Towards Robot Skill Learning and Adaptation with Gaussian Processes

arXiv:2603.01480 · cs.RO · Submitted 2026-03-02 · Read on arXiv

cs.RO

Submitted: 2026-03-02

Updated: 2026-10-16

Comments: Published in IEEE Robotics and Automation Letters (RA-L), 2026. Presented at IEEE/RSJ IROS 2026

Journal ref: IEEE Robotics and Automation Letters, vol. 11, no. 5, pp. 6408-6415, 2026

DOI: 10.1109/LRA.2026.3681188

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Adaptation — 6× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Gaussian Process — 1× in this paper
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

Related papers

• FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
• MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
• RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
• ARC: A Reasoning Recipe for Robot Foundation Models
• HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
• APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies