| Title | PUTN: A Plane-fitting based Uneven Terrain Navigation Framework |
| Author | |
| DOI | |
| Publication Years | 2022
|
| Conference Name | IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
|
| ISSN | 2153-0858
|
| ISBN | 978-1-6654-7928-8
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| Source Title | |
| Pages | 7160-7166
|
| Conference Date | 23-27 Oct. 2022
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| Conference Place | Kyoto, Japan
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| Publication Place | 345 E 47TH ST, NEW YORK, NY 10017 USA
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| Publisher | |
| Abstract | Autonomous navigation of ground robots has been widely used in indoor structured 2D environments, but there are still many challenges in outdoor 3D unstructured environments, especially in rough, uneven terrains. This paper proposed a plane-fitting based uneven terrain navigation framework (PUTN) to solve this problem. The implementation of PUTN is divided into three steps. First, based on Rapidly-exploring Random Trees (RRT), an improved sample-based algorithm called Plane Fitting RRT* (PF-RRT*) is proposed to obtain a sparse trajectory. Each sampling point corresponds to a custom traversability index and a fitted plane on the point cloud. These planes are connected in series to form a traversable "strip". Second, Gaussian Process Regression is used to generate traversability of the dense trajectory interpolated from the sparse trajectory, and the sampling tree is used as the training set. Finally, local planning is performed using nonlinear model predictive control (NMPC). By adding the traversability index and uncertainty to the cost function, and adding obstacles generated by the real-time point cloud to the constraint function, a safe motion planning algorithm with smooth speed and strong robustness is available. Experiments in real scenarios are conducted to verify the effectiveness of the method. The source code is released for the reference of the community. |
| Keywords | |
| SUSTech Authorship | Others
|
| Language | English
|
| URL | [Source Record] |
| Indexed By | |
| Funding Project | Joint Funds of the National Natural Science Foundation of China[U1813216]
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| WOS Research Area | Automation & Control Systems
; Computer Science
; Engineering
; Robotics
|
| WOS Subject | Automation & Control Systems
; Computer Science, Artificial Intelligence
; Engineering, Electrical & Electronic
; Robotics
|
| WOS Accession No | WOS:000909405300016
|
| Data Source | IEEE
|
| PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9981038 |
| Citation statistics |
Cited Times [WOS]:0
|
| Document Type | Conference paper |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/424440 |
| Department | Department of Electrical and Electronic Engineering |
| Affiliation | 1.Center for Artificial Intelligence and Robotics, Shenzhen International Graduate School, Tsinghua University, Shenzhen, China 2.School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China 3.Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China |
| Recommended Citation GB/T 7714 |
Zhuozhu Jian,Zihong Lu,Xiao Zhou,et al. PUTN: A Plane-fitting based Uneven Terrain Navigation Framework[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:7160-7166.
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