{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T12:54:49Z","timestamp":1766408089054,"version":"build-2065373602"},"reference-count":18,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T00:00:00Z","timestamp":1686614400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Michigan Technological University Research Excellence Fund-Research Seed Grant"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>This paper proposes an algorithm that provides operational strategies for multiple tethered autonomous underwater vehicle (T-AUV) systems for entanglement-free navigation. T-AUVs can perform underwater tasks under reliable communication and power supply, which is the most substantial benefit of their operation. Thus, if one can overcome the entanglement issues while utilizing multiple tethered vehicles, the potential applications of the system increase including ecosystem exploration, infrastructure inspection, maintenance, search and rescue, underwater construction, and surveillance. In this study, we focus on developing strategies for task allocation, path planning, and scheduling that ensure entanglement-free operations while considering workload balancing among the vehicles. We do not impose restrictions on the size or shape of the vehicles at this stage; our primary focus is on efficient tether management as an initial work on the topic. To achieve entanglement-free navigation, we propose a heuristic based on the primal-dual technique, which enables initial task allocation and path planning while minimizing the maximum travel cost of the vehicles. Although this heuristic often generates sectioned paths due to its workload-balancing nature, we also propose a mixed approach to provide feasible solutions for non-sectioned initial paths. This approach combines entanglement avoidance techniques with time scheduling and sectionalization methods. To evaluate the effectiveness of our algorithm, extensive simulations were conducted with varying problem sizes. The computational results demonstrate the potential of our algorithm to be applied in real-time operations, as it consistently generates reliable solutions within a reasonable time frame.<\/jats:p>","DOI":"10.3390\/robotics12030085","type":"journal-article","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T02:56:34Z","timestamp":1686624994000},"page":"85","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Coordinating Tethered Autonomous Underwater Vehicles towards Entanglement-Free Navigation"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4643-0471","authenticated-orcid":false,"given":"Abhishek","family":"Patil","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI 49931, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0060-9161","authenticated-orcid":false,"given":"Myoungkuk","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI 49931, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4673-2464","authenticated-orcid":false,"given":"Jungyun","family":"Bae","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering-Engineering Mechanics, Michigan Technological University, Houghton, MI 49931, USA"},{"name":"Department of Applied Computing, Michigan Technological University, Houghton, MI 49931, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,13]]},"reference":[{"key":"ref_1","first-page":"1111","article-title":"Underwater robotic vehicles: Latest development trends and potential challenges","volume":"26","author":"Tahir","year":"2014","journal-title":"Sci. Int."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Schmickl, T., Thenius, R., Moslinger, C., Timmis, J., Tyrrell, A., Read, M., Hilder, J., Halloy, J., Campo, A., and Stefanini, C. (2011, January 3\u20137). CoCoRo\u2013The self-aware underwater swarm. Proceedings of the 2011 Fifth IEEE Conference on Self-Adaptive and Self-Organizing Systems Workshops, Ann Arbor, MI, USA.","DOI":"10.1109\/SASOW.2011.11"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Sutantyo, D., Levi, P., M\u00f6slinger, C., and Read, M. (2013, January 4\u20137). Collective-adaptive L\u00e9vy flight for underwater multi-robot exploration. Proceedings of the 2013 IEEE International Conference on Mechatronics and Automation, Takamatsu, Japan.","DOI":"10.1109\/ICMA.2013.6617961"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Shkurti, F., Xu, A., Meghjani, M., Higuera, J.C.G., Girdhar, Y., Giguere, P., Dey, B.B., Li, J., Kalmbach, A., and Prahacs, C. (2012, January 7\u201312). Multi-domain monitoring of marine environments using a heterogeneous robot team. Proceedings of the 2012 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Vilamoura-Algarve, Portugal.","DOI":"10.1109\/IROS.2012.6385685"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zhou, M., Bachmayer, R., and De Young, B. (2017, January 24\u201328). Underwater acoustic-based navigation towards multi-vehicle operation and adaptive oceanographic sampling. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8206508"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1002\/rob.21435","article-title":"Marine heterogeneous multirobot systems at the great Eastern Japan Tsunami recovery","volume":"29","author":"Murphy","year":"2012","journal-title":"J. Field Robot."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1109\/70.781966","article-title":"Motion planning in R3 for multiple tethered robots","volume":"15","author":"Hert","year":"1999","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.oceaneng.2015.10.007","article-title":"A survey on path planning for persistent autonomy of autonomous underwater vehicles","volume":"110","author":"Zeng","year":"2015","journal-title":"Ocean Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1007\/s11431-017-9198-6","article-title":"Obstacle-avoiding path planning for multiple autonomous underwater vehicles with simultaneous arrival","volume":"62","author":"Yao","year":"2019","journal-title":"Sci. China Technol. Sci."},{"key":"ref_10","unstructured":"Panda, M., Das, B., and Pati, B.B. (2020). Innovation in Electrical Power Engineering, Communication, and Computing Technology, Springer."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"8902","DOI":"10.1109\/JSEN.2018.2866837","article-title":"Data-Gathering Protocol-Based AUV Path-Planning for Long-Duration Cooperation in Underwater Acoustic Sensor Networks","volume":"18","author":"Nam","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.isatra.2019.04.012","article-title":"Cooperative path planning of multiple autonomous underwater vehicles operating in dynamic ocean environment","volume":"94","author":"Zhuang","year":"2019","journal-title":"ISA Trans."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"McCammon, S., and Hollinger, G.A. (June, January 29). Planning and executing optimal non-entangling paths for tethered underwater vehicles. Proceedings of the 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore.","DOI":"10.1109\/ICRA.2017.7989349"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Cao, M., Cao, K., Yuan, S., Nguyen, T.M., and Xie, L. (2023). NEPTUNE: Non-Entangling Planning for Multiple Tethered Unmanned Vehicles. IEEE Trans. Robot., 1\u201319.","DOI":"10.1109\/TRO.2023.3264950"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s10514-021-09972-x","article-title":"Motion planning for a pair of tethered robots","volume":"45","author":"Teshnizi","year":"2021","journal-title":"Auton. Robot."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.robot.2019.05.008","article-title":"Planning coordinated motions for tethered planar mobile robots","volume":"118","author":"Zhang","year":"2019","journal-title":"Robot. Auton. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4064","DOI":"10.1109\/LRA.2021.3067286","article-title":"A Heuristic for Efficient Coordination of Multiple Heterogeneous Mobile Robots Considering Workload Balance","volume":"6","author":"Bae","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Patil, A., Bae, J., and Park, M. (2022). An Algorithm for Task Allocation and Planning for a Heterogeneous Multi-Robot System to Minimize the Last Task Completion Time. Sensors, 22.","DOI":"10.3390\/s22155637"}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/3\/85\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:53:49Z","timestamp":1760126029000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/3\/85"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,13]]},"references-count":18,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["robotics12030085"],"URL":"https:\/\/doi.org\/10.3390\/robotics12030085","relation":{},"ISSN":["2218-6581"],"issn-type":[{"type":"electronic","value":"2218-6581"}],"subject":[],"published":{"date-parts":[[2023,6,13]]}}}