Physics-informed spatio-temporal graph reinforcement learning for safe crowd navigation
Standard distance-based reinforcement learning (RL) policies often fail in dense, mixed-speed crowds because they evaluate pedestrian threats based primarily on spatial proximity, ignoring actual collision timing. We introduce PSTGNav, a physics-informed navigation framework that embeds kinematic tracking into the RL p...