSTAMP:20260602T130620
CREATED:20210504T132058Z
LAST-MODIFIED:20260601T083906Z
UID:10000312-1622798100-1622851140@wasp-sweden.org
SUMMARY:PhD Defense: Learning Visual Perception for Autonomous Systems
DESCRIPTION:Welcome to Doctoral Defense of Gustav Häger\n\nDate and time: June 4\, 09:15 \nLocation: Online \nTitel: Learning Visual Perception for Autonomous Systems \nDoctoral student: Gustav Häger\, Department of Electrical Engineering\, Linköping University \nSupervisor: Michael Felsberg\, Department of Electrical Engineering\, Linköping University \nOpponent: Roman Pflugfelder\, Technische Universität Wien och Austrian Institute of Technology
URL:https://wasp-sweden.org/event/phd-defense-learning-visual-perception-for-autonomous-systems/
LOCATION:Linköping University\, Linköping University\, Linköping\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210602T000000
DTEND;TZID=+01:00:20210602T235959
DTSTAMP:20260602T130620
CREATED:20210318T075343Z
LAST-MODIFIED:20260601T083908Z
UID:10000318-1622592000-1622678399@wasp-sweden.org
SUMMARY:WASP4ALL 2021 - Building Excellence for the Era of AI
DESCRIPTION:WASP has now passed its fifth year and with an expanded program including initiatives towards AI and Math\, WASP continues to build the foundations for ensuring relevance and impact of its research. This event will highlight and showcase the excellence that WASP is producing. With talks from a mix of WASP researchers\, international speakers\, industrial partners and high-profile decision makers\, this event demonstrates how WASP is building excellence for the Era of AI. \n​We warmly welcome you to take part of this streamed production and live talks.
URL:https://wasp-sweden.org/event/wasp4all-2021-building-excellence-for-the-era-of-ai/
LOCATION:Online\, Online\, Other
CATEGORIES:Conference
ATTACH;FMTTYPE=image/png:https://wasp-sweden.org/wp-content/uploads/2021/03/Wasp_1090x495_2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210528T131500
DTEND;TZID=+01:00:20210528T235900
DTSTAMP:20260602T130620
CREATED:20210419T073803Z
LAST-MODIFIED:20260601T083906Z
UID:10000314-1622207700-1622246340@wasp-sweden.org
SUMMARY:Licentiate Defense: Robust LIDAR-Based Localization in Underground Mines
DESCRIPTION:Title: Robust LIDAR-Based Localization in Underground Mines \nSpeaker: MSc Kristin Nielsen\, Epiroc Drills AB/LiU \nOpponent: Prof John Folkesson\, KTH \nSupervisor: Doc Gustaf Hendeby\, LiU \nCo-supervisors: Prof Fredrik Gustafsson\, LiU\, Dr Robert Lundh\, Epiroc Drills AB/LiU \n  \nDate: 2021-05-28 \nTime: 13:15-15:00 \nPlace: https://liu-se.zoom.us/j/68373726076?pwd=RUZRWDBBMlBCUTV3azBWNWNPbWIvZz09 \nLanguage: English \n  \nAbstract: \nThe mining industry is currently facing a transition from manually operated vehicles to remote or semi-automated vehicles. The vision is fully autonomous vehicles being part of a larger fleet\, with humans only setting high-level goals for the autonomous fleet to execute in an optimal way. An enabler for this vision is the presence of robust\, reliable and highly accurate localization. This is a requirement for having areas in a mine with mixed autonomous vehicles\, manually operated vehicles\, and unprotected personnel. The robustness of the system is important from a safety as well as a productivity perspective. When every vehicle in the fleet is connected\, an uncertain position of one vehicle can result in the whole fleet begin halted for safety reasons. \nProviding reliable positions is not trivial in underground mine  environments\, where access to global satellite based navigation systems is denied. Due to the harsh and dynamically changing environment\, onboard positioning solutions are preferred over systems utilizing external infrastructure. The focus of this thesis is localization systems relying only on sensors mounted on the vehicle\, e.g.\, odometers\, inertial measurement units\, and 2D LIDAR sensors. The localization methods are based on the Bayesian filtering framework and estimate the distribution of the position in the reference frame of a predefined map     covering the operation area. This thesis presents research where the properties of 2D LIDAR data\, and specifically characteristics when obtained in an underground mine\, are considered to produce position estimates that are robust\, reliable\, and accurate. \nFirst\, guidelines are provided for how to tune the design parameters associated with the unscented Kalman filter (UKF). The UKF is an algorithm designed for nonlinear dynamical systems\, applicable to this particular positioning problem. There exists no general guidelines for how to choose the parameter values\, and using the standard values suggested in the literature result in unreliable estimates in the considered application. Results show that a proper parameter setup substantially improves the performance of this algorithm. \nNext\, strategies are developed to use only a subset of available measurements without losing quality in the position estimates. LIDAR sensors typically produce large amounts of data\, and demanding real-time positioning information limits how much data the system can process. By analyzing the information contribution from each individual laser ray in a complete LIDAR scan\, a subset is selected by maximizing the information content. It is shown how 80% of available LIDAR measurements can be dropped without significant loss of accuracy. \nLast\, the problem of robustness in non-static environments is addressed. By extracting features from the LIDAR data\, a computationally tractable localization method\, resilient to errors in the map\, is obtained. Moving objects\, and tunnels being extended or closed\, result in a map not corresponding to the LIDAR observations. State-of-the art feature extraction methods for 2D LIDAR data are identified\, and a localization algorithm is defined where features found in LIDAR data are matched to features extracted from the map. Experiments show that regions of the map containing errors are automatically ignored since no matching features are found in the LIDAR data\, resulting in more robust position estimates. \n\nQuestions are answered by Ninna Stensgård\, Phone  013-28 47 25 \nE-mail ninna.stensgard@liu.se \n\n 
URL:https://wasp-sweden.org/event/licentiate-defense-robust-lidar-based-localization-in-underground-mines/
LOCATION:Online\, Online\, Other
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210520T130000
DTEND;TZID=+01:00:20210520T235900
DTSTAMP:20260602T130620
CREATED:20210510T105752Z
LAST-MODIFIED:20260601T083905Z
UID:10000311-1621515600-1621555140@wasp-sweden.org
SUMMARY:PhD Defense: Machine Learning for Wireless Link Adaptation
DESCRIPTION:Author: Vidit Saxena\,  PhD in Electrical Engineering\, KTH \nTitle of thesis: Machine Learning for Wireless Link Adaptation \nDate and location of defense: Thursday May 20\, 2021 at 13.00 in the lecture hall F3\, Lindstedtsvägen 26\, KTH Royal Institute of Technology\, Stockholm\nor online via: https://kth-se.zoom.us/j/68818071898 \nOriginal location: KTH or online.
URL:https://wasp-sweden.org/event/phd-defense-machine-learning-for-wireless-link-adaptation/
LOCATION:KTH Royal Institute of Technology\, KTH Royal Institute of Technology\, Stockholm\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210510T141500
DTEND;TZID=+01:00:20210510T235900
DTSTAMP:20260602T130620
CREATED:20210408T150406Z
LAST-MODIFIED:20260601T083907Z
UID:10000316-1620656100-1620691140@wasp-sweden.org
SUMMARY:PhD Defense: Sensor Management for Target Tracking Applications
DESCRIPTION:Title: Sensor Management for Target Tracking Applications \nSpeaker: Per Boström-Rost \nOpponent: : Prof Peter Willett\, University of Connecticut \nSupervisor: Gustaf Hendeby\, LiU \nCo-supervisors: Daniel Axehill\, LiU \n\nDate: 2021-05-10 \nTime: 14:15-17:00 \nPlace: https://liu-se.zoom.us/j/67125115813?pwd=aDU0NFZOcTdyaGVHc0NGM28yMGpudz09 \nLanguage: English \nLink to thesis \n\nAbstract\nMany practical applications\, such as search and rescue operations and environmental monitoring\, involve the use of mobile sensor platforms. The workload of the sensor operators is becoming overwhelming\, as both the number of sensors and their complexity are increasing. This thesis addresses the problem of automating sensor systems to support the operators. This is often referred to as sensor management. By planning trajectories for the sensor platforms and exploiting sensor characteristics\, the accuracy of the resulting state estimates can be improved. The considered sensor management problems are formulated in the framework of stochastic optimal control\, where prior knowledge\, sensor models\, and environment models can be incorporated. The core challenge lies in making decisions based on the predicted utility of future measurements. \nIn the special case of linear Gaussian measurement and motion models\, the estimation performance is independent of the actual measurements. This reduces the problem of computing sensing trajectories to a deterministic optimal control problem\, for which standard numerical optimization techniques can be applied. A theorem is formulated that makes it possible to reformulate a class of nonconvex optimization problems with matrix-valued variables as convex optimization problems. \nThis theorem is then used to prove that globally optimal sensing trajectories can be computed using off-the-shelf optimization tools. As in many other fields\, nonlinearities make sensor management problems more complicated. Two approaches are derived to handle the randomness inherent in the nonlinear problem of tracking a maneuvering target using a mobile range-bearing sensor with limited field of view. The first approach uses deterministic sampling to predict several candidates of future target trajectories that are taken into account when planning the sensing trajectory. This significantly increases the tracking performance compared to a conventional approach that neglects the uncertainty in the future target trajectory. The second approach is a method to find the optimal range between the sensor and the target. Given the size of the sensor’s field of view and an assumption of the maximum acceleration of the target\, the optimal range is determined as the one that minimizes the tracking error while satisfying a user-defined constraint on the probability of losing track of the target. \nWhile optimization for tracking of a single target may be difficult\, planning for jointly maintaining track of discovered targets and searching for yet undetected targets is even more challenging. Conventional approaches are typically based on a traditional tracking method with separate handling of undetected targets. Here\, it is shown that the Poisson multi-Bernoulli mixture (PMBM) filter provides a theoretical foundation for a unified search and track method\, as it not only provides state estimates of discovered targets\, but also maintains an explicit representation of where undetected targets may be located. Furthermore\, in an effort to decrease the computational complexity\, a version of the PMBM filter which uses a grid-based intensity to represent undetected targets is derived.
URL:https://wasp-sweden.org/event/phd-defense-sensor-management-for-target-tracking-applications/
LOCATION:Online\, Online\, Other
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210506T151500
DTEND;TZID=+01:00:20210506T235900
DTSTAMP:20260602T130620
CREATED:20210408T150236Z
LAST-MODIFIED:20260601T083907Z
UID:10000317-1620314100-1620345540@wasp-sweden.org
SUMMARY:PhD Defense: Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments
DESCRIPTION:Title: Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments \nRespondent: Kristoffer Bergman \nOpponent: Prof. Emilio Frazzoli\, ETH Zürich \nSupervisor: Assoc. Prof. Daniel Axehill \nCo-supervisor: Prof. Torkel Glad \n\nDate: 2021-05-06 \nTime: 15:15 \nPlace: Zoom/Ada Lovelace https://liu-se.zoom.us/j/62231874057?pwd=L3orZW9XY1hNajF1by9MU2lvTkRWUT09 \nLanguage: English \nLink to thesis \n\nAbstract\nDuring the last decades\, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars\, unmanned aerial vehicles and robotic manipulators. The objective in optimal motion planning problems is to find feasible motion plans that also optimize a performance measure. From a control perspective\, the problem is an instance of an optimal control problem. This thesis addresses optimal motion planning problems for complex dynamical systems that operate in unstructured environments\, where no prior reference such as road-lane information is available. Some example scenarios are autonomous docking of vessels in harbors and autonomous parking of self-driving tractor-trailer vehicles at loading sites. The focus is to develop optimal motion planning algorithms that can reliably be applied to these types of problems. This is achieved by combining recent ideas from automatic control\, numerical optimization and robotics. \nThe first contribution is a systematic approach for computing local solutions to motion planning problems in challenging unstructured environments. The solutions are computed by combining homotopy methods and direct optimal control techniques. The general principle is to define a homotopy that transforms\, or preferably relaxes\, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments\, where the presented method outperforms a state-of-the-art asymptotically optimal motion planner based on random sampling. \nThe second contribution is an optimization-based framework for automatic generation of motion primitives for lattice-based motion planners. Given a family of systems\, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance\, the framework computes a library of motion primitives by simultaneously optimizing the motions and the terminal states. \nThe final contribution of this thesis is a motion planning framework that combines the strengths of sampling-based planners with direct optimal control in a novel way. The sampling-based planner is applied to the problem in a first step using a discretized search space\, where the system dynamics and objective function are chosen to coincide with those used in a second step based on optimal control. This combination ensures that the sampling-based motion planner provides a feasible motion plan which is highly suitable as warm-start to the optimal control step. Furthermore\, the second step is modified such that it also can be applied in a receding-horizon fashion\, where the proposed combination of methods is used to provide theoretical guarantees in terms of recursive feasibility\, worst-case objective function value and convergence to the terminal state. The proposed motion planning framework is successfully applied to several problems in challenging unstructured environments for tractor-trailer vehicles. The framework is also applied and tailored for maritime navigation for vessels in archipelagos and harbors\, where it is able to compute energy-efficient trajectories which complies with the international regulations for preventing collisions at sea. \nOriginal location: Zoom/Ada Lovelace
URL:https://wasp-sweden.org/event/phd-defense-exploiting-direct-optimal-control-for-motion-planning-in-unstructured-environments/
LOCATION:Ada Lovelace\, B-building\, Campus Valla\, Linköping University\, Ada Lovelace\, B-building\, Campus Valla\, Linköping University\, Linköping\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210310T131500
DTEND;TZID=+01:00:20210310T235900
DTSTAMP:20260602T130620
CREATED:20210217T143857Z
LAST-MODIFIED:20260601T083908Z
UID:10000319-1615382100-1615420740@wasp-sweden.org
SUMMARY:Launching WASP Research Arenas 2.0
DESCRIPTION:WASP invites industries and researchers to the launch of WARA 2.0\, introducing the updated concept\, news from all five arenas and a glimpse of what is to come. \nWASP Research Arenas (WARAs) are research collaboration platforms gathering researchers from academia and industry. Through the arenas\, the participating researchers gain exclusive access to infrastructures\, resources and competence in a context that facilitates networking and promotes knowledge transfer. \nDuring 2020 the concept of WASP Research Arenas has been rewritten\, resulting in several new\, state of the art research arenas. The new concept and arenas will officially be launched at this webinar. \nProgram\nOpening – Anders Ynnerman\, WASP Program Director\, Linköping University \nWARA 2.0 – Torbjörn Lundahl\, WARA Director\, Ericsson Research\nPresentation of the overall objective with the WARA initiative\, description of the concept and criteria for establishing WARA\, and how to propose and get approval for an arena. \nWARA Common – Johan Eker\, Ericsson Research\nWARA-common is a data center and cloud provider open for WASP researchers to build and operate their services\, deploy large scale computations\, or use in education. We also collect metrics and logs from the full cloud stack and the facilities\, for use in research projects on data-driven operations together with Ericsson. \nWARA Public Safety – Jesper Tordenlid\, Saab\nIn WARA Public Safety we provide a large scale and industrially relevant demonstration environment where heterogeneous Systems of Systems collaborate to solve tasks within Public Safety. You have access to unique autonomous vehicles and sensors in the air\, on water\, on ground and underwater as well as experienced engineers and real users. The coastal environment and scenarios within search & rescue and transportation\, offers challenges relevant for many domains. \nWARA Robotics – Jonas Larsson\, ABB Corporate Research\nThe WARA will include a multitude of manipulation tasks to give a rich set of research problems in an environment that enables robots to navigate and perform manufacturing-relevant manipulation tasks. Under realistic deployment conditions this require robots to autonomously understand the world around them\, to build knowledge incrementally\, learn new skills\, perform them safely and reliably\, and adapt to changes in the environment and humans’ behavior. \nWARA Software – Christoph Reichenbach\, Lund University\nThe WARA for Software connects software technology research between academia and industry.  Its activities focus on understanding and growing the utility of modern tools for building and improving software in the Swedish industry. The WARA constructs benchmarks and platforms for evaluating software tools\, and supports WASP PhD students in both exploiting and advancing the state of the art in software technology. \nWARA Media  – Johanna Björklund\, Umeå University\nThe mission of WARA Media is to foster a community around Media AI\, that cuts across scientific fields and industry sectors.  The research topics cover generation and classification of media\, augmentation and replication of human communication and control\, and finally verification and validation. We welcome new participants from the WASP community and the Swedish industries – please connect if interested. \nWARA NLP – Salla Franzén\, SEB\nNatural Language Processing is a foundational research area and an enabler for human machine interaction\, process automation and many other applications. The aim of the WARA NLP under planning is twofold. Firstly\, to develop a community for academic\, industrial and governmental organizations with interests in NLP applications and base research. Secondly\, to generate high-quality research in NLP in areas of importance for the WARA participants and society\, such as training large-scale language models for Nordic languages with federated learning and adapter models for transfer learning. \nInformation\nThe event will be held in English. \nDate: March 10\, 2021 \nTime: 13:15–14:15 (GMT +1) \nContact\nAny questions regarding this event can be sent to: info@wasp-sweden.org
URL:https://wasp-sweden.org/event/launching-wasp-research-arenas-2-0/
LOCATION:Online\, Online\, Other
CATEGORIES:Webinar
ATTACH;FMTTYPE=image/jpeg:https://wasp-sweden.org/wp-content/uploads/2021/02/WARA-webinar_basic_color.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210217T000000
DTEND;TZID=+01:00:20210217T235959
DTSTAMP:20260602T130620
CREATED:20210121T100808Z
LAST-MODIFIED:20260601T083909Z
UID:10000321-1613520000-1613606399@wasp-sweden.org
SUMMARY:PhD Defense: Location-aware Resource Allocation in Mobile Edge Clouds
DESCRIPTION:Chanh Nguyen Le Tan will defend his doctoral thesis “Location-aware Resource Allocation for Mobile Edge Clouds” on February 17th\, 13:00–16:00. \nOpponent: Professor Maarten Van Steen\, Univ. Twente\, The Netherlands. \nGraduation Committee:\nProfessor Ling Liu\, Georgia Institute of Technology\, US.\nProfessor Andreas Kassler\, Karlstad University\, Sweden.\nProfessor Virginia Dignum\, Umeå University\, Sweden. \nSupervisor: Erik Elmroth \nOriginal location: Umeå universitet\, Aula biologica
URL:https://wasp-sweden.org/event/phd-defense-location-aware-resource-allocation-in-mobile-edge-clouds/
LOCATION:BIO.E.203 Aula Biologica\, Umeå University\, BIO.E.203 Aula Biologica\, Umeå University\, Umeå\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210212T000000
DTEND;TZID=+01:00:20210212T235959
DTSTAMP:20260602T130620
CREATED:20201216T074711Z
LAST-MODIFIED:20260601T083910Z
UID:10000324-1613088000-1613174399@wasp-sweden.org
SUMMARY:PhD Defense: Digital Cognitive Companions for Marine Vessels - On the Path Towards Autonomous Ships
DESCRIPTION:Thesis title: Digital Cognitive Companions for Marine Vessels – On the Path Towards Autonomous Ships \nAuthor: Mårten Lager\, Department of Computer Science\, Lund university \nFaculty opponent: Professor Henrik I. Christensen\, University of California\, USA \nLocation: Online – link by registration
URL:https://wasp-sweden.org/event/phd-defense-digital-cognitive-companions-for-marine-vessels-on-the-path-towards-autonomous-ships/
LOCATION:Online\, Online\, Other
CATEGORIES:Defense
ATTACH;FMTTYPE=image/png:https://wasp-sweden.org/wp-content/uploads/2020/12/PhD-Defense-MårtenLager.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210201T140000
DTEND;TZID=+01:00:20210201T235900
DTSTAMP:20260602T130620
CREATED:20210127T103456Z
LAST-MODIFIED:20260601T083909Z
UID:10000320-1612188000-1612223940@wasp-sweden.org
SUMMARY:Lic. Thesis Seminar: Adaptiveness and Lock-free Synchronization in Parallel Stochastic Gradient Descent
DESCRIPTION:Lic. thesis seminar \nFebruary 1\, 14.00 via zoom \nKarl Bäckström\, Computer Science and Engineering\, Chalmers University of Technology\, will present his lic thesis Adaptiveness and Lock-free Synchronization in Parallel Stochastic Gradient Descent. \n 
URL:https://wasp-sweden.org/event/lic-thesis-seminar-adaptiveness-and-lock-free-synchronization-in-parallel-stochastic-gradient-descent/
LOCATION:Online\, Online\, Other
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210129T131500
DTEND;TZID=+01:00:20210129T235900
DTSTAMP:20260602T130620
CREATED:20210112T114937Z
LAST-MODIFIED:20260601T083909Z
UID:10000322-1611926100-1611964740@wasp-sweden.org
SUMMARY:Lic. Thesis Seminar: Integration of Clouds to Industrial Communication Networks
DESCRIPTION:Title: Integration of Clouds to Industrial Communication Networks \nPresenter: Haorui Peng\, Electrical and Information Technology\, LTH\, Lund University and Wallenberg AI\, Autonomous Systems and Software Program (WASP) \nReviewer: Prof. Åke Arvidsson från Kristianstad University \nWhen: 29 January 2021 at 13.15 \nLocation: Online at the zoom platform. Please register at https://www.lth.se/digitalth/events/register-2021-01-29/ in order to get an access link. \nAbstract\nCloud computing\, owing to its ubiquitousness\, scalability and on-demand ac- cess\, has transformed into many traditional sectors\, such as telecommunication and manufacturing production. As the Fifth Generation Wireless Specifications (5G) emerges\, the demand on ubiquitous and re-configurable computing resources for handling tremendous traffic from omnipresent mobile devices has been put forward. And therein lies the adaption of cloud-native model in service delivery of telecommunication networks. However\, it takes phased approaches to successfully transform the traditional Telco infrastructure to a softwarized model\, especially for Radio Access Networks (RANs)\, which\, as of now\, mostly relies on purpose-built Digital Signal Processors (DSPs) for computing and processing tasks. \nOn the other hand\, Industry 4.0 is leading the digital transformation in manufacturing sectors\, wherein the industrial networks is evolving towards wireless connectivity and the automation process managements are shifting to clouds. However\, such integration may introduce unwanted disturbances to critical industrial automation processes. This leads to challenges to guaran- tee the performance of critical applications under the integration of different systems. \nIn the work presented in this thesis\, we mainly explore the feasibility of inte- grating wireless communication\, industrial networks and cloud computing. We have mainly investigated the delay-inhibited challenges and the performance impacts of using cloud-native models for critical applications. We design a solution\, targeting at diminishing the performance degradation caused by the integration of cloud computing.
URL:https://wasp-sweden.org/event/lic-thesis-seminar-integration-of-clouds-to-industrial-communication-networks/
LOCATION:Online\, Online\, Other
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20210127T000000
DTEND;TZID=+01:00:20210127T235959
DTSTAMP:20260602T130620
CREATED:20201218T072742Z
LAST-MODIFIED:20260601T083910Z
UID:10000323-1611705600-1611791999@wasp-sweden.org
SUMMARY:Webinar: WASP Industrial PhD Student Call
DESCRIPTION:Interested in WASP’s upcoming Industrial PhD Student call? Join our webinar to learn more! \nWASP invites everyone interested in the upcoming WASP Industrial PhD Student Call to an information webinar on January 27th\, 2021\, 13:15-15:15. The webinar will be held through Zoom. If you wish to attend\, please register through the link below. You will receive a meeting invitation a couple of days before the webinar. \nAbout the WASP Industrial PhD Student Call\nWASP is offering up to 10 industrial doctoral student positions within AI\, Autonomous Systems and Software at the five partner universities Chalmers\, KTH\, Linköping University\, Lund University and Umeå University as well as the research groups at Örebro University and Uppsala University that are members of WASP AI. The industrial partner should have research activities in Sweden. \nThe projects are expected to address fundamental research problems within any of WASP’s research areas and expect to have a strong visionary and novelty nature\, i.e.\, not only application development. The call opens January 25th\, 2021. \nWASP industrial PhD students will be part of the WASP graduate school. The graduate school is making efforts to actively attract industrial PhD students. To make the industrial PhD studies relevant to companies\, courses offered in the program are tailored to meet the future needs in industry. \nAbout Industrial PhD studies\nIn our Industrial PhD Report\, an overall comment from the editors is the possibilities for industry to think of industrial PhD students as a strategic instrument. The main types of results for participating industry are partly concrete in the form of research results and a doctoral degree but also\, as shown in recent research\, participating industries improve their overall innovation capability.
URL:https://wasp-sweden.org/event/webinar-wasp-industrial-phd-student-call/
LOCATION:Online\, Online\, Other
CATEGORIES:Webinar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20201210T150000
DTEND;TZID=+01:00:20201210T235900
DTSTAMP:20260602T130620
CREATED:20201113T114820Z
LAST-MODIFIED:20260601T083911Z
UID:10000325-1607612400-1607644740@wasp-sweden.org
SUMMARY:Autonomous Vehicle Maneuvering at the Limit of Friction
DESCRIPTION:Title: Autonomous Vehicle Maneuvering at the Limit of Friction\nRespondent: Victor Fors\nDivision: Vehicular Systems at the Department of Electrical Engineering\, Linköping University\nSupervisors: Lars Nielsen\, Björn Olofsson\, Jan Åslund\nOpponent: Professor J. Christian Gerdes\, Department of Mechanical Engineering\, Stanford University\, CA\, US\nDate and time: 2020-12-10\, 15:00\nPlace: Online via Zoom (can be viewed in Ada Lovelace\, B-building\, Campus Valla\, Linköping University) \nJoin Zoom Meeting https://liu-se.zoom.us/j/65015486154?pwd=eFhNMHFkcTNMOGNNQ1NZUWplV3MvZz09 \nAbstract: \nWithout a driver to fall back on\, a fully self-driving car needs to be able to handle any situation it can encounter. With the perspective of future safety systems\, this research studies autonomous maneuvering at the tire–road friction limit. In these situations\, the dynamics is highly nonlinear\, and the tire–road parameters are uncertain. \nTo gain insights into the optimal behavior of autonomous safety-critical maneuvers\, they are analyzed using optimal control. Since analytical solutions of the studied optimal control problems are intractable\, they are solved numerically. An optimization formulation reveals how the optimal behavior is influenced by the total amount of braking. By studying how the optimal trajectory relates to the attainable forces throughout a maneuver\, it is found that maximizing the force in a certain direction is important. This is like the analytical solutions obtained for friction-limited particle models in earlier research\, and it is shown to result in vehicle behavior close to the optimal also for a more complex model. \nBased on the insights gained from the optimal behavior\, controllers for autonomous safety maneuvers are developed. These controllers are based on using acceleration-vector references obtained from friction-limited particle models. Exploiting that the individual tire forces tend to be close to their friction limits\, the desired tire slip angles are determined for a given acceleration-vector reference. This results in controllers capable of operating at the limit of friction at a low computational cost and reduces the number of vehicle parameters used. For straight-line braking\, ABS can intervene to reduce the braking distance without prior information about the road friction. Inspired by this\, a controller that uses the available actuation according to the least friction necessary to avoid a collision is developed\, resulting in autonomous collision avoidance without any estimation of the tire–road friction. \nInvestigating time-optimal lane changes\, it is found that a simple friction-limited particle model is insufficient to determine the desired acceleration vector\, but including a jerk limit to account for the yaw dynamics is sufficient. To enable a tradeoff between braking and avoidance with a more general obstacle representation\, the acceleration-vector reference is computed in a receding-horizon framework. \nThe controllers developed in this thesis show great promise with low computational cost and performance not far from that obtained offline by using numerical optimization when evaluated in high-fidelity simulation.
URL:https://wasp-sweden.org/event/autonomous-vehicle-maneuvering-at-the-limit-of-friction/
LOCATION:Online\, Online\, Other
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20201130T123000
DTEND;TZID=+01:00:20201201T235900
DTSTAMP:20260602T130620
CREATED:20200206T120505Z
LAST-MODIFIED:20260601T083914Z
UID:10000334-1606739400-1606867140@wasp-sweden.org
SUMMARY:WASP Virtual Industry Meeting 2020
DESCRIPTION:We invite industry\, WASP researchers and WASP PhD students for two virtual days of research ideas exchanges and networking. \nThis is a two-day event with the purpose to identify\, initiate and catalyze exchanges and collaborations between WASP researchers and industry*. \nDay one is devoted to addressing business and industry challenge driven research problems in scientific thematic discussions between WASP researchers and researchers from the industry*. The second day is a job fair where participating companies are invited to sign up for short meetings with WASP PhD students to inspire and engage in career discussions. \n*Swedish Industry with R&D operations in Sweden. \nTimeline\nOctober 1st Registration opens \nOctober 30th Registration deadline\nNovember 6th Participation will be confirmed\nNovember 25th Deadline for industry representatives to book time slots with PhD students (a separate invitation will be sent out during week 47)
URL:https://wasp-sweden.org/event/wasp-virtual-industry-meeting-2020/
LOCATION:Online\, Online\, Other
CATEGORIES:Conference
ATTACH;FMTTYPE=image/jpeg:https://wasp-sweden.org/wp-content/uploads/2020/02/Industrymeeting_new_virtual_basic.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20201105T100000
DTEND;TZID=+01:00:20201105T235900
DTSTAMP:20260602T130620
CREATED:20200305T115145Z
LAST-MODIFIED:20260601T083913Z
UID:10000331-1604570400-1604620740@wasp-sweden.org
SUMMARY:WASP4ALL 2020 - Virtual Worlds for Artificial Intelligence
DESCRIPTION:Are you looking for WASP4ALL 2021? Click here. \nOur flagship conference WASP4ALL this year presents high-profile international speakers\, and researchers from WASP and Swedish industry on the topic “Virtual Worlds for Artificial Intelligence”. \nTogether we will explore how simulation and artificially generated environments can facilitate machine learning and other AI-development. If you are interested in technology\, methods\, challenges and problems – this is a conference you don’t want to miss! \nThe conference is an open\, virtual conference\, not limited to the WASP community. \nThe number of participants is limited – first come-first serve \n  \n\nWASP\, the Wallenberg AI\, Autonomous Systems and Software Program is the largest research program in Sweden ever. WASP4ALL is our yearly flagship conference with 400+ participants from academia and industry. 
URL:https://wasp-sweden.org/event/wasp4all-2020-virtual-worlds-for-artificial-intelligence/
LOCATION:Online\, Online\, Other
CATEGORIES:Conference
ATTACH;FMTTYPE=image/jpeg:https://wasp-sweden.org/wp-content/uploads/2020/03/huvudbild_virtual-worlds-for-artificial-intelligence_v2_final.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20201013T130000
DTEND;TZID=+01:00:20201014T235900
DTSTAMP:20260602T130620
CREATED:20200924T075931Z
LAST-MODIFIED:20260601T083911Z
UID:10000326-1602594000-1602719940@wasp-sweden.org
SUMMARY:First WASP Workshop on Large-Scale Optimization for Autonomy
DESCRIPTION:The First WASP Workshop on Large-Scale Optimization for Autonomy and Learning (LSOAL) will be held October 13-14\, 2020 at KTH. It will be arranged as a hybrid conference\, where those who prefer can attend via a Zoom Webinar. There will be a strict limit on the number of participants on-site. \nWe are looking forward to an exciting workshop where we can exchange ideas on large-scale optimization from theory to applications. The workshop is not limited to autonomy and learning\, but we expect a strong interest in this area. \n  \nWelcome\, \nBo Wahlberg (KTH) and Anders Hansson (LiU) \n\n 
URL:https://wasp-sweden.org/event/first-wasp-workshop-on-large-scale-optimization-for-autonomy/
LOCATION:Online\, Online\, Other
CATEGORIES:Workshop
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200914T130000
DTEND;TZID=+01:00:20200917T235900
DTSTAMP:20260602T130620
CREATED:20200225T102618Z
LAST-MODIFIED:20260601T083913Z
UID:10000332-1600088400-1600387140@wasp-sweden.org
SUMMARY:WARA-PS Field Test and Data Collection
DESCRIPTION:Original location: Gränsö slott\, Västervik
URL:https://wasp-sweden.org/event/wara-ps-field-test-and-data-collection/
LOCATION:Gränsö Slott\, Västervik\, Gränsö Slott\, Västervik\, Västervik\, Sweden
CATEGORIES:Workshop
ATTACH;FMTTYPE=image/jpeg:https://wasp-sweden.org/wp-content/uploads/2019/11/32454_WASPVastervik2019094KDJI_0679MP400_00_23_06Still002_50045_12-1024x576.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200821T000000
DTEND;TZID=+01:00:20200821T235959
DTSTAMP:20260602T130620
CREATED:20200507T083024Z
LAST-MODIFIED:20260601T083911Z
UID:10000327-1597968000-1598054399@wasp-sweden.org
SUMMARY:Veronika Domova – Designing Visualization and Interaction for Industrial Control Rooms of the Future
DESCRIPTION:Location to be decided. \nTentative abstract: \nDuring the last decades\, the industry has been undergoing extensive digitization leading to complex ensembles of humans\, machines\, autonomous agents\, and sensors. With this new setup comes the challenge of how to appropriately support work-practices of industrial operators who now need to monitor and control complex industrial processes through remote interfaces. Information overflow and restrictive interfaces are two significant problems that operators face in their daily routines. In this PhD\, I explore approaches to visualization and interaction that would reduce industrial operators’ information load and enable them to perform their duties in an efficient\, reliable\, and safe manner. The industrial user and the context are the starting points of my research. \nIn this thesis\, I describe multiple examples of custom-tailored data visualizations that reduce the operator’s visual load by consolidating large amounts of data into compact overview displays with often nontrivial data presentation. With respect to interaction\, I propose several tangible and tactile interfaces\, as well as concepts for natural interaction\, that let the user freely interact with the control station rather than be its prisoner. Finally\, I propose several concepts of adaptive systems that adjust to the operator’s context to ensure their high situational awareness and convenience of interaction. \nEven though this thesis is primarily intended for the community of interaction designers\, I expect it to be of interest to a broader audience due to its relation to the user experience field. To a certain extent\, everyone can resonate with the user’s problems because\, in our everyday life\, we all are users of some technology and services. Furthermore\, for a lay reader\, this work lifts the veil of mystery from the industrial domain and can be seen as a comprehensive introduction to how the industry works and what role the human plays there. \n  \nBetygsnämnd \nProfessor Virpi Roto\, Aalto University \nProfessor Morten Fjeld\, Chalmers \nDocent Erik Prytz\, LiU \n  \nOpponent \nProfessor Thomas Porathe\, NTNU Trondheim
URL:https://wasp-sweden.org/event/veronika-domova-designing-visualization-and-interaction-for-industrial-control-rooms-of-the-future/
LOCATION:Location TBD\, Location TBD\, Other\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200529T101500
DTEND;TZID=+01:00:20200529T235900
DTSTAMP:20260602T130620
CREATED:20200507T081432Z
LAST-MODIFIED:20260601T083912Z
UID:10000328-1590747300-1590796740@wasp-sweden.org
SUMMARY:Oskar Ljungqvist – Motion Planning and Feedback Control Techniques with Applications to Long Tractor-Trailer Vehicles
DESCRIPTION:Title: Motion planning and feedback control techniques with applications to long tractor-trailer vehicles \nRespondent: Oskar Ljungqvist\, WASP affiliated PhD student \nOpponent: Prof. Sebastien Gros \nSupervisor: Associate Prof. Daniel Axehill \nCo-supervisors: Associate Prof. Johan Löfberg \nPlace: Online via Zoom. Join Zoom Meeting https://liu-se.zoom.us/j/61330592701 Meeting ID: 613 3059 2701 Password: 300553 \nLanguage: English \nAbstract\nDuring the last decades\, improved sensor and hardware technologies as well as new methods and algorithms have made self-driving vehicles a realistic possibility in the near future. At the same time\, there has been a growing demand within the transportation sector to increase efficiency and to reduce the environmental impact related to transportation of people and goods. Therefore\, many leading automotive and technology companies have turned their attention towards developing advanced driver assistance systems and self-driving vehicles. \nAutonomous vehicles are expected to have their first big impact in closed environments\, such as mines\, harbors\, loading and offloading sites. In such areas\, the legal requirements are less restrictive and the surrounding environment is more controlled and predictable compared to urban areas. Expected positive outcomes include increased productivity and safety\, reduced emissions and the possibility to relieve the human from performing complex or dangerous tasks. Within these sites\, tractor-trailer vehicles are frequently used for transportation. These vehicles are composed of several interconnected vehicle segments\, and are therefore large\, complex and unstable while reversing. This thesis addresses the problem of designing efficient motion planning and feedback control techniques for such systems. \nThe contributions of this thesis are within the area of motion planning and feedback control for long tractor-trailer combinations operating at low-speeds in closed and unstructured environments. It includes development of motion planning and feedback control frameworks\, structured design tools for guaranteeing closed-loop stability and experimental validation of the proposed solutions through simulations\, lab and field experiments. Even though the primary application in this work is tractor-trailer vehicles\, many of the proposed approaches can with some adjustments also be used for other systems\, such as drones and ships. \nThe developed sampling-based motion planning algorithms are based upon the probabilistic closed-loop rapidly exploring random tree (CL-RRT) algorithm and the deterministic lattice-based motion planning algorithm. It is also proposed to use numerical optimal control offline for precomputing libraries of optimized maneuvers as well as during online planning in the form of a warm-started optimization step. \nTo follow the motion plan\, several predictive path-following control approaches are proposed with different computational complexity and performance. Common for these approaches are that they use a path-following error model of the vehicle for future predictions and are tailored to operate in series with a motion planner that computes feasible paths. The design strategies for the path-following approaches include linear quadratic (LQ) control and several advanced model predictive control (MPC) techniques to account for physical and sensing limitations. To strengthen the practical value of the developed techniques\, several of the proposed approaches have been implemented and successfully demonstrated in field experiments on a full-scale test platform. To estimate the vehicle states needed for control\, a novel nonlinear observer is evaluated on the full-scale test vehicle. It is designed to only utilize information from sensors that are mounted on the tractor\, making the system independent of any sensor mounted on the trailer.
URL:https://wasp-sweden.org/event/oskar-ljungqvist-motion-planning-and-feedback-control-techniques-with-applications-to-long-tractor-trailer-vehicles/
LOCATION:Online\, Online\, Other
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200526T130000
DTEND;TZID=+01:00:20200528T235900
DTSTAMP:20260602T130620
CREATED:20200225T102324Z
LAST-MODIFIED:20260601T083914Z
UID:10000333-1590498000-1590710340@wasp-sweden.org
SUMMARY:POSTPONED WARA-PS Field Test and Data Collection
DESCRIPTION:Important information \nDue to the current situation with COVID-19 we regret to inform that this event has been postponed. \n  \n  \nWe will meet and do field tests in WASP Public Safety Research Arena. Research projects will be tested and data collected. PhD students and supervisors will be invited for inspiring workshops where our core team and platforms will be available. Activities will be based on research needs and we encourage supervisors and students to contact WARA-PS with your requests and interest. More info will come. \nTime: May 26 13.00 – May 28 13.00 \nLocation: Gränsö slott\, Västervik \nOriginal location: Gränsö slott\, Västervik
URL:https://wasp-sweden.org/event/postponed-wara-ps-field-test-and-data-collection/
LOCATION:Gränsö Slott\, Västervik\, Gränsö Slott\, Västervik\, Västervik\, Sweden
CATEGORIES:Workshop
ATTACH;FMTTYPE=image/jpeg:https://wasp-sweden.org/wp-content/uploads/2019/11/32454_WASPVastervik2019094KDJI_0679MP400_00_23_06Still002_50045_12-1024x576.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200429T131500
DTEND;TZID=+01:00:20200429T235900
DTSTAMP:20260602T130620
CREATED:20200406T131036Z
LAST-MODIFIED:20260601T083912Z
UID:10000329-1588166100-1588204740@wasp-sweden.org
SUMMARY:Olov Andersson – Learning to Make Safe Real-Time Decisions Under Uncertainty for Autonomous Robots
DESCRIPTION:Abstract\nRobots are increasingly expected to go beyond controlled environments in laboratories and factories\, to act autonomously in real-world workplaces and public spaces. Autonomous robots navigating the realworld have to contend with a great deal of uncertainty\, which poses additional challenges. Uncertainty in the real world accrues from several sources. Some of it may originate from imperfect internal models of reality. Other uncertainty is inherent\, a direct side effect of partial observability induced by sensor limitations and occlusions. \nRegardless of the source\, the resulting decision problem is unfortunately computationally intractable under uncertainty. This poses a great challenge as the real world is also dynamic. It will not pause while the robot computes a solution. Autonomous robots navigating among people\, for example in traffic\, need to be able to make split-second decisions. Uncertainty is therefore often neglected in practice\, with potentially catastrophic consequences when something unexpected happens. \nThe aim of this thesis is to leverage recent advances in machine learning to compute safe real-time approximations to decision-making under uncertainty for realworld robots. We explore a range of methods\, from probabilistic to deep learning\, as well as different combinations with optimization-based methods from robotics\, planning and control. Driven by applications in robot navigation\, and grounded in experiments with real autonomous quadcopters\, we address several parts of this problem. From reducing uncertainty by learning better models\, to directly approximating the decision problem itself\, all the while attempting to satisfy both the safety and real-time requirements of real-world autonomy. \n————————————————– \nThis work has been supported by the Wallenberg AI\, Autonomous Systems and Software Program\, the Swedish Foundation for Strategic Research (SSF) project Symbicloud and the ELLIIT Excellence Center at Linköping-Lund for Information Technology\, in addition to those sources already acknowledged in the individual papers. \nOriginal location: Linköping University\, Online Disputation
URL:https://wasp-sweden.org/event/olov-andersson-learning-to-make-safe-real-time-decisions-under-uncertainty-for-autonomous-robots/
LOCATION:Linköping University\, Linköping University\, Linköping\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200415T133000
DTEND;TZID=+01:00:20200415T235900
DTSTAMP:20260602T130620
CREATED:20200406T130241Z
LAST-MODIFIED:20260601T083913Z
UID:10000330-1586957400-1586995140@wasp-sweden.org
SUMMARY:Rebekka Wohlrab – Living Boundary Objects to Support Agile Inter-Team Coordination at Scale
DESCRIPTION:Context: In the last decades\, large-scale agile development has received increasing attention\, as also organizations with many stakeholders and large systems aim for higher development speed and focus on customer value. A recognized research challenge in large-scale agile development relates to inter-team coordination. To coordinate effectively\, organizations need to identify what knowledge is required across team borders and how it can be managed over time. Knowledge is potentially manifested in boundary objects – artifacts that create a shared understanding between teams (e.g.\, requirements or architecture descriptions). Traceability between artifacts is a key necessity to manage change in agile contexts. Moreover\, agile practitioners aim to reduce the documentation effort to absolutely crucial artifacts and trace links. \nObjective: This thesis aims to improve how practitioners can manage knowledge for inter-team coordination in large-scale agile development. We focus especially on how knowledge can be made explicit in artifacts and trace links that are evolved over time. \nMethod: We empirically investigated problems and developed solutions using a research approach that was inspired by design science. Case studies\, an in-depth design science study\, a mixed methods study\, and surveys were performed. Using this mix of research methods\, we leveraged both qualitative and quantitative data. \nResults: We coined the concept of living boundary objects to manage knowledge for inter-team coordination. Living boundary objects are boundary objects that are traced to other artifacts\, kept up to date\, and serve for inter-team coordination. They should be established early in the lifecycle to create a common understanding of the product to be developed. We scrutinized architecture descriptions\, interfaces\, and requirements and traceability information models as examples of concrete boundary objects. We recommend establishing alignment using a common high-level structure\, but also supporting diverse knowledge management practices to fulfill the individual needs of agile teams. \nConclusions: Our contributions help to establish knowledge management practices that are considered beneficial by practitioners and focus on the crucial aspects to align agile teams on. We suggest concepts and requirements for knowledge management tools that take the distinct role of living boundary objects into consideration and can be adjusted as organizations’ needs evolve. \nOriginal location: Online Disputation
URL:https://wasp-sweden.org/event/rebekka-wohlrab-living-boundary-objects-to-support-agile-inter-team-coordination-at-scale/
LOCATION:Online\, Online\, Other
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200207T131500
DTEND;TZID=+01:00:20200207T235900
DTSTAMP:20260602T130620
CREATED:20191220T095818Z
LAST-MODIFIED:20260601T083915Z
UID:10000336-1581081300-1581119940@wasp-sweden.org
SUMMARY:Timing-Based Localization using Multipath Information
DESCRIPTION:Degree and subject: Licentiate in Electrical Engineering with specialization in Automatic Control \nSpeaker: Andreas Bergström \nOpponent: Dr. Erik Leitinger\, TU Graz \nSupervisor: Prof. Fredrik Gustafsson \nCo-supervisors: Assoc. Prof. Gustaf Hendeby and Assoc. Prof. Fredrik Gunnarsson \nLanguage: English \nAbstract\nThe measurements of radio signals are commonly used for localization purposes where the goal is to determine the spatial position of one or multiple objects. In realistic scenarios\, any transmitted radio signal will be affected by the environment through reflections\, diffraction at edges and corners etc. This causes a phenomenon known as multipath propagation\, by which multiple instances of the transmitted signal having traversed different paths are heard by the receiver. These are known as Multi-Path Components (MPCs). The direct path (DP) between transmitter and receiver may also be occluded\, causing what is referred to as non-Line-of-Sight (non-LOS) conditions. As a consequence of these effects\, the estimated position of the object(s) may often be erroneous. \nThis thesis focuses on how to achieve better localization accuracy by accounting for the above-mentioned multipath propagation and non-LOS effects. It is proposed how to mitigate these in the context of positioning based on estimation of the DP between transmitter and receiver. It is also proposed how to constructively utilize the additional information about the environment which they implicitly provide. This is all done in a framework wherein a given signal model and a map of the surroundings are used to build a mathematical model of the radio environment\, from which the resulting MPCs are estimated. \nFirst\, methods to mitigate the adverse effects of multipath propagation and non-LOS conditions for positioning based on estimation of the DP between transmitter and receiver are presented. This is initially done by using robust statistical measurement error models based on aggregated error statistics\, where significant improvements are obtained without the need to provide detailed received signal information. The gains are seen to be even larger with up-to-date real-time information based on the estimated MPCs. \nSecond\, the association of the estimated MPCs with the signal paths predicted by the environmental model is addressed. This leads to a combinatorial problem which is approached with tools from multi-target tracking theory. A rich radio environment in terms of many MPCs gives better localization accuracy but causes the problem size to grow large — something which can be remedied by excluding less probable paths. Simulations indicate that in such environments\, the single best association hypothesis may be a reasonable approximation which avoids the calculation of a vast number of possible hypotheses. Accounting for erroneous measurements is crucial but may have drawbacks if no such are occurring. \nFinally\, theoretical localization performance bounds when utilizing all or a subset of the available MPCs are derived. A rich radio environment allows for good positioning accuracy using only a few transmitters/receivers\, assuming that these are used in the localization process. In contrast\, in a less rich environment where basically only the DP/LOS components are measurable\, more transmitters/receivers and/or the combination of downlink and uplink measurements are required to achieve the same accuracy. The receiver’s capability of distinguishing between multiple MPCs arriving approximately at the same time also affects the localization accuracy.
URL:https://wasp-sweden.org/event/timing-based-localization-using-multipath-information/
LOCATION:Ada Lovelace\, B-building\, Campus Valla\, Linköping University\, Ada Lovelace\, B-building\, Campus Valla\, Linköping University\, Linköping\, Sweden
CATEGORIES:Defense
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=+01:00:20200124T131500
DTEND;TZID=+01:00:20200124T235900
DTSTAMP:20260602T130620
CREATED:20191216T130039Z
LAST-MODIFIED:20260601T083916Z
UID:10000337-1579871700-1579910340@wasp-sweden.org
SUMMARY:Webinar – Call for Industrial PhD Students
DESCRIPTION:Here you can see the recording of the webinar. \n  \nInterested in WASP’s upcoming Industrial PhD call within AI? Join our webinar to learn more! \nWASP invites everyone interested in the upcoming WASP AI Industrial PhD Call to an information webinar at January 24th\, 2020\, 13:15-15:00. The webinar will be held through Zoom. If you wish to attend\, please register through the link below. You will receive a meeting invitation a couple of days before the webinar. \nAbout the WASP AI Industrial PhD Call\nWASP is offering up to 15 industrial doctoral student positions within AI in 2020. The positions are offered at the five partner universities Chalmers\, KTH\, Linköping University\, Lund University and Umeå University\, as well as at the research groups at Örebro University and Uppsala University that are members of WASP AI. The projects are expected to address fundamental research problems within AI and expect to have a strong visionary and novelty nature. The call opens January 20th\, 2020. \nWASP industrial PhD students will be part of the WASP graduate school. The graduate school is making efforts to actively attract industrial PhD students. To make the industrial PhD studies relevant to companies\, courses offered in the program are tailored to meet the future needs in industry. \nAbout Industrial PhD studies\nIn our recently published Industrial PhD Report\, an overall comment from the editors is the possibilities for industry to think of industrial PhD students as a strategic instrument. The main types of results for participating industry are partly concrete in the form of research results and a doctoral degree but also\, as shown in recent research\, participating industries improve their overall innovation capability. \nWebinar Program\n\n\n\n13:15\nIntroduction by Anders Ynnerman\, Linköping University (WASP) and Danica Kragic\, KTH (WASP AI)\n\n\n13:30\nGeneral presentation about WASP Industrial PhD program\, Karl-Erik Årzén\, Lund University\n\n\n13:55\n WASP AI graduate school\, Amy Loutfi\, Örebro University\n\n\n14:15\nPerspectives from a WASP Industrial Supervisor and a WASP Industrial PhD student\, Salla Franzén and Ciwan Ceylan SEB\n\n\n14:45\n Questions and discussion\n\n\n15:00\nWrap up\n\n\n\nPlease register to the webinar no later than January 20th. A link to the webinar will be sent to all registered participants January 21st.
URL:https://wasp-sweden.org/event/webinar-call-for-industrial-phd-students/
CATEGORIES:Webinar
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DTSTART;TZID=+01:00:20200116T000000
DTEND;TZID=+01:00:20200116T235959
DTSTAMP:20260602T130620
CREATED:20200109T103605Z
LAST-MODIFIED:20260601T083915Z
UID:10000335-1579132800-1579219199@wasp-sweden.org
SUMMARY:Designing for machine learning in medical image diagnostics – Enabling efficient ensembles of professional medical practitioners and learning machines through interaction design
DESCRIPTION:WASP industrial PhD student Martin Lindvall is having his halftime seminar. A halftime seminar is the equivalent of a licentiate seminar\, where Martin will be presenting his ongoing PhD work and discuss it with docent Ylva Fernaeus of KTH\, our external discussant. \nTitle\nDesigning for machine learning in medical image diagnostics — Enabling efficient ensembles of professional medical practitioners and learning machines through interaction design \nAbstract\nAdvancements in machine learning (ML) has led to a dramatic increase in AI capabilities for medical diagnostic tasks. However\, despite impressive technical advances\, predictive algorithms are to a very small extent used in healthcare today. A lack of design considerations and inefficient human-AI collaborations has been identified as a major factor limiting adoption in clinical settings. \nUsing a constructive design research approach\, my work explores how we might design systems with ML components that aid clinical decision-making. Preliminary results are derived from experiments and experiences from four projects\, all aiming to produce novel interactive systems for or with ML components. \nPreliminary contributions consist of identifying design challenges and suitable interaction strategies for human-ML collaboration at different stages of automatic support. Specifically\, I present three works that address challenges in designing for effective human-machine teaching and two in-progress works that address the challenge of designing interactions that afford successful collaborative strategies despite the uncertainty inherent in machine predictions. \nOriginal location: KO301\, Campus Norrköping\, Kopparhammaren 2\, Third floor
URL:https://wasp-sweden.org/event/designing-for-machine-learning-in-medical-image-diagnostics-enabling-efficient-ensembles-of-professional-medical-practitioners-and-learning-machines-through-interaction-design/
LOCATION:Campus Norrköping\, Linköping University\, Campus Norrköping\, Linköping University\, Norrköping\, Sweden
CATEGORIES:Seminar
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DTSTART;TZID=+01:00:20200113T120000
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DTSTAMP:20260602T130620
CREATED:20191108T124025Z
LAST-MODIFIED:20260601T083918Z
UID:10000344-1578916800-1579132740@wasp-sweden.org
SUMMARY:WASP Winter Conference 2020
DESCRIPTION:Winter Conference at Konsert & Kongress in Linköping.\nThe winter conference is an internal WASP conference held in January every year. It includes a kick-off for new PhD students and new supervisors\, in which an introduction is given to the WASP graduate school and related activities. In the conference part\, WASP research results are presented by the PhD students. Also\, shorter and longer talks are given on WASP-related topics. After the actual conference\, the WASP clusters meet to plan for the coming year. \nThis three-day event provides an excellent opportunity to get an overview of WASP’s graduate school and research results. It is mandatory for the PhD students and it is the only recurring occasion where the whole WASP community gathers. Please see the internal webpage for detailed information. \nProgram\nJanuary 13th\n12:00-13:00 Lunch\n13:00-17:00 Kick-off  (new PhD students and supervisors)\n19:00 Kick-off Dinner \nJanuary 14th\n09:00-10:00 Kick-off (cont.)\n10:00-10:30 Get-together Coffee\n10:30-17:00 WASP Conference including lunch (everyone in WASP)\n19:00 Conference dinner \nJanuary 15th\n09:00-12:00 WASP Conference (cont.)\n12:00-13:00 Lunch\n13:00-15:00 Separate WASP Cluster meetings (primarily for PhD students but everyone is welcome)
URL:https://wasp-sweden.org/event/wasp-winter-conference-2020/
LOCATION:Konsert & Kongress\, Linköping\, Konsert & Kongress\, Linköping\, Linköping\, Sweden
CATEGORIES:Conference
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