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Mechanism-parameters optimization of a reconfigurable tracked mobile modular deep-sea Rover ROV
Zhang YX(张运修)1,2; Zhang QF(张奇峰)1; Zhang AQ(张艾群)1; He XH(何旭欢)1,2; Wang C(王聪)1,2; Xu DC(徐东岑)1,2
Department水下机器人研究室
Conference NameOCEANS 2018 MTS/IEEE Kobe
Conference DateMay 28-31, 2018
Conference PlaceKobe, Japan
Source PublicationOCEANS 2018 MTS/IEEE Kobe
PublisherIEEE
Publication PlaceNew York
2018
Pages1-7
Indexed ByEI
EI Accession number20190406415898
Contribution Rank1
ISBN978-1-5386-1654-3
KeywordReconfigurable Tracked Mobile Modular deep-sea rover ROV Crawling obstacles Mechanism-parameters design Multi-objective Genetic Algorithm
AbstractIt is extremely difficult and expensive to operate a traditional remotely operated vehicle (ROV) in the deep sea. In this paper, a small and reconfigurable tracked mobile modular deep-sea rover ROV (R-ROV) is designed to conduct regional fine-sounding operations. The R-ROV can be placed inside a deep-sea lander, which can be operated in 3000m depth seafloor. When the lander lands seafloor, R-ROV can walk out in crawling or cruising mode operated in a fan-shaped area with long working time. In order to obtain mechanism-parameters and improve R-ROV’s adaptability and motility, multi-objective genetic algorithm is used in this paper. So the relationship between the objective functions and mechanism-parameters of the transformable vehicle is established. There are two typical objective obstacles for the crawl mode R-ROV, stair and gully. However, different from the robot walking on land, it is difficult to find the optimal configuration across the stairs underwater because of the buoyancy of water. This paper proposes a method to obtain optimized mechanism-parameters for the R-ROV considering the underwater environment, which has been calculated through simulation. The results are reported in detail. © 2018 IEEE.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/24127
Collection水下机器人研究室
Corresponding AuthorZhang YX(张运修); Zhang QF(张奇峰)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences (CAS), Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Zhang YX,Zhang QF,Zhang AQ,et al. Mechanism-parameters optimization of a reconfigurable tracked mobile modular deep-sea Rover ROV[C]. New York:IEEE,2018:1-7.
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