Navigating by touch: haptic Monte Carlo localization via geometric sensing and terrain classification
| Autor: | Michał Nowicki, Marco Camurri, Maurice Fallon, Russell Buchanan, Krzysztof Walas, Jakub Bednarek |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Terrain classification business.industry Computer science Monte Carlo method Monte Carlo localization Terrain Computer Science - Robotics Legged robots Artificial Intelligence Inertial measurement unit Robot Proprioceptive localization Computer vision Artificial intelligence Legged robot business Robotics (cs.RO) Tactile sensing Pose Haptic technology |
| Zdroj: | Buchanan, R, Bednarek, J, Camurri, M, Nowicki, M R, Walas, K & Fallon, M 2021, ' Navigating by touch : Haptic Monte Carlo localization via geometric sensing and terrain classification ', Autonomous Robots, vol. 45, no. 6, pp. 843-857 . https://doi.org/10.1007/s10514-021-10013-w |
| ISSN: | 1573-7527 0929-5593 |
| Popis: | Legged robot navigation in extreme environments can hinder the use of cameras and laser scanners due to darkness, air obfuscation or sensor damage. In these conditions, proprioceptive sensing will continue to work reliably. In this paper, we propose a purely proprioceptive localization algorithm which fuses information from both geometry and terrain class, to localize a legged robot within a prior map. First, a terrain classifier computes the probability that a foot has stepped on a particular terrain class from sensed foot forces. Then, a Monte Carlo-based estimator fuses this terrain class probability with the geometric information of the foot contact points. Results are demonstrated showing this approach operating online and onboard a ANYmal B300 quadruped robot traversing a series of terrain courses with different geometries and terrain types over more than 1.2km. The method keeps the localization error below 20cm using only the information coming from the feet, IMU, and joints of the quadruped. Autonomous Robots. arXiv admin note: substantial text overlap with arXiv:2005.01567 |
| Databáze: | OpenAIRE |
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