most citedManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills

22 citations · 27 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Reparameterized Policy Learning for Multimodal Trajectory Optimization

Zhiao Huang, Litian Liang, Zhan Ling +3

We investigate the challenge of parametrizing policies for reinforcement learning (RL) in high-dimensional continuous action spaces. Our objective is to develop a multimodal policy…

cs.CV20233 cited

MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field

Kaizhi Yang, Xiaoshuai Zhang, Zhiao Huang +3

We present MovingParts, a NeRF-based method for dynamic scene reconstruction and part discovery. We consider motion as an important cue for identifying parts, that all particles on…

cs.CV20232 cited

DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics

Sizhe Li, Zhiao Huang, Tao Chen +4

In this work, we aim to learn dexterous manipulation of deformable objects using multi-fingered hands. Reinforcement learning approaches for dexterous rigid object manipulation wou…

cs.RO2023

RoboNinja: Learning an Adaptive Cutting Policy for Multi-Material Objects

Zhenjia Xu, Zhou Xian, Xingyu Lin +4

We introduce RoboNinja, a learning-based cutting system for multi-material objects (i.e., soft objects with rigid cores such as avocados or mangos). In contrast to prior works usin…

cs.RO202322 cited

ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills

Jiayuan Gu, Fanbo Xiang, Xuanlin Li +12

Generalizable manipulation skills, which can be composed to tackle long-horizon and complex daily chores, are one of the cornerstones of Embodied AI. However, existing benchmarks,…