On Hierarchical Multi-UAV Dubins Traveling Salesman Problem Paths in a Complex Obstacle Environment
This article aims to solve a hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP). Optimal hierarchical coverage and multi-UAV collaboration are achieved by the proposed approaches in a 3-D complex obstacle environment. A multi-UAV multilayer projection clustering (MMPC) algorithm is pr...
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description | This article aims to solve a hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP). Optimal hierarchical coverage and multi-UAV collaboration are achieved by the proposed approaches in a 3-D complex obstacle environment. A multi-UAV multilayer projection clustering (MMPC) algorithm is presented to reduce the cumulative distance from multilayer targets to corresponding cluster centers. A straight-line flight judgment (SFJ) was developed to reduce the calculation of obstacle avoidance. An improved adaptive window probabilistic roadmap (AWPRM) algorithm is addressed to plan obstacle-avoidance paths. The AWPRM improves the feasibility of finding the optimal sequence based on the proposed SFJ compared with a traditional probabilistic roadmap. To solve the solution to TSP with obstacles constraints, the proposed sequencing-bundling-bridging (SBB) framework combines the bundling ant colony system (BACS) and homotopic AWPRM. An obstacle-avoidance optimal curved path is constructed with a turning radius constraint based on the Dubins method and followed up by solving the TSP sequence. The results of simulation experiments indicated that the proposed strategies can provide a set of feasible solutions for HMDTSPs in a complex obstacle environment. |
doi_str_mv | 10.1109/TCYB.2023.3265926 |
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Optimal hierarchical coverage and multi-UAV collaboration are achieved by the proposed approaches in a 3-D complex obstacle environment. A multi-UAV multilayer projection clustering (MMPC) algorithm is presented to reduce the cumulative distance from multilayer targets to corresponding cluster centers. A straight-line flight judgment (SFJ) was developed to reduce the calculation of obstacle avoidance. An improved adaptive window probabilistic roadmap (AWPRM) algorithm is addressed to plan obstacle-avoidance paths. The AWPRM improves the feasibility of finding the optimal sequence based on the proposed SFJ compared with a traditional probabilistic roadmap. To solve the solution to TSP with obstacles constraints, the proposed sequencing-bundling-bridging (SBB) framework combines the bundling ant colony system (BACS) and homotopic AWPRM. An obstacle-avoidance optimal curved path is constructed with a turning radius constraint based on the Dubins method and followed up by solving the TSP sequence. The results of simulation experiments indicated that the proposed strategies can provide a set of feasible solutions for HMDTSPs in a complex obstacle environment.</description><identifier>ISSN: 2168-2267</identifier><identifier>EISSN: 2168-2275</identifier><identifier>DOI: 10.1109/TCYB.2023.3265926</identifier><identifier>PMID: 37099468</identifier><identifier>CODEN: ITCEB8</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Ant colony optimization ; Autonomous aerial vehicles ; Bundling ; Bundling ant colony system (BACS) ; Clustering ; Clustering algorithms ; Collision avoidance ; Feasibility ; Heuristic algorithms ; hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP) ; homotopic adaptive window probabilistic roadmap (AWPRM) ; Multilayers ; Nonhomogeneous media ; Obstacle avoidance ; Probabilistic logic ; Sequences ; Traveling salesman problem ; Traveling salesman problems ; Unmanned aerial vehicles ; Vehicle dynamics</subject><ispartof>IEEE transactions on cybernetics, 2024-01, Vol.54 (1), p.123-135</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Optimal hierarchical coverage and multi-UAV collaboration are achieved by the proposed approaches in a 3-D complex obstacle environment. A multi-UAV multilayer projection clustering (MMPC) algorithm is presented to reduce the cumulative distance from multilayer targets to corresponding cluster centers. A straight-line flight judgment (SFJ) was developed to reduce the calculation of obstacle avoidance. An improved adaptive window probabilistic roadmap (AWPRM) algorithm is addressed to plan obstacle-avoidance paths. The AWPRM improves the feasibility of finding the optimal sequence based on the proposed SFJ compared with a traditional probabilistic roadmap. To solve the solution to TSP with obstacles constraints, the proposed sequencing-bundling-bridging (SBB) framework combines the bundling ant colony system (BACS) and homotopic AWPRM. An obstacle-avoidance optimal curved path is constructed with a turning radius constraint based on the Dubins method and followed up by solving the TSP sequence. The results of simulation experiments indicated that the proposed strategies can provide a set of feasible solutions for HMDTSPs in a complex obstacle environment.</description><subject>Algorithms</subject><subject>Ant colony optimization</subject><subject>Autonomous aerial vehicles</subject><subject>Bundling</subject><subject>Bundling ant colony system (BACS)</subject><subject>Clustering</subject><subject>Clustering algorithms</subject><subject>Collision avoidance</subject><subject>Feasibility</subject><subject>Heuristic algorithms</subject><subject>hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP)</subject><subject>homotopic adaptive window probabilistic roadmap (AWPRM)</subject><subject>Multilayers</subject><subject>Nonhomogeneous media</subject><subject>Obstacle avoidance</subject><subject>Probabilistic logic</subject><subject>Sequences</subject><subject>Traveling salesman problem</subject><subject>Traveling salesman problems</subject><subject>Unmanned aerial vehicles</subject><subject>Vehicle dynamics</subject><issn>2168-2267</issn><issn>2168-2275</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkV1LHDEUhkOpqNj9AUKRQG-8mW0-ZjLJpa62FpRdcC30KmQyZ2okk1mTGbH_vll2K8Xc5IPnPOScF6FTSuaUEvV1vfh1OWeE8TlnolJMfEDHjApZMFZXH9_Ooj5Cs5SeSF4yPyl5iI54TZQqhTxGdhnwjYNoon101nh8N_nRFQ8XP_HV1LiQ8DqaF_Au_Mb3xkPqTcCrODQeerwy42PCLmCDF0O_8fCKl00ajfWAr8OLi0PoIYyf0EFnfILZfj9BD9-u14ub4nb5_cfi4rawJRVjoRpOTdkYynndttJSSUTTGeA2d0mqTnLScEGJlSXvKqWE4W2rJIGupmJ7O0HnO-8mDs8TpFH3Llnw3gQYpqRZFpaVZIxm9Ms79GmYYsi_00yRUpCK1SpTdEfZOKQUodOb6HoT_2hK9DYEvQ1Bb0PQ-xByzdnePDU9tG8V_0aegc87wAHAf8KsY4Twv7HBiWY</recordid><startdate>202401</startdate><enddate>202401</enddate><creator>Fu, Jinyu</creator><creator>Sun, Guanghui</creator><creator>Liu, Jianxing</creator><creator>Yao, Weiran</creator><creator>Wu, Ligang</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Optimal hierarchical coverage and multi-UAV collaboration are achieved by the proposed approaches in a 3-D complex obstacle environment. A multi-UAV multilayer projection clustering (MMPC) algorithm is presented to reduce the cumulative distance from multilayer targets to corresponding cluster centers. A straight-line flight judgment (SFJ) was developed to reduce the calculation of obstacle avoidance. An improved adaptive window probabilistic roadmap (AWPRM) algorithm is addressed to plan obstacle-avoidance paths. The AWPRM improves the feasibility of finding the optimal sequence based on the proposed SFJ compared with a traditional probabilistic roadmap. To solve the solution to TSP with obstacles constraints, the proposed sequencing-bundling-bridging (SBB) framework combines the bundling ant colony system (BACS) and homotopic AWPRM. An obstacle-avoidance optimal curved path is constructed with a turning radius constraint based on the Dubins method and followed up by solving the TSP sequence. The results of simulation experiments indicated that the proposed strategies can provide a set of feasible solutions for HMDTSPs in a complex obstacle environment.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>37099468</pmid><doi>10.1109/TCYB.2023.3265926</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-1623-2220</orcidid><orcidid>https://orcid.org/0000-0002-8160-9680</orcidid><orcidid>https://orcid.org/0000-0002-2201-3887</orcidid><orcidid>https://orcid.org/0000-0002-6570-3888</orcidid><orcidid>https://orcid.org/0000-0001-8198-5267</orcidid></addata></record> |
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subjects | Algorithms Ant colony optimization Autonomous aerial vehicles Bundling Bundling ant colony system (BACS) Clustering Clustering algorithms Collision avoidance Feasibility Heuristic algorithms hierarchical multi-UAV Dubins traveling salesman problem (HMDTSP) homotopic adaptive window probabilistic roadmap (AWPRM) Multilayers Nonhomogeneous media Obstacle avoidance Probabilistic logic Sequences Traveling salesman problem Traveling salesman problems Unmanned aerial vehicles Vehicle dynamics |
title | On Hierarchical Multi-UAV Dubins Traveling Salesman Problem Paths in a Complex Obstacle Environment |
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