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This course is an archived course. It remains open to registrations although it is not facilitated by the course teachers: its contents are no longer updated and may therefore no longer be up to date (course contents were created in 2015). If you register, you can freely consult the read-only resources but all collaborative spaces are closed (forums, wiki and other collaborative exercises): you cannot interact with the teaching team or with other learners. Furthermore, no attestation of achievement will be delivered for this course.
About This Course
Mobile Robots are increasingly working in close interaction with human beings in environments as diverse as homes, hospitals, public spaces, public transportation systems and disaster areas. The situation is similar when it comes to Autonomous Vehicles, which are equipped with robot-like capabilities (sensing, decision and control).
Such robots must balance constraints such as safety, efficiency and autonomy, while addressing the novel problems of acceptability and human-robot interaction. Given the high stakes involved, developing these technologies is clearly a major challenge for both the industry and the human society.
Overview
Syllabus
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Course Syllabus
Week 1
OBJECTIVES, CHALLENGES, STATE OF THE ART
Week 2
BAYES & KALMAN FILTERS
Week 3
EXTENDED KALMAN FILTERS
Week 4
PERCEPTION & SITUATION AWARENESS & DECISION MAKING
Week 5
BEHAVIOR MODELING AND LEARNING (with examples and exercises in Python)
