4 papers
RoboDream: Compositional World Models for Scalable Robot Data Synthesis
Junjie Ye, Rong Xue, Basile Van Hoorick +6
Scaling robot learning requires large-scale, diverse demonstrations, yet real-world data collection via teleoperation remains prohibitively expensive and time-consuming. While vide…
Batched Differentiable Rigid Body Dynamics in PyTorch for GPU-Accelerated Robot Learning
Yue Wang, Yanran Xu, Wenbo Wu +2
As robot control shifts toward large-scale reinforcement learning with in-loop dynamics computation, the community's reliance on CPU-bound libraries such as Pinocchio creates a thr…
HMCF: A Human-in-the-loop Multi-Robot Collaboration Framework Based on Large Language Models
Zhaoxing Li, Wenbo Wu, Yue Wang +3
Rapid advancements in artificial intelligence (AI) have enabled robots to performcomplex tasks autonomously with increasing precision. However, multi-robot systems (MRSs) face chal…
Quattro: Transformer-Accelerated Iterative Linear Quadratic Regulator Framework for Fast Trajectory Optimization
Yue Wang, Haoyu Wang, Zhaoxing Li
Real-time optimal control remains a fundamental challenge in robotics, especially for nonlinear systems with stringent performance requirements. As one of the representative trajec…