<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></abstract>

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.

RGB–D terrain perception and dense mapping for legged robots

Institute of Control and Information Engineering, Poznań University of Technology, ul. Piotrowo 3A, 60-965 Poznań, Poland

Autonomous Systems Lab, ETH Zurich, LEE J 201, Leonhardstrasse 21, 8092 Zurich, Switzerland

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"RGB\u2013D terrain perception and dense mapping for legged robots"}

This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid...

RGB–D terrain perception and dense mapping for legged robots

Publié en ligne: 31 mars 2016

Pages: 81 - 97

Reçu: 03 oct. 2014

DOI: https://doi.org/10.1515/amcs-2016-0006

Mots clés
RGB-D perception, elevation mapping, uncertainty, legged robots

© 2016 Dominik Belter et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

RGB–D terrain perception and dense mapping for legged robots

Publié en ligne: 31 mars 2016

Pages: 81 - 97

Reçu: 03 oct. 2014

DOI: https://doi.org/10.1515/amcs-2016-0006

Mots clésRGB-D perception, elevation mapping, uncertainty, legged robots

© 2016 Dominik Belter et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
RGB-D perception, elevation mapping, uncertainty, legged robots