TAIL: A Terrain-Aware Multi-Modal SLAM Dataset for Robot Locomotion in Deformable Granular Environments-Reference-Cited by-同舟云学术

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TAIL: A Terrain-Aware Multi-Modal SLAM Dataset for Robot Locomotion in Deformable Granular Environments

Published:2024-07 Issue:7 Volume:9 Page:6696-6703
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Yao Chen¹^ORCID,Ge Yangtao¹^ORCID,Shi Guowei¹^ORCID,Wang Zirui¹^ORCID,Yang Ningbo¹^ORCID,Zhu Zheng¹^ORCID,Wei Hexiang²^ORCID,Zhao Yuntian¹^ORCID,Wu Jing¹^ORCID,Jia Zhenzhong¹^ORCID

Affiliation:

1. Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China

2. Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China

Funder

Science, Technology and Innovation Commission of Shenzhen Municipality

Guangdong Province Science and Technology Program

Guangdong Natural Science Fund-General Programme

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7083369/10534628/10542164.pdf?arnumber=10542164

Reference33 articles.

1. NASAs mars rover has uncertain future as sixth anniversary nears;Webster,2009

2. Mars Rover Trapped in Sand, But What Can End a Mission?

3. STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation

4. The New College Vision and Laser Data Set

5. LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping

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