Efficient path planning of AUVs for container ship oil spill detection in coastal areas. (1st December 2020)
- Record Type:
- Journal Article
- Title:
- Efficient path planning of AUVs for container ship oil spill detection in coastal areas. (1st December 2020)
- Main Title:
- Efficient path planning of AUVs for container ship oil spill detection in coastal areas
- Authors:
- Vinoth Kumar, S.
Jayaparvathy, R.
Priyanka, B.N. - Abstract:
- Abstract: Oil spills due to accidental leakage from Container Ships in a Marine environment poses a major challenge to aquatic living organisms and affects human health by increasing the environmental pollution. Autonomous Underwater Vehicles (AUV's) are deployed for detection and cleaning of oil spills. As the coastal areas are vast and lengthy, effective path planning of deployed AUVs is necessary. Many path planning algorithms for AUVs have been proposed in literature using approaches which necessitate search through large distance. The AUVs have to travel through a large distance to detect the spills in the search area resulting in more energy consumption. In this article we propose an efficient approach for determination of optimal AUV paths for detection of oil spills resulting in reduced search distance for a given area. The proposed approach implements a hybrid evolutionary optimization algorithm named Whale Cuckoo Search Optimization Algorithm (WCSOA) that results in increase in the search space, global search ability and the convergence speed. With the proposed approach the overall search delay and energy consumption of AUVs are reduced. It is observed from the simulation results obtained that the proposed approach provides reduction in AUV energy consumption by 57% compared to the existing Boustrophedon and WOA approach. Highlights: WCSOA (Whale Cuckoo Search Optimization Algorithm) has been proposed for the efficient path planning algorithm. Levy flight propertyAbstract: Oil spills due to accidental leakage from Container Ships in a Marine environment poses a major challenge to aquatic living organisms and affects human health by increasing the environmental pollution. Autonomous Underwater Vehicles (AUV's) are deployed for detection and cleaning of oil spills. As the coastal areas are vast and lengthy, effective path planning of deployed AUVs is necessary. Many path planning algorithms for AUVs have been proposed in literature using approaches which necessitate search through large distance. The AUVs have to travel through a large distance to detect the spills in the search area resulting in more energy consumption. In this article we propose an efficient approach for determination of optimal AUV paths for detection of oil spills resulting in reduced search distance for a given area. The proposed approach implements a hybrid evolutionary optimization algorithm named Whale Cuckoo Search Optimization Algorithm (WCSOA) that results in increase in the search space, global search ability and the convergence speed. With the proposed approach the overall search delay and energy consumption of AUVs are reduced. It is observed from the simulation results obtained that the proposed approach provides reduction in AUV energy consumption by 57% compared to the existing Boustrophedon and WOA approach. Highlights: WCSOA (Whale Cuckoo Search Optimization Algorithm) has been proposed for the efficient path planning algorithm. Levy flight property of Cuckoo search is incorporated with WOA in the exploration phase to increase the search space, global search ability and the convergence speed. The proposed WCSOA approach uses Cuckoo Search as an augmentation to the Whale Optimization Algorithm to select the best path for the AUV to detect the oil spills. The proposed approach provides reduction in distance travelled and energy consumption of the AUV to detect the oil spills. … (more)
- Is Part Of:
- Ocean engineering. Volume 217(2020)
- Journal:
- Ocean engineering
- Issue:
- Volume 217(2020)
- Issue Display:
- Volume 217, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 217
- Issue:
- 2020
- Issue Sort Value:
- 2020-0217-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-12-01
- Subjects:
- AUV -- Optimization -- Oil spill -- Whale optimization algorithm -- Cuckoo search algorithm
Ocean engineering -- Periodicals
Ocean engineering
Periodicals
620.4162 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00298018 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.oceaneng.2020.107932 ↗
- Languages:
- English
- ISSNs:
- 0029-8018
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6231.280000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14997.xml