6 papers · 1 filter
Morphogenetic Assembly and Adaptive Control for Heterogeneous Modular Robots
Chongxi Meng, Da Zhao, Yifei Zhao +4
This paper presents a closed-loop automation framework for heterogeneous modular robots, covering the full pipeline from morphological construction to adaptive control. In this fra…
HAFO: A Force-Adaptive Control Framework for Humanoid Robots in Intense Interaction Environments
Chenhui Dong, Haozhe Xu, Wenhao Feng +4
Reinforcement learning (RL) controllers have made impressive progress in humanoid locomotion and light-weight object manipulation. However, achieving robust and precise motion cont…
A Tactile-based Interactive Motion Planner for Robots in Unknown Cluttered Environments
Chengjin Wang, Yanmin Zhou, Zheng Yan +5
In unknown cluttered environments with densely stacked objects, the free-motion space is extremely barren, posing significant challenges to motion planners. Collision-free planning…
Learning Efficient Robotic Garment Manipulation with Standardization
Changshi Zhou, Feng Luan, Jiarui Hu +5
Garment manipulation is a significant challenge for robots due to the complex dynamics and potential self-occlusion of garments. Most existing methods of efficient garment unfoldin…
Kaiwu: A Multimodal Manipulation Dataset and Framework for Robot Learning and Human-Robot Interaction
Shuo Jiang, Haonan Li, Ruochen Ren +3
Cutting-edge robot learning techniques including foundation models and imitation learning from humans all pose huge demands on large-scale and high-quality datasets which constitut…
Robot Learning in the Era of Foundation Models: A Survey
Xuan Xiao, Jiahang Liu, Zhipeng Wang +5
The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning from automation towards general embodied Artificial Intelligence (AI). Adopting foundation…