36 citations · 73 across the 13 of their papers we have counts for
13 papers
AirIO: Learning Inertial Odometry with Enhanced IMU Feature Observability
Yuheng Qiu, Can Xu, Yutian Chen +3
Inertial odometry (IO) using only Inertial Measurement Units (IMUs) offers a lightweight and cost-effective solution for Unmanned Aerial Vehicle (UAV) applications, yet existing le…
iKap: Kinematics-aware Planning with Imperative Learning
Qihang Li, Zhuoqun Chen, Haoze Zheng +5
Trajectory planning in robotics aims to generate collision-free pose sequences that can be reliably executed. Recently, vision-to-planning systems have gained increasing attention…
Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy
Chen Wang, Kaiyi Ji, Junyi Geng +16
Data-driven methods such as reinforcement and imitation learning have achieved remarkable success in robot autonomy. However, their data-centric nature still hinders them from gene…
The Impact of Time Step Frequency on the Realism of Robotic Manipulation Simulation for Objects of Different Scales
Minh Q. Ta, Holly Dinkel, Hameed Abdul-Rashid +5
This work evaluates the impact of time step frequency and component scale on robotic manipulation simulation accuracy. Increasing the time step frequency for small-scale objects is…
PyPose v0.6: The Imperative Programming Interface for Robotics
Zitong Zhan, Xiangfu Li, Qihang Li +33
PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has…
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…
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…
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…
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…
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…
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…
iCaps: Iterative Category-level Object Pose and Shape Estimation
Xinke Deng, Junyi Geng, Timothy Bretl +2
This paper proposes a category-level 6D object pose and shape estimation approach iCaps, which allows tracking 6D poses of unseen objects in a category and estimating their 3D shap…
Deep Algorithm Unrolling for Blind Image Deblurring
Yuelong Li, Mohammad Tofighi, Junyi Geng +2
Blind image deblurring remains a topic of enduring interest. Learning based approaches, especially those that employ neural networks have emerged to complement traditional model ba…