Page 47 - Read Online
P. 47

Sellers et al. Intell Robot 2022;2(4):333­54  I http://dx.doi.org/10.20517/ir.2022.21  Page 353


                  DOI
               15. Jan GE, Luo C, Lin HT, Fung K. Complete area coverage path­planning with arbitrary shape obstacles. J Autom Contr Eng 2019;7.
                  Available from:  https://d1wqtxts1xzle7.cloudfront.net/79144324/20191218032728291­with­cover­page­v2.pdf?Expires=166193823
                  6&Signature=F9H9SowZfI7P9v74Xs1quZpkYuja0eBkKJxIC­­LkgBppman~V~hvtZqk1Z­ChAOsmQM1p2471dlhAmBjm8EsjnfvOq
                  vVrjjfLCVHUK­opgkdCHuQgdFors7oKBCBkgHI0tg9tVHAND8hqgv0izfLx3YKuQeNidjvTlfXT66CbSDDtsfuZUe6wTnKYrVIq993
                  iBCwGpQmWZ8nhQGPYqiw­fC06aBPWusmC9jCpidVZpb6R0IvlZ~ii7gnj1~rdOG6AgaIqUlSEPR7csU~9­oPDnZ2FZbXqcvlcuge75
                  e4JhqmG3sMdzLIfOSJofxK­3Ff1NLakRVxpWYA20EbJTviA__&Key­Pair­Id=APKAJLOHF5GGSLRBV4ZA [Last accessed on 31
                  Aug 2022].
               16. Lei T, Sellers T, Rahimi S, Cheng S, Luo C. A nature­inspired algorithm to adaptively safe navigation of a Covid­19 disinfection robot.
                  In: International Conference on Intelligent Robotics and Applications. Cham: Springer; 2021. pp. 123–34. DOI
               17. Lei T, Luo C, Sellers T, Wang Y, Liu L. Multi­task allocation framework with spatial dislocation collision avoidance for multiple aerial
                  robots. IEEE Trans Aerosp Electron Syst 2022. DOI
               18. Chen Y, Liu C, Shi BE, Liu M. Robot navigation in crowds by graph convolutional networks with attention learned from human gaze.
                  IEEE Rob Autom Lett 2020;5:2754–61. DOI
               19. Chen J, Luo C, Krishnan M, Paulik M, Tang Y. An enhanced dynamic Delaunay triangulation­based path planning algorithm for au­
                  tonomous mobile robot navigation. In: Intelligent Robots and Computer Vision XXVII: Algorithms and Techniques. vol. 7539. California,
                  USA: SPIE; 2010. pp. 253–64. DOI
               20. Luo C, Xiao Y, Yang SX, Jan GE. Improving vehicle navigation by a heading­enabled ACO approach. In: World Automation Congress.
                  Rio Grande, USA: IEEE; 2016. pp. 1–6. DOI
               21. Lei T, Luo C, Jan GE, Fung K. Variable speed robot navigation by an ACO approach. In: International Conference on Swarm Intelligence.
                  Cham: Springer; 2019. pp. 232–42. DOI
               22. Wang L, Luo C, Li M, Cai J. Trajectory planning of an autonomous mobile robot by evolving ant colony system. Int J Rob Autom
                  2017;32:406–13. DOI
               23. Lei T, Luo C, Sellers T, Rahimi S. A bat­pigeon algorithm to crack detection­enabled autonomous vehicle navigation and mapping. Intell
                  Syst Appl 2021;12:200053. DOI
               24. Luo C, Yang SX, Krishnan M, Paulik M. An effective vector­driven biologically­motivated neural network algorithm to real­time au­
                  tonomous robot navigation. In: IEEE International Conference on Robotics and Automation. Hong Kong, China; 2014. pp. 4094–99.
                  DOI
               25. Na YK, Oh SY. Hybrid control for autonomous mobile robot navigation using neural network based behavior modules and environment
                  classification. Auton 2003;15:193–206. DOI
               26. Zhong C, Luo C, Chu Z, Gan W. A continuous hopfield neural network based on dynamic step for the traveling salesman problem. In:
                  International Joint Conference on Neural Network. Anchorage, USA: IEEE; 2017. pp. 3318–23. DOI
               27. Lazreg M, Benamrane N.  Hybrid system for optimizing the robot mobile navigation using ANFIS and PSO.  Rob Auton Syst
                  2022;153:104114. DOI
               28. Jensen­Nau KR, Hermans T, Leang KK. Near­optimal area­coverage path planning of energy­constrained aerial robots with application
                  in autonomous environmental monitoring. IEEE Trans Autom Sci Eng 2021;18:1453–68. DOI
               29. Janoš J, Vonásek V, Pěnička R. Multi­goal path planning using multiple random trees. IEEE Rob Autom Lett 2021;6:4201–8. DOI
               30. Ortiz S, Yu W. Autonomous navigation in unknown environment using sliding mode SLAM and genetic algorithm. Intell Robot ;1:131–50.
                  DOI
               31. Bernardo R, Sousa J, Gonçalves PJ. Planning robotic agent actions using semantic knowledge for a home environment. Intell Robot
                  2021;1:101–15. DOI
               32. Luo C, Yang SX. A bioinspired neural network for real­time concurrent map building and complete coverage robot navigation in unknown
                  environments. IEEE Trans Neural Netw 2008;19:1279–98. DOI
               33. Shair S, Chandler JH, GonzÁlez­Villela VJ, Parkin RM, Jackson MR. The use of aerial images and GPS for mobile robot waypoint
                  navigation. IEEE/ASME Trans Mechatron 2008;13:692–99. DOI
               34. Yang Y, Khalife J, Morales JJ, Kassas ZM. UAV waypoint opportunistic navigation in GNSS­denied environments. IEEE Trans Aerosp
                  Electron Syst 2022;58:663–78. DOI
               35. Teng F, Zhang H, Luo C, Shan Q. Delay tolerant containment control for second­order multi­agent systems based on communication
                  topology design. Neurocomputing 2020;380:11–19. DOI
               36. Lee DT, Drysdale RL III. Generalization of Voronoi diagrams in the plane. SIAM J Comput 1981;10:73–87. DOI
               37. Takahashi O, Schilling RJ. Motion planning in a plane using generalized Voronoi diagrams. IEEE Trans Robot 1989;5:143–50. DOI
               38. Lei T, Luo C, Ball JE, Rahimi S. A graph­based ant­like approach to optimal path planning. In: IEEE Congress on Evolutionary
                  Computation. Glasgow, UK; 2020. pp. 1–6. DOI
               39. Li X, Li X, Khyam MO, Luo C, Tan Y. Visual navigation method for indoor mobile robot based on extended BoW model. CAAI Trans
                  Intell Tech 2017;2:142–47. Available from: https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/trit.2017.0020 [Last accessed on
                  31 Aug 2022].
               40. Yang Y, Deng Q, Shen F, Zhao J, Luo C. A shapelet learning method for time series classification. In: IEEE International Conference on
                  Tools with Artificial Intelligence. San Jose, USA; 2016. pp. 423–30. DOI
               41. Liu L, Luo C, Shen F. Multi­agent formation control with target tracking and navigation. In: IEEE International Conference on Information
                  and Automation. Macao, China; 2017. pp. 98–103. DOI
   42   43   44   45   46   47   48   49   50   51   52