{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:50:02Z","timestamp":1754157002705,"version":"3.41.2"},"reference-count":13,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2010,6,15]],"date-time":"2010-06-15T00:00:00Z","timestamp":1276560000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,6,15]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to improve the D* algorithm which has been used usually in robotics for mobile robot navigation in unknown or dynamic environments.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>First, the model of 2D workspace with some obstacles is expressed in regularity grids. The optimal path is planned by using the improved D* algorithm by searching in the neighbor grid cells in 16 directions. It makes the robot that the smallest turning angle drops to \u03c0\/8. The robot moving angle discrete precision is raised and the unnecessary cost of path planning is reduced so the robot motion path is smoother. Then, the improved D* algorithm is simulated in MOBOTSIM software environment and is tested by the WiRobotX80 mobile robot.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>To search in the neighbor grid cells in 16 directions instead of eight directions by using D* algorithms for path planning.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>The map should be expressed in regularity grids.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The improved D* algorithm is effective and it can result in a higher quality path than the conventional D* algorithm at the same map environment.<\/jats:p><\/jats:sec>","DOI":"10.1108\/03684921011046708","type":"journal-article","created":{"date-parts":[[2010,7,11]],"date-time":"2010-07-11T19:57:21Z","timestamp":1278878241000},"page":"935-945","source":"Crossref","is-referenced-by-count":5,"title":["A study of improvement of D* algorithms for mobile robot path planning in partial unknown environments"],"prefix":"10.1108","volume":"39","author":[{"given":"Jianming","family":"Guo","sequence":"first","affiliation":[]},{"given":"Liang","family":"Liu","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2022032020344272500_b3","unstructured":"Dai, B., Xiao, X.\u2010M. and Cai, Z.\u2010X. (2005), \u201cCurrent status and future development of mobile robot path planning technology\u201d, Control Engineering of China, Vol. 12 No. 3, pp. 198\u2010202."},{"key":"key2022032020344272500_b7","doi-asserted-by":"crossref","unstructured":"Ferguson, D. and Stentz, A. (2006), \u201cUsing interpolation to improve path planning: the field D* algorithm\u201d, Journal of Field Robotics, Vol. 23 No. 2, pp. 79\u2010101.","DOI":"10.1002\/rob.20109"},{"key":"key2022032020344272500_b5","doi-asserted-by":"crossref","unstructured":"Koenig, S. and Likhachev, M. (2005), \u201cFast replanning for navigation in unknown terrain\u201d, IEEE Transactions on Robotics and Automation, Vol. 21 No. 3, pp. 354\u201063.","DOI":"10.1109\/TRO.2004.838026"},{"key":"key2022032020344272500_b13","doi-asserted-by":"crossref","unstructured":"Liu, K.D., Lin, Y. and Gao, L.G. (2002), \u201cUnascertained rationals and subjective uncertain information\u201d, Systems Analysis Modelling Simulation, Vol. 42, pp. 343\u201058.","DOI":"10.1080\/02329290290031053"},{"key":"key2022032020344272500_b11","doi-asserted-by":"crossref","unstructured":"OuYang, S.C., Lin, Y., Wang, Z. and Peng, T.Y. (2001), \u201cBlown\u2010up theory of evolution science and fundamental problems of the first push\u201d, Kybernetes: The International Journal of Systems & Cybernetics, Vol. 30 No. 4, pp. 448\u201062.","DOI":"10.1108\/03684920110386955"},{"key":"key2022032020344272500_b12","doi-asserted-by":"crossref","unstructured":"OuYang, S.C., Peng, T.Y., Xiao, T.G., Lin, Y. and Miao, J.H. (2000), \u201cInfrastructural analysis and restriction in evolution of weather systems\u201d, Kybernetes: The International Journal of Systems & Cybernetics, Vol. 29, pp. 184\u2010200.","DOI":"10.1108\/03684920010312731"},{"key":"key2022032020344272500_b1","doi-asserted-by":"crossref","unstructured":"Stents, A. (1994), \u201cOptimal and efficient path planning for partially\u2010known environments\u201d, Proceedings of the IEEE International Conference on Robotics and Automation, May, pp. 3310\u20107.","DOI":"10.1109\/ROBOT.1994.351061"},{"key":"key2022032020344272500_b2","unstructured":"Stents, A. (1995), \u201cThe focussed D* algorithm for real\u2010time replanning\u201d, Proceedings of the International Joint Conference on Artificial Intelligence, August, pp. 1625\u201059."},{"key":"key2022032020344272500_b6","doi-asserted-by":"crossref","unstructured":"Zelinsky, A. (1992), \u201cA mobile robot exploration algorithm\u201d, IEEE Transactions on Robotics and Automation, Vol. 8 No. 2, pp. 707\u201017.","DOI":"10.1109\/70.182671"},{"key":"key2022032020344272500_b4","unstructured":"Zhang, Y. and Wu, C.\u2010D. (2002), \u201cRobot motion planning based on genetic algorithms\u201d, Journal of Shenyang Arch. and Civ. Eng. Univ., Vol. 18 No. 4, pp. 302\u20105."},{"key":"key2022032020344272500_frd1","unstructured":"Hu, Z., Zhang, Y. and Chen, L. (2006), \u201cStudy on the integrated modeling of the entire rider\u2010vehicle\u2010road system\u201d, Advances in Systems Science and Applications, Vol. 6 No. 2, pp. 224\u201033."},{"key":"key2022032020344272500_frd2","unstructured":"Wang, W. and Wang, B. (2006), \u201cResearch on virtual common information platform for intelligent transportation system based on grid model\u201d, Advances in Systems Science and Applications, Vol. 6 No. 2, pp. 304\u201011."},{"key":"key2022032020344272500_frd3","unstructured":"Xiao, N. (2005), \u201cLearning\u2010based robot force servoing control\u201d, Advances in Systems Science and Applications, Vol. 5 No. 1, pp. 41\u20105."}],"container-title":["Kybernetes"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/03684921011046708","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/03684921011046708\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/03684921011046708\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T23:26:59Z","timestamp":1753399619000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/k\/article\/39\/6\/935-945\/271057"}},"subtitle":[],"editor":[{"given":"Hejing","family":"Xiong","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2010,6,15]]},"references-count":13,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2010,6,15]]}},"alternative-id":["10.1108\/03684921011046708"],"URL":"https:\/\/doi.org\/10.1108\/03684921011046708","relation":{},"ISSN":["0368-492X"],"issn-type":[{"type":"print","value":"0368-492X"}],"subject":[],"published":{"date-parts":[[2010,6,15]]}}}