Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments. Issue 3 (9th November 2020)
- Record Type:
- Journal Article
- Title:
- Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments. Issue 3 (9th November 2020)
- Main Title:
- Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments
- Authors:
- Salavasidis, Georgios
Munafò, Andrea
Fenucci, Davide
Harris, Catherine A.
Prampart, Thomas
Templeton, Robert
Smart, Michael
Roper, Daniel T.
Pebody, Miles
Abrahamsen, E. Povl
McPhail, Stephen D.
Rogers, Eric
Phillips, Alexander B. - Abstract:
- Abstract: Deploying long‐range autonomous underwater vehicles (AUVs) mid‐water column in the deep ocean is one of the most challenging applications for these submersibles. Without external support and speed over the ground measurements, dead‐reckoning (DR) navigation inevitably experiences an error proportional to the mission range and the speed of the water currents. In response to this problem, a computationally feasible and low‐power terrain‐aided navigation (TAN) system is developed. A Rao‐Blackwellized Particle Filter robust to estimation divergence is designed to estimate the vehicle's position and the speed of water currents. To evaluate performance, field data from multiday AUV deployments in the Southern Ocean are used. These form a unique test case for assessing the TAN performance under extremely challenging conditions. Despite the use of a small number of low‐power sensors and a Doppler velocity log to enable TAN, the algorithm limits the localisation error to within a few hundreds of metres, as opposed to a DR error of 40 km, given a 50 m resolution bathymetric map. To evaluate further the effectiveness of the system under a varying map quality, grids of 100, 200, and 400 m resolution are generated by subsampling the original 50 m resolution map. Despite the high complexity of the navigation problem, the filter exhibits robust and relatively accurate behaviour. Given the current aim of the oceanographic community to develop maps of similar resolution, theAbstract: Deploying long‐range autonomous underwater vehicles (AUVs) mid‐water column in the deep ocean is one of the most challenging applications for these submersibles. Without external support and speed over the ground measurements, dead‐reckoning (DR) navigation inevitably experiences an error proportional to the mission range and the speed of the water currents. In response to this problem, a computationally feasible and low‐power terrain‐aided navigation (TAN) system is developed. A Rao‐Blackwellized Particle Filter robust to estimation divergence is designed to estimate the vehicle's position and the speed of water currents. To evaluate performance, field data from multiday AUV deployments in the Southern Ocean are used. These form a unique test case for assessing the TAN performance under extremely challenging conditions. Despite the use of a small number of low‐power sensors and a Doppler velocity log to enable TAN, the algorithm limits the localisation error to within a few hundreds of metres, as opposed to a DR error of 40 km, given a 50 m resolution bathymetric map. To evaluate further the effectiveness of the system under a varying map quality, grids of 100, 200, and 400 m resolution are generated by subsampling the original 50 m resolution map. Despite the high complexity of the navigation problem, the filter exhibits robust and relatively accurate behaviour. Given the current aim of the oceanographic community to develop maps of similar resolution, the results of this study suggest that TAN can enable AUV operations of the order of months using global bathymetric models. … (more)
- Is Part Of:
- Journal of field robotics. Volume 38:Issue 3(2021)
- Journal:
- Journal of field robotics
- Issue:
- Volume 38:Issue 3(2021)
- Issue Display:
- Volume 38, Issue 3 (2021)
- Year:
- 2021
- Volume:
- 38
- Issue:
- 3
- Issue Sort Value:
- 2021-0038-0003-0000
- Page Start:
- 402
- Page End:
- 428
- Publication Date:
- 2020-11-09
- Subjects:
- long‐range AUVs -- long‐range terrain‐aided navigation -- nonlinear filtering
Robots, Industrial -- Periodicals
Automatic control -- Periodicals
629.892 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1556-4967 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/rob.21994 ↗
- Languages:
- English
- ISSNs:
- 1556-4959
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4984.130000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16189.xml