Multiresolution Representations for Large-Scale Terrain with Local Gaussian Process Regression
文献类型：会议论文
| 作者 | Liu X(刘旭)1,2,3; Li DC(李德才)2,3 ; He YQ(何玉庆)2,3
|
| 出版日期 | 2021 |
| 会议日期 | May 30 - June 5, 2021 |
| 会议地点 | Xi'an, China |
| 页码 | 5497-5503 |
| 英文摘要 | To address the problem of building accurate and coherent models for large-scale terrains from incomplete and noisy sensor data, this paper proposes a novel framework that can efficiently infer terrain structures by divisionally providing the best linear unbiased estimates for the elevation values. To avoid data ambiguity caused by the uncertainty of sensor data, the proposed method introduces elevation filtering to extract the terrain surfaces, which reduces the amount of data greatly while the contained terrain information is basically unchanged. Then, for the large-scale terrains, the Gaussian mixture model is used to divide the interested regions, which remarkably improves the prediction accuracy and speed. Finally, for each subregion, a gaussian process regression model based on the static kernel is used to create a multiresolution terrain representation, which can deal with incompleteness of sensor data by considering the spatial correlations of the terrain. Evaluations of the proposed technique were conducted on diverse large-scale field terrains, including the quarry, planetary emulation terrain and highland, showing that the proposed method outperforms the state-of-art terrain modeling techniques in terms of the prediction accuracy, computation speed and memory consumption. As a practical application, the path planning problem was explored based on this terrain modeling technique to produce a better path. |
| 源文献作者 | Baidu ; Biomimetic Intelligence and Robotics ; dji ; et al. ; Mech Mind Robotics Technologies ; Toyota Research Institute |
| 产权排序 | 1 |
| 会议录 | 2021 IEEE International Conference on Robotics and Automation, ICRA 2021
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISSN号 | 1050-4729 |
| ISBN号 | 978-1-7281-9077-8 |
| WOS记录号 | WOS:000765738804032 |
| 源URL | [http://ir.sia.cn/handle/173321/30558]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Liu X(刘旭) |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing 100049, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 3.The State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Liu X,Li DC,He YQ. Multiresolution Representations for Large-Scale Terrain with Local Gaussian Process Regression[C]. 见:. Xi'an, China. May 30 - June 5, 2021. |
入库方式： OAI收割
来源：沈阳自动化研究所
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