首页|Study Results from Northeastern University in the Area of Robotics Reported (A N ovel Robot Path Planning Algorithm Based On the Improved Wild Horse Optimiser Wi th Hybrid Strategies)
Study Results from Northeastern University in the Area of Robotics Reported (A N ovel Robot Path Planning Algorithm Based On the Improved Wild Horse Optimiser Wi th Hybrid Strategies)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Robotics are presented in a new rep ort. According to news reporting originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “Metaheuristic algorithms pla y a pivotal role in addressing the challenges of robot path planning, offering v ersatile, and efficient solutions. Nevertheless, the standard wild horse optimis er (WHO) has limitations, including limited population diversity during initiali sation, constrained global search capability, and challenges in escaping local o ptima.” Our news editors obtained a quote from the research from Northeastern University , “This paper proposed an improved WHO with hybrid strategies (HI-WHO) to overco me these disadvantages in solving robot path planning problem. The algorithm emp loys Sobol sequence for uniform population initialisation, integrating the Le <acute accent >vy flight strategy, and dynamic adaptive f actor to balance exploration and exploitation. Concurrently, it ensures global s earch capability and prevents local optima by using the lens imaging opposition- based learning strategy and greedy mechanism. The robustness and effectiveness of the enhanced algorithm were evaluated on a set of 20 benchmark functions.”
ShenyangPeople’s Republic of ChinaAs iaAlgorithmsEmerging TechnologiesMachine LearningRobotRoboticsNorthe astern University
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