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20192025
most citedPyPose: A Library for Robot Learning with Physics-based Optimization

36 citations · 73 across the 13 of their papers we have counts for

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Showing 2022 · cs.ROShow all

6 papers · 2 filters

cs.RO2022★ 36 cited

PyPose: A Library for Robot Learning with Physics-based Optimization

Chen Wang, Dasong Gao, Kuan Xu +34

Deep learning has had remarkable success in robotic perception, but its data-centric nature suffers when it comes to generalizing to ever-changing environments. By contrast, physic…

cs.RO2022★ 1 cited

Seamless Interaction Design with Coexistence and Cooperation Modes for Robust Human-Robot Collaboration

Zhe Huang, Ye-Ji Mun, Xiang Li +6

A robot needs multiple interaction modes to robustly collaborate with a human in complicated industrial tasks. We develop a Coexistence-and-Cooperation (CoCo) human-robot collabora…

cs.RO2022

Insights from an Industrial Collaborative Assembly Project: Lessons in Research and Collaboration

Tan Chen, Zhe Huang, James Motes +13

Significant progress in robotics reveals new opportunities to advance manufacturing. Next-generation industrial automation will require both integration of distinct robotic technol…

cs.RO2022

Off-Policy Evaluation with Online Adaptation for Robot Exploration in Challenging Environments

Yafei Hu, Junyi Geng, Chen Wang +2

Autonomous exploration has many important applications. However, classic information gain-based or frontier-based exploration only relies on the robot current state to determine th…

cs.RO2022

Hierarchical Intention Tracking for Robust Human-Robot Collaboration in Industrial Assembly Tasks

Zhe Huang, Ye-Ji Mun, Xiang Li +6

Collaborative robots require effective human intention estimation to safely and smoothly work with humans in less structured tasks such as industrial assembly, where human intentio…

cs.RO2022★ 2 cited

Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

Shuijing Liu, Peixin Chang, Zhe Huang +6

We study the problem of safe and intention-aware robot navigation in dense and interactive crowds. Most previous reinforcement learning (RL) based methods fail to consider differen…