Improving the autonomous navigation of mobile robots in crowded spaces using people as sensors

A team of researchers from University of Illinois at Urbana-Champaign and Stanford University led by Prof. Katie Driggs-Campbell, have recently developed a new deep reinforcement learning-based method that could improve the ability of mobile robots to safely navigate crowded spaces. Their method, introduced in a paper pre-published on arXiv, is based on the idea of using people in the robot's surroundings as indicators of potential obstacles.

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