RGB-D terrain perception and dense mapping for legged robots

• Autorzy: Belter D. , Łabecki P , Fankhauser P. , Siegwart R.

Identyfikatory

DOI

10.1515/amcs-2016-0006

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

RGB-D perception; elevation mapping; uncertainty; legged robots

PL

RGB-D; niepewność; robot nożny

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2016
• Tom: Vol. 26, no. 1
• Strony: 81--97
• Opis fizyczny: Bibliogr. 43 poz., rys., tab., wykr.

Twórcy

autor

Belter D.

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

autor

Łabecki P

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

autor

Fankhauser P.

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

autor

Siegwart R.

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

Bibliografia

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.