From the 1 of 5 linked papers with an AI index.
5 papers
LENS: LLM-guided Environment Simplification for Planning and Control in Clutter
Aileen Liao, Rachel Holladay, Dinesh Jayaraman +1
Despite recent advances in general-purpose robotic manipulation, real-world multi-object clutter remains challenging to handle for today's prevalent approaches. The problem scales…
Where to Touch, How to Contact: A Hierarchical RL-MPC Framework for Geometry-Aware Sim-to-Real Manipulation
Zhixian Xie, Yu Xiang, Michael Posa +1
The paper introduces a hierarchical framework that uses a high‑level reinforcement learning policy to choose where a robot should touch an object and a low‑level contact‑implicit m…
Push Anything: Single- and Multi-Object Pushing From First Sight with Contact-Implicit MPC
Hien Bui, Yufeiyang Gao, Haoran Yang +6
Non-prehensile manipulation of diverse objects remains a core challenge in robotics, driven by unknown physical properties and the complexity of contact-rich interactions. Recent a…
Object Reconstruction under Occlusion with Generative Priors and Contact-induced Constraints
Minghan Zhu, Zhiyi Wang, Qihang Sun +2
Object geometry is key information for robot manipulation. Yet, object reconstruction is a challenging task because cameras only capture partial observations of objects, especially…
Vysics: Object Reconstruction Under Occlusion by Fusing Vision and Contact-Rich Physics
Bibit Bianchini, Minghan Zhu, Mengti Sun +3
We introduce Vysics, a vision-and-physics framework for a robot to build an expressive geometry and dynamics model of a single rigid body, using a seconds-long RGBD video and the r…