5 papers
Exposing the Long-tail in Embodied Urban Navigation via Scalable Learning from In-the-Wild Videos
Bingyi Xia, Han Bao, Zhewei Chen +5
Learning embodied urban navigation policies from real-world data is constrained by the cost of task-specific data collection and the limited coverage of rare yet safety-critical sc…
NavIsaacLab: Generating Realistic Crowd via Parallel Robot Learning for Benchmarking Human-aware Navigation
Bingyi Xia, Han Bao, Jingyu Zhu +6
Robot autonomous navigation that accounts for surrounding human activities is crucial for ensuring both safety and natural human-robot interaction in real-world environments shared…
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…
Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following
Hanjing Ye, Weixi Situ, Jianwei Peng +4
Robot person following (RPF) -- mobile robots that follow and assist a specific person -- has emerging applications in personal assistance, security patrols, eldercare, and logisti…
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…