Search Results for author: Arth Shukla

Found 3 papers, 3 papers with code

ManiSkill-HAB: A Benchmark for Low-Level Manipulation in Home Rearrangement Tasks

1 code implementation • 9 Dec 2024 • Arth Shukla, Stone Tao, Hao Su

High-quality benchmarks are the foundation for embodied AI research, enabling significant advancements in long-horizon navigation, manipulation and rearrangement tasks.

Imitation Learning Object Rearrangement +1

Paper
Code

ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI

1 code implementation • 1 Oct 2024 • Stone Tao, Fanbo Xiang, Arth Shukla, Yuzhe Qin, Xander Hinrichsen, Xiaodi Yuan, Chen Bao, Xinsong Lin, Yulin Liu, Tse-kai Chan, Yuan Gao, Xuanlin Li, Tongzhou Mu, Nan Xiao, Arnav Gurha, Zhiao Huang, Roberto Calandra, Rui Chen, Shan Luo, Hao Su

We introduce and open source ManiSkill3, the fastest state-visual GPU parallelized robotics simulator with contact-rich physics targeting generalizable manipulation.

Imitation Learning Motion Planning +1

1,389

Paper
Code

Reverse Forward Curriculum Learning for Extreme Sample and Demonstration Efficiency in Reinforcement Learning

1 code implementation • 6 May 2024 • Stone Tao, Arth Shukla, Tse-kai Chan, Hao Su

A forward curriculum is then used to accelerate the training of the initial policy to perform well on the full initial state distribution of the task and improve demonstration and sample efficiency.

Reinforcement Learning (RL)

Paper
Code

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