HOU Juntao,QIAN Lu,CAO Jingjing,et al.Robot path planning method based on a multi-strategy improved artificial lemming optimization algorithm[J].Journal of Mechanical Transmission,XXXX,XX(XX):1-11.
HOU Juntao,QIAN Lu,CAO Jingjing,et al.Robot path planning method based on a multi-strategy improved artificial lemming optimization algorithm[J].Journal of Mechanical Transmission,XXXX,XX(XX):1-11.DOI:
Robot path planning method based on a multi-strategy improved artificial lemming optimization algorithm
To address the issues of uneven initial population distribution
susceptibility to local optima
and insufficient directionality in local exploration within traditional artificial lemming algorithm (ALA) for mobile robot path planning
a multi-strategy improved artificial lemming algorithm (IALA) was proposed in this paper.
Methods
2
Firstly
Latin hypercube sampling was employed to initialize the population
enhancing the quality of global exploration starting points. Secondly
an anti-predation strategy was introduced during the exploration phase. Embedded after the algorithm's long-distance migration and burrowing behaviors
it forces individuals to deviate from current local optima
expanding the search scope. Finally
a raccoon tree-climbing strategy was proposed for the exploitation phase. This strategy combines the linear advancement update method from the raccoon optimization algorithm with Lévy flight
enhancing the algorithm's directional advancement capability and convergence robustness in the mid-to-late stages. To validate the proposed algorithm's effectiveness
experiments were conducted using six standard test functions and two sets of grid maps.
Results
2
Test results demonstrate that IALA achieves superior optimization accuracy and stability compared to the comparison algorithms. In path planning tests on 20×20 and 40×40 grid maps
its optimal path lengths were reduced by 1.17 and 3.82 units
respectively
compared to the standard lemming optimization algorithm. Additionally
IALA exhibited smaller standard deviations and smoother paths
validating its stability and reliability.
关键词
Keywords
references
Dian S Y , Zhong J N , Guo B , et al . A smooth path planning method for mobile robot using a BES-incorporated modified QPSO algorithm [J]. Expert Systems with Applications , 2022 , 208 : 118256 .
Wang Yubin , Shen Zhenjun , Wang Yuchen , et al . Research on path planning for tetrahedral robots based on A* algorithm [J]. Journal of Mechanical Transmission , 2024 , 48 ( 2 ): 42 - 47 .
Zhao Qian , Shi Yuqiang . Research on real time path planning and obstacle avoidance of AGV by integrating improved A* algorithm and DWA [J]. Modern Manufacturing Engineering , 2025 ( 5 ): 91 - 98 .
Yang Yuge , Hao Yangyang , Wang Yiwen . Sand cat swarm optimization algorithm based on weibull flight and warning mechanism and its application [J]. Computer Engineering and Applications , 2025 , 61 ( 2 ): 145 - 157 .
Yang Hong , Li Shengming . A path planning control algorithm for mobile self-guided robots based on improved slime mold optimization [J]. Machine Design & Research , 2025 , 41 ( 3 ): 359 - 366 .
Han Tao , Li Tingting , Huang Yourui . Agricultural UAV path planning based on improved hippopotamus optimization algorithm [J]. Transactions of the Chinese Society for Agricultural Machinery , 2026 , 57 ( 1 ): 339 - 347 .
Huang Kaiqi , Xu Jun . Multi-strategy improved whale optimization algorithm for mobile robot path planning [J]. Transducer and Microsystem Technologies , 2025 , 44 ( 7 ): 121 - 125 .
Xiao Y N , Cui H , Abu Khurma R , et al . Artificial lemming algorithm:a novel bionic meta-heuristic technique for solving real-world engineering optimization problems [J]. Artificial Intelligence Review , 2025 , 58 ( 3 ): 84 .
Zhao Cong , Yang Dingbang , Tang Kezong . Improved sparrow search algorithm fused with Latin hypercube sampling [J]. Journal of Fujian Computer , 2025 , 41 ( 8 ): 1 - 7 .
Zhu Y W , Huang H S , Wei J N , et al . ISO:an improved snake optimizer with multi-strategy enhancement for engineering optimization [J]. Expert Systems with Applications , 2025 , 281 : 127660 .
Dehghani M , Montazeri Z , Trojovská E , et al . Coati Optimization Algorithm:a new bio-inspired metaheuristic algorithm for solving optimization problems [J]. Knowledge-Based Systems , 2023 , 259 : 110011 .