ShapeMap 3-D: Efficient shape mapping through dense touch and vision
Author:
Affiliation:
1. Robotics Institute, Carnegie Mellon University
2. Brigham Young University,Electrical and Computer Engineering Department
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9811522/9811357/09812040.pdf?arnumber=9812040
Reference53 articles.
1. Incremental sparse GP regression for continuous-time trajectory estimation and mapping
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5. Local implicit surface estimation for haptic exploration
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1. AcTExplore: Active Tactile Exploration on Unknown Objects;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
2. Enhancing Generalizable 6D Pose Tracking of an In-Hand Object With Tactile Sensing;IEEE Robotics and Automation Letters;2024-02
3. Real-Time Reconstruction of 3-D Tactile Motion Field via Multitask Learning;IEEE Transactions on Instrumentation and Measurement;2024
4. Real-time and robust feature detection of continuous marker pattern for dense 3-D deformation measurement;Measurement;2023-11
5. Sliding Touch-Based Exploration for Modeling Unknown Object Shape with Multi-Fingered Hands;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01
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