Mapping repetitive structural tunnel environments for a biologically-inspired climbing robot
- Publication Type:
- Conference Proceeding
- Assistive Robotics: Proceedings of the 18th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, CLAWAR 2015, 2015, pp. 325 - 333
- Issue Date:
© 2015, World Scientific Publishing Co. Pte Ltd. All rights reserved. This paper presents an approach to using noisy and incomplete depth-camera datasets to detect reliable surface features for use in map construction for a caterpillar-inspired climbing robot. The approach uses a combination of plane extraction, clustering and template matching techniques to infer from the restricted dataset a usable map. This approach has been tested in both laboratory and real-world steel bridge tunnel datasets generated by a climbing robot, with the results showing that the generated maps are accurate enough for use in localisation and step trajectory planning.
Please use this identifier to cite or link to this item: