{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:46:11Z","timestamp":1761597971306,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,3]],"date-time":"2018-08-03T00:00:00Z","timestamp":1533254400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Development and Reform Commission of Shenzhen Maunicipality","award":["JCYJ20170413110656460"],"award-info":[{"award-number":["JCYJ20170413110656460"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Efficient distributed processing is vital for collaborative searching tasks of robotic swarm systems. Typically, those systems are decentralized, and the members have only limited communication and processing capacities. What is illustrated in this paper is a distributed processing paradigm for robotic swarms moving in a line or v-shape formation. The introduced concept is capable of exploits the line and v-shape formations for 2-D filtering and processing algorithms based on a modified multi-dimensional Roesser model. The communication is only between nearest adjacent members with a simple state variable. As an example, we applied a salient region detection algorithm to the proposed framework. The simulation results indicate the designed paradigm can detect salient regions by using a moving line or v-shape formation in a scanning way. The requirement of communication and processing capability in this framework is minimal, making it a good candidate for collaborative exploration of formatted robotic swarms.<\/jats:p>","DOI":"10.3390\/s18082543","type":"journal-article","created":{"date-parts":[[2018,8,3]],"date-time":"2018-08-03T11:03:26Z","timestamp":1533294206000},"page":"2543","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Line and V-Shape Formation Based Distributed Processing for Robotic Swarms"],"prefix":"10.3390","volume":"18","author":[{"given":"Jian","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Mechanical and Automation Engineering, Harbin Institute of Technology Shenzhen, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Automation Engineering, Harbin Institute of Technology Shenzhen, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Bauer","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of Notre Dame, Notre Dame, IN 46656, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5117","DOI":"10.1016\/j.eswa.2015.02.040","article-title":"Line formation algorithm in a swarm of reactive robots constrained by underwater environment","volume":"42","author":"Sousselier","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1007\/s11721-011-0053-0","article-title":"Self-organized cooperation between robotic swarms","volume":"5","author":"Ducatelle","year":"2011","journal-title":"Swarm Intell."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.neucom.2015.05.116","article-title":"A review of swarm robotics tasks","volume":"172","year":"2016","journal-title":"Neurocomputing"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4137","DOI":"10.3390\/s110404137","article-title":"Bioinspired principles for large-scale networked sensor systems: An overview","volume":"11","author":"Zhang","year":"2011","journal-title":"Sensors"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"15262","DOI":"10.3390\/s140815262","article-title":"Particle swarm inspired underwater sensor self-deployment","volume":"14","author":"Du","year":"2014","journal-title":"Sensors"},{"key":"ref_6","first-page":"86","article-title":"Ultra-Low Complexity Control Mechanisms for Sensor Networks and Robotic Swarms","volume":"3","author":"Scheutz","year":"2013","journal-title":"Int. J. New Comput. Archit. Appl."},{"key":"ref_7","unstructured":"Thenius, R., Moser, D., Varughese, J.C., Kernbach, S., Kuksin, I., Kernbach, O., Kuksina, E., Mi\u0161kovi\u0107, N., Bogdan, S., and Petrovi\u0107, T. (2016). subCULTron-Cultural Development as a Tool in Underwater Robotics. Artificial Life and Intelligent Agents Symposium, Springer."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Parker, L.E., Rus, D., and Sukhatme, G.S. (2016). Multiple Mobile Robot Systems. Springer Handbook of Robotics, Springer.","DOI":"10.1007\/978-3-319-32552-1_53"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Trianni, V., and Campo, A. (2015). Fundamental collective behaviors in swarm robotics. Springer Handbook of Computational Intelligence, Springer.","DOI":"10.1007\/978-3-662-43505-2_71"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kennedy, J. (2011). Particle swarm optimization. Encyclopedia of Machine Learning, Springer.","DOI":"10.1007\/978-0-387-30164-8_630"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1016\/j.pnsc.2008.03.029","article-title":"Particle swarm optimization with a leader and followers","volume":"18","author":"Wang","year":"2008","journal-title":"Progress Nat. Sci."},{"key":"ref_12","unstructured":"Burgard, W., Moors, M., Fox, D., Simmons, R., and Thrun, S. (2000, January 24\u201328). Collaborative multi-robot exploration. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2000), San Francisco, CA, USA."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Alur, R., Das, A., Esposito, J., Fierro, R., Grudic, G., Hur, Y., Kumar, V., Lee, I., Ostrowski, J., and Pappas, G. (2001). A framework and architecture for multirobot coordination. Experimental Robotics VII, Springer.","DOI":"10.1007\/3-540-45118-8_31"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"04014047","DOI":"10.1061\/(ASCE)AS.1943-5525.0000351","article-title":"UAV formation control via the virtual structure approach","volume":"28","author":"Askari","year":"2013","journal-title":"J. Aerosp. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bayindir, L., and Sahin, E. (April, January 30). Modeling self-organized aggregation in swarm robotic systems. Proceedings of the 2009 IEEE Swarm Intelligence Symposium, Nashville, TN, USA.","DOI":"10.1109\/SIS.2009.4937849"},{"key":"ref_16","unstructured":"Balch, T., and Hybinette, M. (2000, January 24\u201328). Social potentials for scalable multi-robot formations. Proceedings of the IEEE International Conference on Robotics & Automation, San Francisco, CA, USA."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1109\/TAC.2005.846556","article-title":"Consensus seeking in multiagent systems under dynamically changing interaction topologies","volume":"50","author":"Ren","year":"2005","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.robot.2016.12.006","article-title":"Bio-inspired self-organising multi-robot pattern formation: A review","volume":"91","author":"Oh","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1162\/artl.2008.14.2.179","article-title":"V-like formations in flocks of artificial birds","volume":"14","author":"Nathan","year":"2008","journal-title":"Artif. Life"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Li, X., Tan, Y., Fu, J., and Mareels, I. (2017, January 3\u20136). On V-shaped flight formation of bird flocks with visual communication constraints. Proceedings of the 13th IEEE International Conference on Control & Automation (ICCA), Ohrid, Macedonia.","DOI":"10.1109\/ICCA.2017.8003113"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yang, J., Wang, X., and Bauer, P. (2016, January 13\u201315). Formation forming based low-complexity swarms with distributed processing for decision making and resource allocation. Proceedings of the 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand.","DOI":"10.1109\/ICARCV.2016.7838561"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s11045-010-0143-y","article-title":"Realization using the Roesser model for implementations in distributed grid sensor networks","volume":"22","author":"Sumanasena","year":"2011","journal-title":"Multidimens. Syst. Signal Process."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TAC.1975.1100844","article-title":"A discrete state-space model for linear image processing","volume":"20","author":"Roesser","year":"1975","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1038\/35058500","article-title":"Computational modelling of visual attention","volume":"2","author":"Itti","year":"2001","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1007\/s11045-015-0341-8","article-title":"Multidimensional control systems: Case studies in design and evaluation","volume":"26","author":"Rogers","year":"2015","journal-title":"Multidimens. Syst. Signal Process."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Xu, Y., Ou, J., He, H., Zhang, X., and Mills, J. (2016). Mosaicking of unmanned aerial vehicle imagery in the absence of camera poses. Remote Sens., 8.","DOI":"10.3390\/rs8030204"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/s11045-012-0221-4","article-title":"A multidimensional wave digital filter bank for video-based motion analysis","volume":"25","author":"Schwerdtfeger","year":"2014","journal-title":"Multidimens. Syst. Signal Process."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/8\/2543\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:16:25Z","timestamp":1760195785000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/8\/2543"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,3]]},"references-count":27,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["s18082543"],"URL":"https:\/\/doi.org\/10.3390\/s18082543","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2018,8,3]]}}}