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Paper details
Number 1 - March 2016
Volume 26 - 2016
RGB-D terrain perception and dense mapping for legged robots
Dominik Belter, Przemysław Łabecki, Péter Fankhauser, Roland Siegwart
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.
Keywords
RGB-D perception, elevation mapping, uncertainty, legged robots