5 papers
Simulation-Ready Cluttered Scene Estimation via Physics-aware Joint Shape and Pose Optimization
Wei-Cheng Huang, Jiaheng Han, Xiaohan Ye +2
Estimating simulation-ready scenes from real-world observations is crucial for downstream planning and policy learning tasks. Regretfully, existing methods struggle in cluttered en…
One-Shot Real-to-Sim via End-to-End Differentiable Simulation and Rendering
Yifan Zhu, Tianyi Xiang, Aaron Dollar +1
Identifying predictive world models for robots in novel environments from sparse online observations is essential for robot task planning and execution in novel environments. Howev…
Physics-informed Temporal Difference Metric Learning for Robot Motion Planning
Ruiqi Ni, Zherong Pan, Ahmed H Qureshi
The motion planning problem involves finding a collision-free path from a robot's starting to its target configuration. Recently, self-supervised learning methods have emerged to t…
SRPose: Two-view Relative Pose Estimation with Sparse Keypoints
Rui Yin, Yulun Zhang, Zherong Pan +3
Two-view pose estimation is essential for map-free visual relocalization and object pose tracking tasks. However, traditional matching methods suffer from time-consuming robust est…
Global Convergence of an SQP Method for Contact-Implicit Trajectory Optimization
Zherong Pan, Yifan Zhu, Fuquan Wang
Contact-Implicit Trajectory Optimization (CITO) is a powerful framework for planning motions of robots that interact with complex environments, but its convergence behavior remains…