Human-Aware Navigation Planner for Diverse Human-Robot Contexts

Phani-Teja Singamaneni (1) , Anthony Favier (1) , Rachid Alami (1)

1 LAAS-RIS - Équipe Robotique et InteractionS

As more robots are being deployed into human environments, a human-aware navigation planner needs to handle multiple contexts that occur in indoor and outdoor environments. In this paper, we propose a tunable human-aware robot navigation planner that can handle a variety of human-robot contexts. We present the architecture of the system and discuss the features along with some implementation details. Then we present a detailed analysis of various simulated human-robot contexts using the proposed planner. Further, we show that our system performs better when compared with an exiting human-aware planner in various contexts. Finally, we show the results in a real-world scenario after deploying our system on a real robot.

Domaines: Robotique [cs.RO]

Phani-Teja Singamaneni, Anthony Favier, Rachid Alami. Human-Aware Navigation Planner for Diverse Human-Robot Contexts. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sep 2021, Prague (online), Czech Republic. ⟨10.1109/IROS51168.2021.9636613⟩. ⟨hal-03262888v2⟩