52 citations · 100 across the 10 of their papers we have counts for
7 papers · 1 filter
Efficient Extrinsic Self-Calibration of Multiple IMUs using Measurement Subset Selection
Jongwon Lee, David Hanley, Timothy Bretl
This paper addresses the problem of choosing a sparse subset of measurements for quick calibration parameter estimation. A standard solution to this is selecting a measurement only…
Accurate Simulation and Parameter Identification of Deformable Linear Objects using Discrete Elastic Rods in Generalized Coordinates
Qi Jing Chen, Timothy Bretl, Quang-Cuong Pham
This paper presents a fast and accurate model of a deformable linear object (DLO) -- e.g., a rope, wire, or cable -- integrated into an established robot physics simulator, MuJoCo.…
Comparative Study of Visual SLAM-Based Mobile Robot Localization Using Fiducial Markers
Jongwon Lee, Su Yeon Choi, David Hanley +1
This paper presents a comparative study of three modes for mobile robot localization based on visual SLAM using fiducial markers (i.e., square-shaped artificial landmarks with a bl…
Hypergraph-based Multi-Robot Task and Motion Planning
James Motes, Tan Chen, Timothy Bretl +2
We present a multi-robot task and motion planning method that, when applied to the rearrangement of objects by manipulators, results in solution times up to three orders of magnitu…
Extrinsic Calibration of Multiple Inertial Sensors from Arbitrary Trajectories
Jongwon Lee, David Hanley, Timothy Bretl
We present a method of extrinsic calibration for a system of multiple inertial measurement units (IMUs) that estimates the relative pose of each IMU on a rigid body using only meas…
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…
Self-supervised 6D Object Pose Estimation for Robot Manipulation
Xinke Deng, Yu Xiang, Arsalan Mousavian +3
To teach robots skills, it is crucial to obtain data with supervision. Since annotating real world data is time-consuming and expensive, enabling robots to learn in a self-supervis…