Multi-objective path planning for mobile robot in nuclear accident environment based on improved ant colony optimization with modified A∗
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
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* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP
Abstract
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* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP
참고문헌 (47)
- K. Qian, "Small teleoperated robot for nuclear radiation and chemical leak detection", Int. J. Adv. Rob. Syst, 9, pp.1~9 (2012)
- S. Kawatsuma, "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, pp.1~7 (2017)
- T. Kobayashi, "Development of remote surveillance squads for information collection on nuclear accidents", Adv. Robot, 16, pp.497~500 (2002)
- R. Guzman, "RESCUER: development of a modular chemical, biological, radiological, and nuclear robot for intervention, sampling, and situation awareness", J. Field Robot, 33, pp.931~945 (2016)
- S. Kawatsuma, "Emergency response by robots to Fukushima-Daiichi accident : summary and lessons learned", Ind. Robot, 39, pp.428~435 (2012)
- Y. Isozaki, "Development of a work robot with a manipulator and a transport robot for nuclear facility emergency preparedness", Adv. Robot, 16, pp.489~492 (2002)
- H. F. Zhou, "Radiation avoiding algorithm for nuclear robot path optimization", Ann. Nucl. Energy, 169, pp.108948~ (2022)
- Z. Chen, "Patrol robot path planning in nuclear power plant using an interval multi-objective particle swarm optimization algorithm", Appl. Soft Comput, 116, pp.108192~ (2022)
- Ying Huang, "Autonomous navigation of mobile robot in radiation environment with uneven terrain", International Journal of Intelligent Robotics and Applications, 7(3), pp.497~509 (2022), Springer Science and Business Media LLC[DOI]
- J. B. Wen, "Path planning for autonomous underwater vehicles under the influence of ocean currents based on a fusion heuristic algorithm", IEEE Trans. Veh. Technol, 70, pp.8529~8544 (2021)
- N. Ghita, "Trajectory planning for a car-like robot by environment abstraction", Robot, Auto. Syst, 60, pp.609~619 (2012)
- W. Z. Chi, "A generalized Voronoi diagram-based efficient heuristic path planning method for RRTs in mobile robots", IEEE Trans. Ind. Electron, 69, pp.4926~4937 (2022)
- H. S. Min, "Path planning of mobile robot by mixing experience with modified artificial potential field method", Adv. Mech. Eng, 7, pp.1~17 (2015)
- I. K. Ibraheem, "Path planning of an autonomous mobile robot using swarm based optimization techniques", Al-Khawarizmi. Eng. J, 12, pp.12~25 (2016)
- M. Davoodi, "Multi-objective path planning in discrete space", Appl. Soft Comput, 13, pp.709~720 (2013)
- B. Song, "An improved PSO algorithm for smooth path planning of mobile robots using continuous high-degree Bezier curve", Appl. Soft Comput, 100, pp.1~11 (2021)
- J. Guo, "The path planning for mobile robot based on bat algorithm", Int. J. Autom. Control, 9, pp.50~61 (2015)
- F. Hassan Ajeil, "A novel path planning algorithm for mobile robot in dynamic environments using modified bat swarm optimization", J. Eng, 2021, pp.37~48 (2021)
- F. H. Ajeil, "Grid-based mobile robot path planning using aging-based ant colony optimization algorithm in static and dynamic environments", Sensors, 20, pp.1880~ (2020)
- C. Miao, "Path planning optimization of indoor mobile robot based on adaptive ant colony algorithm", Comput. Ind. Eng, 156, pp.107230~ (2021)
- F. H. Ajeil, "Multi-objective path planning of an autonomous mobile robot using hybrid PSO-MFB optimization algorithm", Appl. Soft Comput, 89, pp.106076~ (2020)
- B. K. Oleiwi, "A hybrid approach based on ACO and Ga for multi objective mobile robot path planning", Appl. Mech. Mater, 527, pp.203~212 (2014)
- A.Q. Alzalloum, "Application of Shortest Path Algorithms to Find Paths of Minimum Radiation Dose", pp.2009
- K. Chizhov, "Methods of minimising doses incurred by external exposure while moving in radiation hazardous areas", J. Radiol. Prot, 37, pp.697~714 (2017)
- Q. Y. Pei, "Minimum collective dose based optimal evacuation path-planning method under nuclear accidents", Ann. Nucl. Energy, 147, pp.107644~ (2020)
- Y. K. Liu, "Minimum dose method for walking-path planning of nuclear facilities", Ann. Nucl. Energy, 83, pp.161~171 (2015)
- M. K. Li, "Dynamic minimum dose path-searching method for virtual nuclear facilities", Prog. Nucl. Energy, 91, pp.1~8 (2016)
- L. L Tao, "An improved A* algorithm-guided path-planning method for radioactive environment", J. Radiat. Res. Radiat. Process, 36, pp.56~61 (2018)
- C. Chen, "An improved A* algorithm for searching the minimum dose path in nuclear facilities", Prog. Nucl. Energy, 126, pp.103394~ (2020)
- N. Chao, "A sampling-based method with virtual reality technology to provide minimum dose path navigation for occupational workers in nuclear facilities", Prog. Nucl. Energy, 100, pp.22~32 (2017)
- N. Chao, "Grid-based RRT* for minimum dose walking path-planning in complex radioactive environments", Ann. Nucl. Energy, 115, pp.73~82 (2018)
- Nan Chao, "DL-RRT* Algorithm for Least Dose Path Re-planning in Dynamic Radioactive Environments", Nuclear Engineering and Technology, 51(3), pp.825~836 (2019), 한국원자력학회[DOI]
- Z. Wang, "Probabilistic roadmap method for path-planning in radioactive environment of nuclear facilities", Prog. Nucl. Energy, 109, pp.113~120 (2018)
- Z. Wang, "The path-planning in radioactive environment of nuclear facilities using an improved particle swarm optimization algorithm", Nucl. Eng. Des, 326, pp.79~86 (2018)
- X. Xie, "The multi-objective inspection path-planning in radioactive environment based on an improved ant colony optimization algorithm", Prog. Nucl. Energy, 144, pp.104076~ (2021)
- K. Tan, "A radiation avoiding algorithm of path optimization for radiation protection of workers and robots", Ann. Nucl. Energy, 135, pp.106968~ (2020)
- Y. C. Lai, "Metaheuristic minimum dose path planning for nuclear power plant decommissioning", Ann. Nucl. Energy, 166, pp.108800~ (2022)
- M. Li, "An optimization algorithm based on artificial potential field and particle swarm optimization to avoid radiation exposure under radioactive environment", Nucl. Sci. Eng, 194, pp.447~461 (2020)
- Q. Xiao, "The path-planning in radioactive environment based on HIOSDPRM method", Ann. Nucl. Energy, 171, pp.109018~ (2022)
- D.V. Lu, "Layered costmaps for context-sensitive navigation", IEEE, 2014, ~
- A. West, "Real-time avoidance of ionising radiation using layered costmaps for mobile robots", Front. Robot. AI, 17, pp.862067~ (2022)
- M. Ernest Miyombo, "Minimum dose path planning based on three-degree vertex algorithm and FLUKA modeling : radiation source discrimination and shielding considerations", Ann. Nucl. Energy, 168, pp.108916~ (2022)
- K. Nagatani, "Emergency response to the nuclear accident at the Fukushima Daiichi NPPs using mobile rescue robots", J. Field Robot, 30, pp.44~63 (2013)
- C. Ducros, "RICA : a tracked robot for sampling and radiological characterization in the nuclear field", J. Field Robot, 34, pp.583~599 (2017)
- A. Sadrpour, "Mission energy prediction for unmanned ground vehicles using real-time measurements and prior knowledge", J. Field Robot, 30, pp.399~414 (2013)
- M. Dorigo, "Ant colony system : a cooperative learning approach to the traveling salesman problem", IEEE. Evolut. Comput, 1, pp.53~66 (1997)
- X. Dai, "Mobile robot path planning based on ant colony algorithm with A* heuristic method", Front. Neurorob, 13, pp.1~23 (2019)