{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T02:32:12Z","timestamp":1769308332782,"version":"3.49.0"},"reference-count":24,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T00:00:00Z","timestamp":1629158400000},"content-version":"vor","delay-in-days":228,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hunan Provincial Philosophy and Social Science Project","award":["18YBA208"],"award-info":[{"award-number":["18YBA208"]}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Wireless Communications and Mobile Computing"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>With the continuous emergence and innovation of computer technology, mobile robots are a relatively hot topic in the field of artificial intelligence. It is an important research area of more and more scholars. The core of mobile robots is to be able to realize real\u2010time perception of the surrounding environment and self\u2010positioning and to conduct self\u2010navigation through this information. It is the key to the robot\u2019s autonomous movement and has strategic research significance. Among them, the goal recognition ability of the soccer robot vision system is the basis of robot path planning, motion control, and collaborative task completion. The main recognition task in the vision system is the omnidirectional vision system. Therefore, how to improve the accuracy of target recognition and the light adaptive ability of the robot omnidirectional vision system is the key issue of this paper. Completed the system construction and program debugging of the omnidirectional mobile robot platform, and tested its omnidirectional mobile function, positioning and map construction capabilities in the corridor and indoor environment, global navigation function in the indoor environment, and local obstacle avoidance function. How to use the local visual information of the robot more perfectly to obtain more available information, so that the \u201ceyes\u201d of the robot can be greatly improved by relying on image recognition technology, so that the robot can obtain more accurate environmental information by itself has always been domestic and foreign one of the goals of the joint efforts of scholars. Research shows that the standard error of the experimental group\u2019s shooting and dribbling test scores before and the experimental group\u2019s shooting and dribbling test results after the standard error level is 0.004, which is less than 0.05, which proves the use of soccer\u2010assisted robot\u2010assisted training. On the one hand, we tested the positioning and navigation functions of the omnidirectional mobile robot, and on the other hand, we verified the feasibility of positioning and navigation algorithms and multisensor fusion algorithms.<\/jats:p>","DOI":"10.1155\/2021\/5532210","type":"journal-article","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T23:14:25Z","timestamp":1629242065000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Soccer\u2010Assisted Training Robot Based on Image Recognition Omnidirectional Movement"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2668-2479","authenticated-orcid":false,"given":"Bin","family":"Tan","sequence":"first","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,8,17]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12555-016-0544-2"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.2197\/ipsjjip.24.49"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1049\/iet-rsn.2018.5043"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-014-0918-5"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2745103"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-015-1750-1"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1142\/S1793351X16500045"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2399298"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.3233\/IDT-190022"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1080\/13682199.2018.1483481"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535302"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cja.2019.08.014"},{"key":"e_1_2_9_14_2","first-page":"1","article-title":"Control system of hexacopter using color histogram footprint and convolutional neural network","volume":"1862","author":"Ruliputra R. 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