Suryamurthy, V;
Sushrutha Raghavan, V;
Laurenzi, A;
Tsagarakis, N;
Kanoulas, D;
(2019)
Terrain Segmentation and Roughness Estimation using RGB Data: Path Planning Application on the CENTAURO Robot.
In:
2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids).
(pp. pp. 289-296).
IEEE-RAS
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P28__Suryamurthy_Raghavan_Laurenzi_Tsagarakis_Kanoulas__2019__Terrain_Segmentation_and_Roughness_Estimation_using_RGB_Data-Path_Planning_Application_on_the_CENTAURO_Robot.pdf - Accepted Version Download (2MB) | Preview |
Abstract
Robots operating in real world environments require a high-level perceptual understanding of the chief physical properties of the terrain they are traversing. In unknown environments, roughness is one such important terrain property that could play a key role in devising robot control/planning strategies. In this paper, we present a fast method for predicting pixel-wise labels of terrain (stone, sand, road/sidewalk, wood, grass, metal) and roughness estimation, using a single RGB-based deep neural network. Real world RGB images are used to experimentally validate the presented approach. Furthermore, we demonstrate an application of our proposed method on the centaur-like wheeled-legged robot CENTAURO, by integrating it with a navigation planner that is capable of re-configuring the leg joints to modify the robot footprint polygon for stability purposes or for safe traversal among obstacles.
| Type: | Proceedings paper |
|---|---|
| Title: | Terrain Segmentation and Roughness Estimation using RGB Data: Path Planning Application on the CENTAURO Robot |
| Event: | Proceedings of the 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids) |
| Location: | Toronto (ON), Canada |
| Dates: | 15th-17th October 2019 |
| ISBN-13: | 978-1-5386-7630- |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/Humanoids43949.2019.9035009 |
| Publisher version: | https://doi.org/10.1109/Humanoids43949.2019.903500... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | collision avoidance, image colour analysis, image segmentation, image sensors, legged locomotion, navigation, neural nets, path planning |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10083218 |
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