TY - JOUR
T1 - Virtual Maps for Autonomous Exploration of Cluttered Underwater Environments
AU - Wang, Jinkun
AU - Chen, Fanfei
AU - Huang, Yewei
AU - McConnell, John
AU - Shan, Tixiao
AU - Englot, Brendan
N1 - Publisher Copyright:
© 1976-2012 IEEE.
PY - 2022/10/1
Y1 - 2022/10/1
N2 - We consider the problem of autonomous mobile robot exploration in an unknown environment, taking into account a robot's coverage rate, map uncertainty and state estimation uncertainty. In this article, we present a novel exploration framework for underwater robots operating in cluttered environments, built upon simultaneous localization and mapping with imaging sonar. The proposed system comprises path generation, place recognition forecasting, belief propagation and utility evaluation using a virtual map, which estimates the uncertainty associated with map cells throughout a robot's workspace. We evaluate the performance of this framework in simulated experiments, showing that our algorithm maintains a high coverage rate during exploration while also maintaining low mapping and localization error. The real-world applicability of our framework is also demonstrated on an underwater remotely operated vehicle exploring a harbor environment.
AB - We consider the problem of autonomous mobile robot exploration in an unknown environment, taking into account a robot's coverage rate, map uncertainty and state estimation uncertainty. In this article, we present a novel exploration framework for underwater robots operating in cluttered environments, built upon simultaneous localization and mapping with imaging sonar. The proposed system comprises path generation, place recognition forecasting, belief propagation and utility evaluation using a virtual map, which estimates the uncertainty associated with map cells throughout a robot's workspace. We evaluate the performance of this framework in simulated experiments, showing that our algorithm maintains a high coverage rate during exploration while also maintaining low mapping and localization error. The real-world applicability of our framework is also demonstrated on an underwater remotely operated vehicle exploring a harbor environment.
KW - Autonomous underwater vehicles (AUVs)
KW - motion planning
KW - simultaneous localization and mapping (SLAM)
KW - sonar navigation
UR - http://www.scopus.com/inward/record.url?scp=85133556809&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85133556809&partnerID=8YFLogxK
U2 - 10.1109/JOE.2022.3153897
DO - 10.1109/JOE.2022.3153897
M3 - Article
AN - SCOPUS:85133556809
SN - 0364-9059
VL - 47
SP - 916
EP - 935
JO - IEEE Journal of Oceanic Engineering
JF - IEEE Journal of Oceanic Engineering
IS - 4
ER -