TY - GEN
T1 - Terrain-Relative Diver following with Autonomous Underwater Vehicle for Coral Reef Mapping
AU - Prasad Antervedi, Lakshmi Gana
AU - Chen, Zhiang
AU - Anand, Harish
AU - Martin, Roberta
AU - Arrowsmith, Ramon
AU - Das, Jnaneshwar
N1 - Funding Information:
*This work was supported in part by NSF award CNS-1521617 Authors are with Arizona State University, Tempe, Arizona. Lakshmi, Zhiang, Harish, Ramon and Jnaneshwar are with School of Earth and Space Exploration. Roberta Martin is with School of Geographical Sciences and Urban Planning. lanterve, zchen256, hanand4, Roberta.Martin, ramon.arrowsmith, jdas5@asu.edu
Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/23
Y1 - 2021/8/23
N2 - Coral reef mapping is an indispensable step in coral conservation efforts across the globe. Monitoring reefs at regular intervals helps conservationists understand and address the problems causing coral reef degradation. Autonomous Underwater Vehicles (AUVs) have a tremendous potential to assist humans in these efforts. Delegating mapping and measurement acquisition tasks to AUVs would not only limit the number of human divers required for the missions but could also improve the quality of the maps developed. Consistency in imagery and spectroscopic measurements could be significantly improved by keeping the imagery payload at a fixed distance from the reefs to reduce heteroscedasticity in the measurements. To this end, we present a Terrain-Relative Diver Following system for an AUV that can follow a human diver while maintaining a fixed distance from the terrain. Our proposed system consists of separate modules for diver detection, tracking, and terrain following. We extensively tested our system in Gazebo simulation environment with three different terrain models, including a terrain model of a coral reef in Honaunau Bay, Hawaii. To the best of our knowledge, this is the first diver following system that also carries out terrain-relative navigation, ensuring minimal variation of distance to the terrain. We have released the code for our system, and the datasets used in the detection module.
AB - Coral reef mapping is an indispensable step in coral conservation efforts across the globe. Monitoring reefs at regular intervals helps conservationists understand and address the problems causing coral reef degradation. Autonomous Underwater Vehicles (AUVs) have a tremendous potential to assist humans in these efforts. Delegating mapping and measurement acquisition tasks to AUVs would not only limit the number of human divers required for the missions but could also improve the quality of the maps developed. Consistency in imagery and spectroscopic measurements could be significantly improved by keeping the imagery payload at a fixed distance from the reefs to reduce heteroscedasticity in the measurements. To this end, we present a Terrain-Relative Diver Following system for an AUV that can follow a human diver while maintaining a fixed distance from the terrain. Our proposed system consists of separate modules for diver detection, tracking, and terrain following. We extensively tested our system in Gazebo simulation environment with three different terrain models, including a terrain model of a coral reef in Honaunau Bay, Hawaii. To the best of our knowledge, this is the first diver following system that also carries out terrain-relative navigation, ensuring minimal variation of distance to the terrain. We have released the code for our system, and the datasets used in the detection module.
UR - http://www.scopus.com/inward/record.url?scp=85117058769&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85117058769&partnerID=8YFLogxK
U2 - 10.1109/CASE49439.2021.9551624
DO - 10.1109/CASE49439.2021.9551624
M3 - Conference contribution
AN - SCOPUS:85117058769
T3 - IEEE International Conference on Automation Science and Engineering
SP - 2307
EP - 2312
BT - 2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021
PB - IEEE Computer Society
T2 - 17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Y2 - 23 August 2021 through 27 August 2021
ER -