CoCoNav: Conformal Control for Safe Robot Navigation in Crowds
Safe and efficient robot navigation in crowds requires anticipating pedestrian motion despite uncertain and potentially shifting prediction errors. Existing reactive methods can produce oscillatory behavior, while predictive planners often treat forecasts as exact or rely on restrictive error models. Incorporating conservative uncertainty sets as hard constraints can also render model predictive control (MPC) infeasible. We propose \textit{CoCoNav}, a crowd-navigation framework that combines online conformal calibration with runtime-certified planning. A horizon-specific conformal proportional--integral controller adapts trajectory-error bounds to regulate long-run empirical coverage, ena...
| Authors | Cheng Guo, Mingzhe Ni, Zheng Liang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 7 August 2026 |
| Last updated at source | 7 August 2026 |
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