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cs.RO2026
DRL-Based Pose Control for Double-Ackermann Robots Under Actuation Uncertainties
Oussama Zaim, Mélodie Daniel, Aly Magassouba +2
Robust deployment of deep reinforcement learning (DRL) policies on real robots remains challenging due to discrepancies between simulation and real-world dynamics. We address this…
cs.RO2026
ManeuverNet: A Soft Actor-Critic Framework for Precise Maneuvering of Double-Ackermann-Steering Robots with Optimized Reward Functions
Kohio Deflesselle, Mélodie Daniel, Aly Magassouba +2
Autonomous control of double-Ackermann-steering robots is essential in agricultural applications, where robots must execute precise and complex maneuvers within a limited space. Cl…