19 papers
Monte Carlo Tree Search with Tensor Factorization for Optimization Problems in Robotics
Teng Xue, Yan Zhang, Amirreza Razmjoo +1
Many robotic tasks, such as inverse kinematics, motion planning, and contact-rich manipulation, can be formulated as optimization problems. Solving these problems requires addressi…
Physics-Informed Eikonal Caging for Whole-Arm Manipulation Planning
Yan Zhang, Yiming Li, Yifei Dong +2
Planning contact-rich whole-arm manipulation is challenging because interactions that involve extended robot geometry give rise to complex contact dynamics that are difficult to mo…
Spline Policy: A Structured Representation for Robot Policies
Mengze Tian, Yiming Li, Sichao Liu +2
Modern imitation-learning policies for robot manipulation often represent actions as fixed-resolution action chunks, which are simple and effective but expose limited geometric and…
Learn2Decompose: Learning Problem Decomposition for Efficient Sequential Multi-object Manipulation Planning
Yan Zhang, Teng Xue, Amirreza Razmjoo +1
We present an efficient task and motion replanning approach for sequential multi-object manipulation in dynamic environments. Conventional Task And Motion Planning (TAMP) solvers e…
Ergodic Imitation for Adaptive Exploration around Demonstrations
Ziyi Xu, Cem Bilaloglu, Yiming Li +1
In robotics, a common challenge in imitation learning is the mismatch between training and deployment conditions, caused, for example, by environmental changes or imperfect observa…
Robustness-Aware Tool Selection and Manipulation Planning with Learned Energy-Informed Guidance
Yifei Dong, Yan Zhang, Sylvain Calinon +1
Humans subconsciously choose robust ways of selecting and using tools, for example, choosing a ladle over a flat spatula to serve meatballs. However, robustness under external dist…