Mobile robots can readily map static environments for world building and navigation. But what if the environment is constantly changing? For researchers interested in understanding phenomena that change in both space and time, observations are vital. Current measurements techniques may require the deployment of vast arrays of sensors and manual observation campaigns by personnel, which are both slow and costly. If mobile robots can collect and synthesize data from ever-changing environments, such campaigns could be cheaper, faster, and more responsive.
Publications and Videos
Mapping Waves with an Uncrewed Surface Vessel
This work will be presented at ICRA 2023 in London, United Kingdom.
T. M. C. Sears, M. R. Cooper, and J. A. Marshall. Mapping waves with an uncrewed surface vessel via Gaussian process regression. To appear in Proceedings of the 2023 IEEE International Conference on Robotics & Automation (ICRA), London, UK, May-June 2023. [Preprint PDF]
Spatiotemporal Mapping by Mobile Robots
This work was presented at IROS 2022 in Kyoto, Japan.
T. M. C. Sears and J. A. Marshall. Mapping of spatiotemporal scalar fields by mobile robots using Gaussian process regression. In Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan, October 2022. DOI: 10.1109/IROS47612.2022.9981548 [Preprint PDF]