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CrowdMove: Autonomous Mapless Navigation in Crowded Scenarios
July 19, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Tingxiang Fan, Xinjing Cheng, Jia Pan, Dinesh Manocha, Ruigang Yang
arXiv ID
1807.07870
Category
cs.RO: Robotics
Citations
62
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Navigation is an essential capability for mobile robots. In this paper, we propose a generalized yet effective 3M (i.e., multi-robot, multi-scenario, and multi-stage) training framework. We optimize a mapless navigation policy with a robust policy gradient algorithm. Our method enables different types of mobile platforms to navigate safely in complex and highly dynamic environments, such as pedestrian crowds. To demonstrate the superiority of our method, we test our methods with four kinds of mobile platforms in four scenarios. Videos are available at https://sites.google.com/view/crowdmove.
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