Stability-aware Residual Reinforcement Learning Framework for Robotic Manipulator Disturbance Compensation

arXiv:2609.21307 · cs.RO · Submitted 2026-09-18 · Read on arXiv

cs.RO

Submitted: 2026-09-18

Updated: 2026-09-18

Terminology

• Latent Space — 15× in this paper · explained in 7 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Reinforcement Learning — 11× in this paper · explained in 4 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Actor — 7× in this paper · explained in 3 episodes
• Adaptation — 6× in this paper · explained in 1 episode
• Sim-to-Real Transfer — 5× in this paper · explained in 2 episodes
• System Identification — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Latent Representation — 4× in this paper · explained in 2 episodes
• Calibration — 3× in this paper · explained in 7 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Adaptability — 2× in this paper · explained in 1 episode
• Clustering — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Nonlinear Model Predictive Control (NMPC) — 2× in this paper · explained in 3 episodes
• Reward Function — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Actor-Critic Model — 1× in this paper · explained in 1 episode
• Closed-Loop Control — 1× in this paper · explained in 3 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Integral of Absolute Error — 1× in this paper
• Interpretability — 1× in this paper · explained in 15 episodes
• Model Predictive Control (MPC) — 1× in this paper · explained in 5 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Shaping — 1× in this paper · explained in 2 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes

Sources

• Residual MPC: Blending Reinforcement Learning with GPU-Parallelized Model Predictive Control
• RL-augmented Adaptive Model Predictive Control for Bipedal Locomotion over Challenging Terrain
• IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality
• Residual Policy Learning
• Residual Policy Learning for Vehicle Control of Autonomous Racing Cars

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