Navigating the Proximity-Safety Balance: Constraint Decomposition for Human Following in Pedestrian Crowds
Following a target human in crowded environments involves an inherent conflict between staying close to the target and navigating safely among surrounding pedestrians and obstacles. This conflict becomes more severe in dense scenarios, where aggressive following risks collisions and conservative margins lead to target loss, especially when pedestrian behaviors are unfamiliar or unpredictable. Existing reinforcement learning (RL) methods typically encode these competing objectives into a single dense reward, but the resulting proximity-safety balance is implicit and difficult to adjust across conditions. To address this, we decompose the human-following task into a sparse task reward and i...
| Authors | Shiting Gong, Jianpeng Yao, Jinfeng Wang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 10 August 2026 |
| Last updated at source | 10 August 2026 |
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