IEEE RA-L

Transformer Driven Visual Servoing for Fabric Texture Matching Using Dual-Arm Manipulator

基于双臂机械臂的Transformer驱动视觉伺服织物纹理匹配

Fuyuki Tokuda, Akira Seino, Akinari Kobayashi, Kai Tang, Kazuhiro Kosuge

机构 * JC STEM Lab of Robotics for Soft Materials, Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong（机器人柔性材料联合实验室、电气与电子工程系、工程学院、香港大学） 纠错

AI总结 本文提出基于Transformer的视觉伺服方法，利用双臂机械臂实现织物纹理匹配，通过差分提取注意力模块提升姿态预测精度，实现零样本部署。

Comments 8 pages, 11 figures. Accepted to IEEE Robotics and Automation Letters (RA-L)

AORRTC: Almost-Surely Asymptotically Optimal Planning with RRT-Connect

AORRTC: 几乎确定性渐进最优规划与RRT-Connect

Tyler Wilson, Wil Thomason, Zachary Kingston, Jonathan Gammell

AI总结 AORRTC通过扩展RRT-Connect实现几乎确定性渐进最优规划，以高效且可靠的方式解决高自由度机器人运动规划问题。

Comments IEEE Robotics and Automation Letters (RA-L). 8 pages, 4 figures, 1 table. A video of AORRTC can be found at https://www.youtube.com/watch?v=j1itxP3KuiM . Information on the implementation of AORRTC is available at https://robotic-esp.com/code/aorrtc/

Journal ref IEEE Robotics and Automation Letters, vol. 10 num. 12, (2025). Pages 13375-13382