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Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation
Yihao Wu, Jinming Ma, Junbo Tan +5
Diffusion-based policies generalize poorly in semantic manipulation, a key obstacle to real-world deployment, because text-only instructions cannot reliably steer the policy toward…
Data-Driven MPC with Data Selection for Flexible Cable-Driven Robotic Arms
Huayue Liang, Yanbo Chen, Hongyang Cheng +5
Flexible cable-driven robotic arms (FCRAs) offer dexterous and compliant motion. Still, the inherent properties of cables, such as resilience, hysteresis, and friction, often lead…
D3-ARM: High-Dynamic, Dexterous and Fully Decoupled Cable-driven Robotic Arm
Hong Luo, Jianle Xu, Shoujie Li +4
Cable transmission enables motors of robotic arm to operate lightweight and low-inertia joints remotely in various environments, but it also creates issues with motion coupling and…
Efficient Collision Detection Framework for Enhancing Collision-Free Robot Motion
Xiankun Zhu, Yucheng Xin, Shoujie Li +3
Fast and efficient collision detection is essential for motion generation in robotics. In this paper, we propose an efficient collision detection framework based on the Signed Dist…
RoboDuet: Learning a Cooperative Policy for Whole-body Legged Loco-Manipulation
Guoping Pan, Qingwei Ben, Zhecheng Yuan +6
Fully leveraging the loco-manipulation capabilities of a quadruped robot equipped with a robotic arm is non-trivial, as it requires controlling all degrees of freedom (DoFs) of the…