PREDICTION OF RECEIVED SIGNAL STRENGTH USING THE FUZZY LOGIC CONTROLLER FOR LOCALISATION OF SENSORS IN MOBILE ROBOTS, 302-311.

Sneha Suresh Kumaran, Samson Jerold Samuel Chelladurai, K.B. Badri Narayanan, and T.A. Selvan

References

  1. [1] P.K. Panigrahi and S.K. Bisoy, Localization strategies forautonomous mobile robots: a review, Journal King SaudUniversity - Computer Information Sciences, 34, 2022,6019–6039.
  2. [2] Z. Xiao and Y. Zeng, An overview on integrated localizationand communication towards 6G, Science China InformationSciences, 65, 2021, 131301.
  3. [3] Z. Zhou, L. Li, A. F¨ursterling, H.J. Durocher, J. Mouridsen,and X. Zhang, Learning-based object detection and localizationfor a mobile robot manipulator in SME production, Roboticsand Computer-Integrated Manufacturing, 73, 2022, 102229.
  4. [4] A. Albanese, V. Sciancalepore, A. Banchs, and X. Costa-P´erez,LOKO: Localization-aware roll-out planning for future mobilenetworks, IEEE Transactions on Mobile Computing, 22, 2022,5359–5374. https://doi.org/10.1109/TMC.2022.3168076.
  5. [5] T. Yabe, N.K.W. Jones, P.S.C. Rao, M.C. Gonzalez, and S.V.Ukkusuri, Mobile phone location data for disasters: a reviewfrom natural hazards and epidemics, Computers, Environmentand Urban Systems, 94, 2022, 101777.
  6. [6] K.L. Keung, Y.Y. Chan, K.K.H. Ng, S.L. Mak, C.H. Li, Y. Qin,and C.W. Yu, Edge intelligence and agnostic robotic paradigmin resource synchronisation and sharing in flexible robotic andfacility control system, Advanced Engineering Informatics, 52,2022, 101530.
  7. [7] G. Deak, K. Curran, and J. Condell, A survey ofactive and passive indoor localisation systems, ComputerCommunications, 35, 2012, 1939–1954.
  8. [8] S. ˇCapkun, M. Hamdi, and J.-P. Hubaux, GPS-free positioningin mobile ad hoc networks, Cluster Computing, 5, 2002,157–167.
  9. [9] N. Bulusu, J. Heidemann, and D. Estrin, GPS-less low-costoutdoor localization for very small devices, IEEE PersonalCommunication, 7, 2000, 28–34.
  10. [10] H. Obeidat, W. Shuaieb, O. Obeidat, and R. Abd-Alhameed,A review of indoor localization techniques and wireless tech-nologies, 119, 2021, 289–327. https://doi.org/10.1007/s11277-021-08209-5.
  11. [11] H. Zhang, Y. Xia, K. Liu, F. Jin, C. Chen, andY. Liao, A Kalman filter based indoor tracking systemvia joint Wi-Fi/PDR localization, Proc. IEEE Smart-World, Ubiquitous Intelligence & Computing, Advanced &Trusted Computing, Scalable Computing & Communications,Cloud & Big Data Computing, Internet of People andSmart City Innovation, Guangzhou, China, 2018, 1444–1449,https://doi.org/10.1109/SmartWorld.2018.00250.
  12. [12] P. Bahl and V.N. Padmanabhan, RADAR: An in-buildingRF-based user location and tracking system, Proc. IEEEINFOCOM 2000. Conference on Computer Communications.Nineteenth Annual Joint Conference of the IEEE Computerand Communications Societies IEEE, Tel Aviv, Israel, 2000,775–784, https://doi.org/10.1109/INFCOM.2000.832252.
  13. [13] Y. Yang, B. Huang, Z. Xu, and R. Yang, A fuzzy logic-based energy-adaptive localization scheme by fusing WiFi and309PDR, Wireless Communications and Mobile Computing, 2023,9052477, https://doi.org/10.1155/2023/9052477.
  14. [14] X. Ou, M. Wu, Y. Pu, B. Tu, G. Zhang, and Z. Xu, Cuckoosearch algorithm with fuzzy logic and Gauss–Cauchy forminimizing localization error of WSN, Applied Soft Computing,125, 2022, 109211.
  15. [15] P. Singh, N. Mittal, and R. Salgotra, Comparison of range-based versus range-free WSNs localization using adaptive SSAalgorithm, Wireless Networks, 28, 2022, 1625–1647.
  16. [16] D.K. Mishra, A. Thomas, J. Kuruvilla, P. Kalyanasundaram,K.R. Prasad, and A. Haldorai, Design of mobile robot naviga-tion controller using neuro-fuzzy logic system, Computers andElectrical Engineering, 101, 2022, 108044.
  17. [17] J. Chadha and A. Jain, Fuzzy logic-based range-free localizationin WSN, Proc. Machine Learning, Advances in Computing,Renewable Energy and Communication, Singapore, 2022,89–97, https://doi.org/10.1007/978-981-16-2354-7 9.
  18. [18] B. Karaduman, B.T. Tezel, and M. Challenger, Deploymentof software agents and application of fuzzy controller on theUWB localization based mobile robots, Proc. InternationalConference on Intelligent and Fuzzy Systems, Cham, 2022,98–105, https://doi.org/10.1007/978-3-031-09173-5 13.
  19. [19] E. Rahayu, A. Rusdinar, B. Rahmat, and C. Setianingsih,Inverted global sensor for automated guided vehicle localizationand navigation, Proc. 4th International Conf. on SmartSensors Application, Kuala Lumpur, Malaysia, 2022, 5–10,https://doi.org/10.1109/ICSSA54161.2022.9870958.
  20. [20] P. Singh, N. Mittal, and P. Singh, A novel hybrid range-freeapproach to locate sensor nodes in 3D WSN using GWO-FAalgorithm, Telecommunication Systems, 80, 2022, 303–323.
  21. [21] B. Bhushan and G. Sahoo, FLEAC: Fuzzy logic-based energyadequate clustering protocol for wireless sensor networksusing improved grasshopper optimization algorithm, WirelessPersonal Communications, 124, 2022, 573–606.
  22. [22] M. Vargheese, S. Vanithamani, D.S. David, and G.R.K. Rao,Design of fuzzy logic control framework for QoS routing inMANET, Intelligent Automation and Soft Computing, 35,2023, 3479–3499.
  23. [23] R. Ranjita and S. Acharya, A fuzzy logic-based congestiondetection technique for vehicular ad hoc networks, Proc.Advances in Distributed Computing and Machine Learning,Singapore, 2022, 167–177, https://doi.org/10.1007/978-981-19-1018-0 15.
  24. [24] B. Fahima and N. Abdelkrim, Multispectral visual odometryusing SVSF for mobile robot localization, Unmanned Systems,10, 2022, 273–288.
  25. [25] O. Bamasaq, D. Alghazzawi, S. Bhatia, P. Dadheech, F. Arslan,S. Sengan, and S.H. Hassan, Distance matrix and Markov chainbased sensor localization in WSN, Computers, Materials andContinua, 71, 2022, 4051–4068.
  26. [26] Himanshu, R. Khanna, and A. Kumar, Knowledge acquisitionfor 3D coordinates of target in wireless sensor networksfor smart city application, Expert Systems, 39, 2022,https://doi.org/10.1111/exsy.12910.
  27. [27] B. Narayanan and M. Sreekumar, Design, modelling, optimi-sation and validation of condition-based maintenance in IoTenabled hybrid flow shop, International Journal of ComputerIntegrated Manufacturing, 35, 2022,927–941.
  28. [28] K.B. Badri Narayanan and M. Sreekumar, Diagnosing of riskstate in subsystems of CNC turning center using intervaltype-2 fuzzy logic system with semi elliptic membershipfunctions, International Journal of Fuzzy Systems, 24, 2022,823–840.
  29. [29] K.B.B. Narayanan and S. Muthusamy, Prediction of machin-ability parameters in turning operation using interval type-2 fuzzy logic system based on semi-elliptic and trapezoidalmembership functions, Soft Computing, 26, 2022, 3197–3216.
  30. [30] Y. Zhuang, K. Wang, W. Wang, and H. Hu, A hybrid sensingapproach to mobile robot localization in complex indoor envi-ronments, International Journal of Robotics and Automation,27, 2012, https://doi.org/10.2316/Journal.206.2012.2.206-3498.
  31. [31] J. Savage, E. Marquez, and F. Lepe-Casillas, Hidden Markovmodels and vector quantization for mobile robot localization,Robotics and Applications, 2005.
  32. [32] A. Kraeussling, A novel approach to the mobile robot local-ization problem using tracking methods, Proc. 13th IASTEDInternational Conference on Robotics and Applications (RA2007), W¨urzburg, 2007, 107–112.
  33. [33] W.Z.C. Guo, K. Huang, Y. Luo, and H. Zhang, Object-orientedsemantic mapping and dynamic optimization on a mobile robot,International Journal of Robotics and Automation, 37, 2022,321–331.
  34. [34] A. Bayram and A.S. Duru, Design and control of arehabilitation robot manipulator for head–neck orthopaedicdisorders, International Journal of Robotics and Automation,37, 2022, 486–497.
  35. [35] Y. D.Q. Zou, C. Ming, and L. Dong, Brain-inspired cognitivemap building for mobile robot, International Journal ofRobotics and Automation, 37, 2022, 88–96.
  36. [36] H.J.M. Tapas, K. Maiti, D. Sunandan, O. Yoshihiro, and M.M.-Mattausch, Electro-mechanical model and its application tobiped-robot stability with force sensors, International Journalof Robotics and Automation, 37, 2022, 332–345.
  37. [37] H. Kang, J. Yun, S. Kim, and J. Lee, Mobile robot localizationby EKF and indoor GPS based on eliminated maximumerror anchor, Proc. Robotics, Calgary, AB, Canada, 2010,https://doi.org/10.2316/P.2010.703-054.
  38. [38] Y. Lu, V. Polotski, and J. Sasiadek, Outdoor mobile robotlocalization with 2-D laser range sensor, Proc. Tenth IASTEDInternational Conference, Beijing , 2007, 622–803.
  39. [39] Y. Li, W. Liu, L. Li, and X. Lei, Charging trajectory planningand motion control for indoor mobile robots, InternationalJournal of Robotics and Automation, 37, 2022, 520–528.
  40. [40] T.D. Dung and G. Capi, Application of neural networks forrobot 3D mapping and annotation using depth image camera,International Journal of Robotics and Automation, 37, 2022,529–536.
  41. [41] X. Wang, Z. Xia, X. Zhou, J. Wei, X. Gu, and H. Yan, Collision-free path planning for arc welding robot based on IDA-DEalgorithm, International Journal of Robotics and Automation,37, 2022, 476–485.
  42. [42] J. V. Marti, J. Sales, R. Marin, and E. Jimenez-Ruiz,Localization of mobile sensors and actuators for intervention inlow-visibility conditions: The ZigBee fingerprinting approach,International Journal of Distributed Sensor Networks, 2012,(2012), 951213. https://doi.org/10.1155/2012/951213.
  43. [43] P.K. Muhuri and A.K. Shukla, Semi-elliptic membership func-tion: Representation, generation, operations, defuzzification,ranking and its application to the real-time task schedulingproblem, Engineering Applications of Artificial Intelligence,60, 2017, 71–82.
  44. [44] L. Jouffe, Fuzzy inference system learning by reinforcementmethods, IEEE Transactions on Systems, Man, and Cybernet-ics, Part C (Applications and Reviews), 28, 1998, 338–355.

Important Links:

Go Back