Article contents
Self-Localization in Highly Dynamic Environments Based on Dual-Channel Unscented Particle Filter
Published online by Cambridge University Press: 19 November 2020
Summary
Self-localization in highly dynamic environments is still a challenging problem for humanoid robots with limited computation resource. In this paper, we propose a dual-channel unscented particle filter (DC-UPF)-based localization method to address it. A key novelty of this approach is that it employs a dual-channel switch mechanism in measurement updating procedure of particle filter, solving for sparse vision feature in motion, and it leverages data from a camera, a walking odometer, and an inertial measurement unit. Extensive experiments with an NAO robot demonstrate that DC-UPF outperforms UPF and Monte–Carlo localization with regard to accuracy.
Keywords
- Type
- Article
- Information
- Copyright
- © The Author(s), 2020. Published by Cambridge University Press
References
- 4
- Cited by