DOI QR코드

DOI QR Code

Multi-objective path planning for mobile robot in nuclear accident environment based on improved ant colony optimization with modified A*

  • De Zhang (School of Resource Environment and Safety Engineering, University of South China) ;
  • Run Luo (School of Resource Environment and Safety Engineering, University of South China) ;
  • Ye-bo Yin (School of Computer Science, University of South China) ;
  • Shu-liang Zou (Hunan Provincial Key Laboratory of Emergency Safety Technology and Equipment for Nuclear Facilities )
  • 투고 : 2022.08.19
  • 심사 : 2023.02.03
  • 발행 : 2023.05.25

초록

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A* (IACO-A*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A* IACO-A* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

키워드

과제정보

This work was supported by the Scientific Research Foundation of Hunan Provincial Education Department of China (Grant No. 19B502) and the Basic Scientific research project of National Defense of China (Grant No. JCKY2019403D003) and the authors would like to thank the comments from the anonymous reviewers that improved the quality of the paper.

참고문헌

  1. K. Qian, A.G. Song, J.T. Bao, H.T. Zhang, Small teleoperated robot for nuclear radiation and chemical leak detection, Int. J. Adv. Rob. Syst. 9 (2012) 1-9.  https://doi.org/10.5772/7789
  2. S. Kawatsuma, R. Mimura, H. Asama, Unitization for portability of emergency response surveillance robot system: experiences and lessons learned from the deployment of the JAEA-3 emergency response robot at the Fukushima Daiichi NPPs, Robomech J 4 (2017) 1-7.  https://doi.org/10.1186/s40648-016-0070-2
  3. T. Kobayashi, K. Miyajima, S. Yanagihara, Development of remote surveillance squads for information collection on nuclear accidents, Adv. Robot. 16 (2002) 497-500.  https://doi.org/10.1163/156855302320535818
  4. R. Guzman, R. Navarro, J. Ferre, M. Moreno, RESCUER: development of a modular chemical, biological, radiological, and nuclear robot for intervention, sampling, and situation awareness, J. Field Robot. 33 (2016) 931-945.  https://doi.org/10.1002/rob.21588
  5. S. Kawatsuma, M. Fukushima, T. Okada, Emergency response by robots to Fukushima-Daiichi accident: summary and lessons learned, Ind. Robot 39 (2012) 428-435.  https://doi.org/10.1108/01439911211249715
  6. Y. Isozaki, K. Nakai, Development of a work robot with a manipulator and a transport robot for nuclear facility emergency preparedness, Adv. Robot. 16 (2002) 489-492.  https://doi.org/10.1163/156855302320535791
  7. H.F. Zhou, H. Zhang, M.W. Qiu, Radiation avoiding algorithm for nuclear robot path optimization, Ann. Nucl. Energy 169 (2022), 108948. 
  8. Z. Chen, H. Wu, Y. Chen, L. Cheng, B. Zhang, Patrol robot path planning in nuclear power plant using an interval multi-objective particle swarm optimization algorithm, Appl. Soft Comput. 116 (2022), 108192. 
  9. Y. Huang, X. Shi, Y. Zhou, Z. Xiong, Autonomous navigation of mobile robot in radiation environment with uneven terrain, Int. J. Intell. Robot. (2022), https://doi.org/10.1007/s41315-022-00255-x. 
  10. J.B. Wen, J.C. Yang, T.Y. Wang, Path planning for autonomous underwater vehicles under the influence of ocean currents based on a fusion heuristic algorithm, IEEE Trans. Veh. Technol. 70 (2021) 8529-8544.  https://doi.org/10.1109/TVT.2021.3097203
  11. N. Ghita, M. Kloetzer, Trajectory planning for a car-like robot by environment abstraction, Robot, Auto. Syst. 60 (2012) 609-619.  https://doi.org/10.1016/j.robot.2011.12.004
  12. W.Z. Chi, Z.Y. Ding, J.K. Wang, G.D. Chen, L.N. Sun, A generalized Voronoi diagram-based efficient heuristic path planning method for RRTs in mobile robots, IEEE Trans. Ind. Electron. 69 (2022) 4926-4937.  https://doi.org/10.1109/TIE.2021.3078390
  13. H.S. Min, Y.H. Lin, S.J. Wang, F. Wu, X. Shen, Path planning of mobile robot by mixing experience with modified artificial potential field method, Adv. Mech. Eng. 7 (2015) 1-17.  https://doi.org/10.1177/1687814015619276
  14. I.K. Ibraheem, F.H. Ajeil, Path planning of an autonomous mobile robot using swarm based optimization techniques, Al-Khawarizmi. Eng. J. 12 (2016) 12-25.  https://doi.org/10.22153/kej.2016.08.002
  15. M. Davoodi, F. Panahi, A. Mohades, S.N. Hashemi, Multi-objective path planning in discrete space, Appl. Soft Comput. 13 (2013) 709-720.  https://doi.org/10.1016/j.asoc.2012.07.023
  16. B. Song, Z. Wang, L. Zou, An improved PSO algorithm for smooth path planning of mobile robots using continuous high-degree Bezier curve, Appl. Soft Comput. 100 (2021) 1-11.  https://doi.org/10.1016/j.asoc.2020.106960
  17. J. Guo, Y. Gao, G. Cui, The path planning for mobile robot based on bat algorithm, Int. J. Autom. Control 9 (2015) 50-61.  https://doi.org/10.1504/IJAAC.2015.068041
  18. F. Hassan Ajeil, I. Ibraheem, A. Humaidi, Z.H. Khan, A novel path planning algorithm for mobile robot in dynamic environments using modified bat swarm optimization, J. Eng. 2021 (2021) 37-48.  https://doi.org/10.1049/tje2.12009
  19. F.H. Ajeil, I.K. Ibraheem, A.T. Azar, A.J. Humaidi, Grid-based mobile robot path planning using aging-based ant colony optimization algorithm in static and dynamic environments, Sensors 20 (2020) 1880. 
  20. C. Miao, G. Chen, C. Yan, Y. Wu, Path planning optimization of indoor mobile robot based on adaptive ant colony algorithm, Comput. Ind. Eng. 156 (2021), 107230. 
  21. F.H. Ajeil, I.K. Ibraheem, M.A. Sahib, A.J. Humaidi, Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm, Appl. Soft Comput. 89 (2020), 106076. 
  22. B.K. Oleiwi, H. Roth, B.I. Kazem, A hybrid approach based on ACO and Ga for multi objective mobile robot path planning, Appl. Mech. Mater. 527 (2014) 203-212.  https://doi.org/10.4028/www.scientific.net/AMM.527.203
  23. A.Q. Alzalloum, Application of Shortest Path Algorithms to Find Paths of Minimum Radiation Dose, 2009. 
  24. K. Chizhov, M.K. Sneve, S. Shinkarev, A. Tsovyanov, G.M. Smith, A. Krasnoschekov, I. Kemsky, V. Kryuchkov, Methods of minimising doses incurred by external exposure while moving in radiation hazardous areas, J. Radiol. Prot. 37 (2017) 697-714.  https://doi.org/10.1088/1361-6498/aa7c4f
  25. Q.Y. Pei, L.J. Hao, C.H. Chen, X.L. Zheng, T. He, Minimum collective dose based optimal evacuation path-planning method under nuclear accidents, Ann. Nucl. Energy 147 (2020), 107644. 
  26. Y.K. Liu, M.K. Li, C.L. Xie, M.J. Peng, S.Y. Wang, M. Chao, Z.K. Liu, Minimum dose method for walking-path planning of nuclear facilities, Ann. Nucl. Energy 83 (2015) 161-171.  https://doi.org/10.1016/j.anucene.2015.04.019
  27. M.K. Li, Y.K. Liu, M.J. Peng, C.L. Xie, S.Y. Wang, N. Chao, Z.B. Wen, Dynamic minimum dose path-searching method for virtual nuclear facilities, Prog. Nucl. Energy 91 (2016) 1-8.  https://doi.org/10.1016/j.pnucene.2016.04.001
  28. L. L Tao, P.C. Long, X.L. Zheng, X.L. Zheng, Z.H. Yang, L. M Shang, T. He, An improved A* algorithm-guided path-planning method for radioactive environment, J. Radiat. Res. Radiat. Process. 36 (2018) 56-61. 
  29. C. Chen, J.J. Cai, Z. Wang, F.C. Chen, W.J. Yi, An improved A* algorithm for searching the minimum dose path in nuclear facilities, Prog. Nucl. Energy 126 (2020), 103394. 
  30. N. Chao, Y.K. Liu, H. Xia, C.L. Xie, A. Ayodeji, H. Yang, L. Bai, A sampling-based method with virtual reality technology to provide minimum dose path navigation for occupational workers in nuclear facilities, Prog. Nucl. Energy 100 (2017) 22-32.  https://doi.org/10.1016/j.pnucene.2017.05.024
  31. N. Chao, Y.K. Liu, H. Xia, A. Ayodeji, L. Bai, Grid-based RRT* for minimum dose walking path-planning in complex radioactive environments, Ann. Nucl. Energy 115 (2018) 73-82.  https://doi.org/10.1016/j.anucene.2018.01.007
  32. N. Chao, Y.K. Liu, H. Xia, M.J. Peng, A. Ayodeji, DL-RRT* algorithm for least dose path Re-planning in dynamic radioactive environments, Nucl. Eng. Technol. 51 (2019) 825-836.  https://doi.org/10.1016/j.net.2018.11.018
  33. Z. Wang, J.J. Cai, Probabilistic roadmap method for path-planning in radioactive environment of nuclear facilities, Prog. Nucl. Energy 109 (2018) 113-120.  https://doi.org/10.1016/j.pnucene.2018.08.006
  34. Z. Wang, J.J. Cai, The path-planning in radioactive environment of nuclear facilities using an improved particle swarm optimization algorithm, Nucl. Eng. Des. 326 (2018) 79-86.  https://doi.org/10.1016/j.nucengdes.2017.11.006
  35. X. Xie, Z. Tang, J. Cai, The multi-objective inspection path-planning in radioactive environment based on an improved ant colony optimization algorithm, Prog. Nucl. Energy 144 (2021), 104076. 
  36. K. Tan, M.K. Li, H.X. Gu, M. Yang, A radiation avoiding algorithm of path optimization for radiation protection of workers and robots, Ann. Nucl. Energy 135 (2020), 106968. 
  37. Y.C. Lai, S. Smith, Metaheuristic minimum dose path planning for nuclear power plant decommissioning, Ann. Nucl. Energy 166 (2022), 108800. 
  38. M. Li, G. Wei, Z. Xu, J. Wang, M. Yang, An optimization algorithm based on artificial potential field and particle swarm optimization to avoid radiation exposure under radioactive environment, Nucl. Sci. Eng. 194 (2020) 447-461.  https://doi.org/10.1080/00295639.2019.1710975
  39. Q. Xiao, J. Cai, The path-planning in radioactive environment based on HIOSD-PRM method, Ann. Nucl. Energy 171 (2022), 109018. 
  40. D.V. Lu, D. Hershberger, W.D. Smart, Layered costmaps for context-sensitive navigation, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014. Chicago, IL, USA, September 14-18. 
  41. A. West, T. Wright, I. Tsitsimpelis, K. Groves, M.J. Joyce, B. Lennox, Real-time avoidance of ionising radiation using layered costmaps for mobile robots, Front. Robot. AI. 17 (2022), 862067. 
  42. M. Ernest Miyombo, Y.K. Liu, A. Ayodeji, Minimum dose path planning based on three-degree vertex algorithm and FLUKA modeling: radiation source discrimination and shielding considerations, Ann. Nucl. Energy 168 (2022), 108916. 
  43. K. Nagatani, S. Kiribayashi, Y. Okada, K. Otake, K. Yoshida, S. Tadokoro, K. Yoshida, Emergency response to the nuclear accident at the Fukushima Daiichi NPPs using mobile rescue robots, J. Field Robot. 30 (2013) 44-63.  https://doi.org/10.1002/rob.21439
  44. C. Ducros, G. Hauser, N. Mahjoubi, P. Girones, L. Boisset, A. Sorin, E. Jonquet, J.M. Falciola, A. Benhamou, RICA: a tracked robot for sampling and radiological characterization in the nuclear field, J. Field Robot. 34 (2017) 583-599.  https://doi.org/10.1002/rob.21650
  45. A. Sadrpour, J.H. Jin, A.G. Ulsoy, Mission energy prediction for unmanned ground vehicles using real-time measurements and prior knowledge, J. Field Robot. 30 (2013) 399-414.  https://doi.org/10.1002/rob.21453
  46. M. Dorigo, L.M. Gambardella, Ant colony system: a cooperative learning approach to the traveling salesman problem, IEEE. Evolut. Comput. 1 (1997) 53-66.  https://doi.org/10.1109/4235.585892
  47. X. Dai, S. Long, Z. Zhang, D. Gong, Mobile robot path planning based on ant colony algorithm with A* heuristic method, Front. Neurorob. 13 (2019) 1-23.