Paper Info
Title
Stereo-vision-based navigation of a six-legged walking robot in unknown rough terrain
Abstract
In this paper we present a visual navigation algorithm for the six-legged walking robot DLR Crawler in rough terrain. The algorithm is based on stereo images from which depth images are computed using the semi-global matching (SGM) method. Further, a visual odometry is calculated along with an error measure. Pose estimates are obtained by fusing inertial data with relative leg odometry and visual odometry measurements using an indirect information filter. The visual odometry error measure is used in the filtering process to put lower weights on erroneous visual odometry data, hence, improving the robustness of pose estimation. From the estimated poses and the depth images, a dense digital terrain map is created by applying the locus method. The traversability of the terrain is estimated by a plane fitting approach and paths are planned using a D* Lite planner taking the traversability of the terrain and the current motion capabilities of the robot into account. Motion commands and the traversability measures of the upcoming terrain are sent to the walking layer of the robot so that it can choose an appropriate gait for the terrain. Experimental results show the accuracy of the navigation algorithm and its robustness against visual disturbances.
Year
DOI
Venue
2012
10.1177/0278364911435161
I. J. Robotic Res.
Keywords
Field
DocType
Stereo vision,mapping,pose estimation,sensor fusion,rough terrain navigation,walking robots
Computer vision,Visual odometry,Stereopsis,Terrain,Odometry,Robustness (computer science),Pose,Sensor fusion,Artificial intelligence,Robot,Mathematics
Journal
Volume
Issue
ISSN
31
4
0278-3649
Citations 
PageRank 
References 
31
1.32
25
Authors
3
Name
Order
Citations
PageRank
Annett Stelzer1442.99
Heiko Hirschmüller282745.70
Martin Görner3473.15