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.
OBJECTIVES, CHALLENGES, STATE OF THE ART
BAYES & KALMAN FILTERS
EXTENDED KALMAN FILTERS
PERCEPTION & SITUATION AWARENESS & DECISION MAKING
BEHAVIOR MODELING AND LEARNING
Dizan Vasquez, Agostino Martinelli and Christian Laugier