5 papers
AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation
Hengkai Tan, Yao Feng, Xinyi Mao +5
Learning generalizable manipulation policies hinges on data, yet robot manipulation data is scarce and often entangled with specific embodiments, making both cross-task and cross-p…
ATRS: Adaptive Trajectory Re-splitting via a Shared Neural Policy for Parallel Optimization
Jiajun Yu, Guodong Liu, Li Wang +6
Parallel trajectory optimization via the Alternating Direction Method of Multipliers (ADMM) has emerged as a scalable approach to long-horizon motion planning. However, existing fr…
Vidar: Embodied Video Diffusion Model for Generalist Manipulation
Yao Feng, Hengkai Tan, Xinyi Mao +5
Scaling general-purpose manipulation to new robot embodiments remains challenging: each platform typically needs large, homogeneous demonstrations, and end-to-end pixel-to-action p…
RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
Tianxing Chen, Zanxin Chen, Baijun Chen +23
Simulation-based data synthesis has emerged as a powerful paradigm for advancing real-world robotic manipulation. Yet existing datasets remain insufficient for robust bimanual mani…
TOP: Trajectory Optimization via Parallel Optimization towards Constant Time Complexity
Jiajun Yu, Nanhe Chen, Guodong Liu +3
Optimization has been widely used to generate smooth trajectories for motion planning. However, existing trajectory optimization methods show weakness when dealing with large-scale…