期刊
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE
卷 26, 期 1, 页码 81-97出版社
UNIV ZIELONA GORA PRESS
DOI: 10.1515/amcs-2016-0006
关键词
RGB-D perception; elevation mapping; uncertainty; legged robots
资金
- Polish National Science Centre [DEC-2013/09/B/ST7/01583]
- Swiss National Science Foundation (SNF) [200021_149427/1]
- National Centre of Competence in Research Robotics
- Swiss National Science Foundation (SNF) [200021_149427] Funding Source: Swiss National Science Foundation (SNF)
This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used to produce a dense depth map. The model for the uncertainty of the stereo vision camera is based on uncertainty propagation from calibration, through undistortion and rectification algorithms, allowing calculation of the uncertainty of measured 3D point coordinates. The proposed uncertainty models were used for the construction of a terrain elevation map using the Videre Design STOC stereo vision camera and Kinect-like range sensors. We provide experimental verification of the proposed mapping method, and a comparison with another recently published terrain mapping method for walking robots.
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