arXiv AI By Nolan B. Gutierrez, Joseph M. Cloud, William J. Beksi

Movement Primitives in Robotics: A Comprehensive Survey

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arXiv:2601. 02379v2 Announce Type: replace-cross Abstract: Biological systems exhibit a continuous stream of movements, consisting of sequential segments, that allow them to perform complex tasks in a creative and versatile fashion.

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arXiv Computer Vision
Aug 25

TONAV: Task-Oriented Navigation and Action-Velocity Chunk Learning for Articulated Object Quadrupedal Mobile Manipulation

arXiv:2608.22296v1 Announce Type: cross Abstract: Quadruped mobile manipulation requires two tightly coupled capabilities: reaching manipulation-ready configurations and maintaining stable contact th...

By Haoran Lin, Mingyu Yang, Pengfei Qi, Kehan Chen, Qiang Diao, Liangji Zeng, Wenrui Chen, Yaonan Wang, Kailun Yang
arXiv AI
Sep 16

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation

The paper introduces QDTraj, a method that uses Quality‑Diversity algorithms to automatically generate a diverse set of low‑level trajectory primitives for manipulating articulated objects. By leveraging sparse reward exploration, QDTraj produces at least five times more diverse trajectories for hinge and slider tasks compared to baseline methods, and demonstrates strong generalization across 30 articulations from the PartNetMobility dataset, averaging 704 trajectories per task. The resulting primitives are validated both in simulation and on real robots, with the code released publicly.

By Mathilde Kappel, Mahdi Khoramshahi, Louis Annabi, Faiz Ben Amar, St\'ephane Doncieux
arXiv AI
Jul 22

AnchorRefine: Synergy-Manipulation Based on Trajectory Anchor and Residual Refinement for Vision-Language-Action Models

arXiv:2604. 17787v2 Announce Type: replace-cross Abstract: Precision-critical manipulation requires both global trajectory organization and local execution correction, yet most vision-language-action (VLA) policies generate actions within a single unified space.

By Tingzheng Jia, Kan Guo, Lanping Qian, Yongli Hu, Daxin Tian, Guixian Qu, Chunmian Lin, Baocai Yin, Jiapu Wang