Robot Manipulation Learning and Interaction Control

Dear Colleagues,

This Topic, “Robot Manipulation Learning and Interaction Control”, aims to serve as a platform for advancing the theory and practice of robotic manipulation, control, and human–robot interaction. Building upon recent progress in robot learning, teleoperation, and adaptive control, this Topic seeks to address the growing need for intelligent, flexible, and robust robotic systems capable of performing complex manipulation tasks across diverse environments—from industry to homes and hospitals, etc. We hope to foster interdisciplinary collaboration among researchers, roboticists, engineers, and practitioners to share cutting-edge developments, novel methodologies, and real-world applications. Our objective is to catalyse research that advances the autonomy, adaptability, and safety of robotic manipulation and control systems, particularly in dynamic, unstructured, or human-centric settings. In this context, we welcome contributions that explore frameworks, models, algorithms, and systems related to robot learning, interaction control, and teleoperation. Topics of interest include (but are not limited to) the following:

• Learning-based manipulation and grasping strategies;
• Reinforcement learning and imitation learning for robot control;
• Teleoperation systems and shared autonomy;
• Visual–tactile perception for dexterous manipulation;
• Human-in-the-loop and collaborative control;
• Multimodal sensor fusion for manipulation tasks;
• Safety-aware and adaptive control in dynamic environments;
• Real-world deployment and benchmarking of manipulation systems;
• Robot learning from demonstration and simulation-to-reality transfer;
• Interaction-aware trajectory planning and motion generation.

We encourage researchers, engineers, and industry experts to contribute original research articles, review papers, and case studies that highlight recent advancements, innovative approaches, and practical insights within this rapidly evolving field.

Dr. Weiyong Si
Dr. Anqing Duan
Dr. Longnan Li
Prof. Dr. Chenguang Yang
Topic Editors