From the 1 of 21 linked papers with an AI index.
1 citations · 1 across the 15 of their papers we have counts for
22 papers
Globalized Constrained Stein Variational Inference for Diverse Feasible Robot Motion Planning
Jiayun Li, Georgia Chalvatzaki
The paper introduces SteinSQP, a constrained Stein variational inference algorithm that generates diverse, feasible robot motion plans by embedding constraints into a kernel-space…
IMPACT: An Implicit Active-Set Augmented Lagrangian for Fast Contact-Implicit Trajectory Optimization
Jiayun Li, Dejian Gong, Georgia Chalvatzaki
Contact-implicit trajectory optimization (CITO) has attracted growing attention as a unified framework for planning and control in contact-rich robotic tasks. Recent approaches hav…
Bimanual Robot Manipulation via Multi-Agent In-Context Learning
Alessio Palma, Indro Spinelli, Vignesh Prasad +4
Language Models (LLMs) have emerged as powerful reasoning engines for embodied control. In particular, In-Context Learning (ICL) enables off-the-shelf, text-only LLMs to predict ro…
Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning
Rickmer Krohn, Vignesh Prasad, Gabriele Tiboni +1
Effective contact-rich manipulation requires robots to synergistically leverage vision, force, and proprioception. However, Reinforcement Learning agents struggle to learn in such…
Robot-DIFT: Correspondence-Sensitive Diffusion Features for Contact-Rich Robot Manipulation
Yu Deng, Yufeng Jin, Xiaogang Jia +3
Robot manipulation often fails in the final millimeters: a policy may recognize the right object yet miss the pose offsets, boundaries, or pre-contact alignments needed for action.…
HARBOR: A Harness Framework for Agentic Robot Reinforcement Learning
Zechu Li, Yufeng Jin, Xiaoyang Liu +4
Reinforcement learning (RL) has become a powerful paradigm for robot learning, particularly in sim-to-real settings, but its broader adoption remains limited by the engineering pip…