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Shunyi Yao

3 accepted papers

2023

Training a Non-Cooperator to Identify Vulnerabilities and Improve Robustness for Robot Navigation

RA-L 2023

Autonomous mobile robots have become popular in various applications coexisting with humans, which requires robots to navigate efficiently and safely in crowd environments with diverse pedestrians. Pedestrians may cooperate with the robot by avoiding it actively or ignoring the robot during their wa

Cited by 2SourceScholar
2022

Learning to Socially Navigate in Pedestrian-rich Environments with Interaction Capacity

ICRA 2022poster

Existing navigation policies for autonomous robots tend to focus on collision avoidance while ignoring human-robot interactions in social life. For instance, robots can pass along the corridor safer and easier if pedestrians notice them. Sounds have been considered as an efficient way to attract the…

Cited by 18SourceScholar
2021

Crowd-Aware Robot Navigation for Pedestrians with Multiple Collision Avoidance Strategies via Map-based Deep Reinforcement Learning

IROS 2021poster

It is challenging for a mobile robot to navigate through human crowds. Existing approaches usually assume that pedestrians follow a predefined collision avoidance strategy, like social force model (SFM) or optimal reciprocal collision avoidance (ORCA). However, their performances commonly need to be…

Cited by 41SourceScholar