Title: Robot Navigation in Dense Human Crowds: the Case for Cooperation
Authors: Pete Trautman, Jeremy Ma, Richard M. Murray and Andreas Krause
in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2013)
Abstract:
... we explore two questions. Can we design a navigation
algorithm that encourages humans to cooperate with a robot? Would such
cooperation improve navigation performance? We address the first
question by developing a probabilistic predictive model of cooperative
collision avoidance and goal-oriented behavior. ... We
answer the second question by empirically validating our model in a
natural environment (a university cafeteria), and in the process, carry
out the first extensive quantitative study of robot navigation in dense
human crowds (completing 488 runs). The “multiple goal” interacting
Gaussian processes algorithm performs comparably with human
teleoperators in crowd densities near 1 person/m2, while a state of the
art noncooperative planner exhibits unsafe behavior more than 3 times as
often as our planner. ... We conclude
that a cooperation model is critical for safe and efficient robot
navigation in dense human crowds.
Link
No comments:
Post a Comment