Lab Meeting Oct. 3rd (Jim): Robot Navigation in Dense Human Crowds: the Case for Cooperation

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