Hybrid physics-plus-PD-plus-residual-SAC control yields 100% simulated success for Ackermann-leader navigation and omnidirectional formation tracking, outperforming pure residual RL ablations.
Leader-following formation of heterogeneous multi-agent systems with time-varying topology: A virtual neighbor framework,
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High-Precision Formation Control for Heterogeneous Multi-Robot Systems via Hierarchical Hybrid Physics-Informed Deep Reinforcement Learning
Hybrid physics-plus-PD-plus-residual-SAC control yields 100% simulated success for Ackermann-leader navigation and omnidirectional formation tracking, outperforming pure residual RL ablations.