5 papers · 1 filter
Learning Robot Visual Navigation in Crowds via Intention-Aware Scene Representations
Han Bao, Bingyi Xia, Hanjing Ye +5
Robot crowd navigation requires the ability to infer human intentions while accounting for the structural constraints of the environment. Currently, deep reinforcement learning (DR…
MfNeuPAN: Proactive End-to-End Navigation in Dynamic Environments via Direct Multi-Frame Point Constraints
Yiwen Ying, Hanjing Ye, Senzi Luo +4
Obstacle avoidance in complex and dynamic environments is a critical challenge for real-time robot navigation. Model-based and learning-based methods often fail in highly dynamic s…
Adap-RPF: Adaptive Trajectory Sampling for Robot Person Following in Dynamic Crowded Environments
Weixi Situ, Hanjing Ye, Jianwei Peng +2
Robot person following (RPF) is a core capability in human-robot interaction, enabling robots to assist users in daily activities, collaborative work, and other service scenarios.…
TPT-Bench: A Large-Scale, Long-Term and Robot-Egocentric Dataset for Benchmarking Target Person Tracking
Hanjing Ye, Yu Zhan, Weixi Situ +6
Tracking a target person from robot-egocentric views is crucial for developing autonomous robots that provide continuous personalized assistance or collaboration in Human-Robot Int…
RPF-Search: Field-based Search for Robot Person Following in Unknown Dynamic Environments
Hanjing Ye, Kuanqi Cai, Yu Zhan +3
Autonomous robot person-following (RPF) systems are crucial for personal assistance and security but suffer from target loss due to occlusions in dynamic, unknown environments. Cur…