首页|New Robotics Findings from School of Applied Technology Described (Path Planning of Fruit And Vegetable Picking Robots Based on Improved A* Algorithm And Particle Swarm Optimization Algorithm)
New Robotics Findings from School of Applied Technology Described (Path Planning of Fruit And Vegetable Picking Robots Based on Improved A* Algorithm And Particle Swarm Optimization Algorithm)
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NETL
NSTL
Inst Natl Cercetare
Investigators publish new report on robotics. According to news reporting from Henan, People’s Republic of China, by NewsRx journalists, research stated, “Aiming at the suboptimal local path, slow convergence speed, and many inflection points in the path planning of fruit and vegetable picking robots in complex environments, a global planning method combining particle swarm optimization (PSO) algorithm and A* algorithm was proposed.” Our news editors obtained a quote from the research from School of Applied Technology: “Firstly, Manhattan distance was taken as a heuristic function of global programming based on the A* algorithm. Secondly, the step size of PSO was adjusted to optimize the path, shorten the path length, and reduce the number of inflection points. Finally, the planned path of the fruit and vegetable picking robot was smoothed so that it could steadily move along a smoother driving path in real scenarios. The experimental results show that compared with the traditional PSO algorithm, the hybrid algorithm based on the improved A* algorithm and PSO algorithm achieves a smoother path and fewer folding points.”
School of Applied TechnologyHenanPeople’s Republic of ChinaAsiaAlgorithmsEmerging TechnologiesMachine LearningNano-robotParticle Swarm OptimizationRobotics
NETL
NSTL
Inst Natl Cercetare
