21 citations · 21 across the 6 of their papers we have counts for
6 papers
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…
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.…
Robust Manipulation Primitive Learning via Domain Contraction
Teng Xue, Amirreza Razmjoo, Suhan Shetty +1
Contact-rich manipulation plays an important role in human daily activities, but uncertain parameters pose significant challenges for robots to achieve comparable performance throu…
Logic-Skill Programming: An Optimization-based Approach to Sequential Skill Planning
Teng Xue, Amirreza Razmjoo, Suhan Shetty +1
Recent advances in robot skill learning have unlocked the potential to construct task-agnostic skill libraries, facilitating the seamless sequencing of multiple simple manipulation…
Tensor Train for Global Optimization Problems in Robotics
Suhan Shetty, Teguh Lembono, Tobias Loew +1
The convergence of many numerical optimization techniques is highly dependent on the initial guess given to the solver. To address this issue, we propose a novel approach that util…
Ergodic Exploration using Tensor Train: Applications in Insertion Tasks
Suhan Shetty, João Silvério, Sylvain Calinon
In robotics, ergodic control extends the tracking principle by specifying a probability distribution over an area to cover instead of a trajectory to track. The original problem is…