STATE ESTIMATION FOR AQUATIC ROBOTS IN COMPLEX ENVIRONMENTS
Lead Research Organisation:
University of Manchester
Department Name: Electrical and Electronic Engineering
Abstract
Localisation for aquatic robots in confined environments is necessary for autonomous inspection and monitoring, of locations, not limited to, nuclear storage facilities, flooded mines, and offshore oil and gas rigs. Historically, the majority of research in this area has focused on open waters and large marine environments. Localisation in confined environments however, presents a different set of challenges and due to the smaller scale of confined areas necessitates a higher degree of accuracy (sub-centimetre), precision and repeatability than is typically required at sea. Additionally, robots that work in small environments tend to have a limited sensor payload than their open water analogues due to their reduced size, whilst confined environments render certain sensors such as satellite based global positioning systems unusable. This often means that some established localisation solutions are not implementable.
The research focuses on localisation for small autonomous aquatic robots whose primary use case fits and operating condition fit the above description. A deadreckoning system for localisation will be developed which is capable of running on any aquatic robot with an inertial measurement unit (IMU) and a velocity reading from a sensor such as a Doppler velocity log (DVL). This deadreckoning system can provide an odometry reading for Simultaneous Localisation and Mapping (SLAM) algorithms or be used as a short-term stand-alone or backup localisation system.
The research focuses on localisation for small autonomous aquatic robots whose primary use case fits and operating condition fit the above description. A deadreckoning system for localisation will be developed which is capable of running on any aquatic robot with an inertial measurement unit (IMU) and a velocity reading from a sensor such as a Doppler velocity log (DVL). This deadreckoning system can provide an odometry reading for Simultaneous Localisation and Mapping (SLAM) algorithms or be used as a short-term stand-alone or backup localisation system.
Organisations
People |
ORCID iD |
Keir Groves (Primary Supervisor) | |
Jessica Paterson (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/T517823/1 | 01/10/2020 | 30/09/2025 | |||
2857230 | Studentship | EP/T517823/1 | 01/07/2021 | 31/12/2024 | Jessica Paterson |