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X-WR-CALNAME:WASP
X-ORIGINAL-URL:https://wasp-sweden.org
X-WR-CALDESC:Events for WASP
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TZID:+01:00
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BEGIN:VEVENT
DTSTART;TZID=+01:00:20190903T000000
DTEND;TZID=+01:00:20190903T235959
DTSTAMP:20260602T152248
CREATED:20190708T152028Z
LAST-MODIFIED:20260601T083919Z
UID:10000346-1567468800-1567555199@wasp-sweden.org
SUMMARY:WARA-PS Preparation workshop
DESCRIPTION:By invitation only \nThe WARA-PS Core team and WASP PhD students integrates\, tests and collect data for research and preparation for the September demonstration two weeks later. During these days autonomous boats\, drones and sensors will be tested together with cloud based services for delegation and command and control systems.
URL:https://wasp-sweden.org/event/wara-ps-preparation-workshop/
LOCATION:Gränsö Slott\, Västervik\, Gränsö Slott\, Västervik\, Västervik\, Sweden
CATEGORIES:Workshop
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BEGIN:VEVENT
DTSTART;TZID=+01:00:20190614T000000
DTEND;TZID=+01:00:20190614T235959
DTSTAMP:20260602T152248
CREATED:20191112T103938Z
LAST-MODIFIED:20260601T083917Z
UID:10000340-1560470400-1560556799@wasp-sweden.org
SUMMARY:On Motion Planning Using Numerical Optimal Control
DESCRIPTION:Defense by Kristoffer Bergman\nFor: Licentiate in automatic control\nTitle: On Motion Planning Using Numerical Optimal Control\nDate and Time: 2019-06-14\nLocation: Ada Lovelace\, B-building\, Linköpings University\nOpponent: Assoc. Prof. Paolo Falcone\, Chalmers\nSupervisor: Assoc. Prof. Daniel Axehill\nCo-supervisors: Prof. Torkel Glad \nOriginal location: Ada Lovelace\, B-building\, Linköpings University
URL:https://wasp-sweden.org/event/on-motion-planning-using-numerical-optimal-control/
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=+01:00:20190605T100000
DTEND;TZID=+01:00:20190605T235900
DTSTAMP:20260602T152248
CREATED:20190531T082636Z
LAST-MODIFIED:20260601T083919Z
UID:10000347-1559728800-1559779140@wasp-sweden.org
SUMMARY:Tactical decision-making for autonomous driving: A reinforcement learning approach
DESCRIPTION:Defense by Carl-Johan Hoel\nFor: Licentiate of Engineering in Adaptive systems\nLocation: Lecture hall FB\, Fysikgården 4\, Chalmers University of Technology\, Göteborg \nDiscussion leader: Associate Professor Christos Dimitrakakis\, Department of Computer Science and Engineering\, Chalmers.\nSupervisors: Associate Professor Krister Wolff (Chalmers)\, Adjunct Professor Leo Laine (AB Volvo).\nExaminer: Professor Mattias Wahde \nThe tactical decision-making task of an autonomous vehicle is challenging\, due to the diversity of the environments the vehicle operates in\, the uncertainty in the sensor information\, and the complex interaction with other road users. This thesis introduces and compares three general approaches\, based on reinforcement learning\, to creating a tactical decision-making agent. The first method uses a genetic algorithm to automatically generate a rule based decision-making agent\, whereas the second method is based on a Deep QNetwork agent. The third method combines the concepts of planning and learning\, in the form of Monte Carlo tree search and deep reinforcement learning. The three approaches are applied to several highway driving cases in a simulated environment and outperform a commonly used baseline model by taking decisions that allow the vehicle to navigate 5% to 10% faster through dense traffic. However\, the main advantage of the methods is their generality\, which is indicated by applying them to conceptually different driving cases. Furthermore\, this thesis introduces a novel way of applying a convolutional neural network architecture to a high level state description of interchangeable objects\, which speeds up the learning process and eliminates all collisions in the test cases. \nOriginal location: Chalmers University of Technology\, Göteborg
URL:https://wasp-sweden.org/event/tactical-decision-making-for-autonomous-driving-a-reinforcement-learning-approach/
LOCATION:Chalmers University of Technology\, Chalmers University of Technology\, Göteborg\, Sweden
CATEGORIES:Defense
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