12 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…
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…
Sampling-Based Constrained Motion Planning with Products of Experts
Amirreza Razmjoo, Teng Xue, Suhan Shetty +1
We present a novel approach to enhance the performance of sampling-based Model Predictive Control (MPC) in constrained optimization by leveraging products of experts. Our methodolo…
CCDP: Composition of Conditional Diffusion Policies with Guided Sampling
Amirreza Razmjoo, Sylvain Calinon, Michael Gienger +1
Imitation Learning offers a promising approach to learn directly from data without requiring explicit models, simulations, or detailed task definitions. During inference, actions a…
Geometry-aware Policy Imitation
Yiming Li, Nael Darwiche, Amirreza Razmjoo +4
We propose a Geometry-aware Policy Imitation (GPI) approach that rethinks imitation learning by treating demonstrations as geometric curves rather than collections of state-action…
Robust Contact-rich Manipulation through Implicit Motor Adaptation
Teng Xue, Amirreza Razmjoo, Suhan Shetty +1
Contact-rich manipulation plays an important role in daily human activities. However, uncertain physical parameters often pose significant challenges for both planning and control.…