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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part C. Journal of mechanical engineering science >Minimum-time trajectory planning for an inchworm-like climbing robot based on quantum-behaved particle swarm optimization
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Minimum-time trajectory planning for an inchworm-like climbing robot based on quantum-behaved particle swarm optimization

机译：基于量子行为粒子群优化的九虫攀爬机器人的最小时间轨迹规划

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摘要

Since inchworm-like robots can exhibit excellent mobility in unstructured environments, it will be widely applied in agriculture, forestry, and high-altitude operations. Trajectory planning is an important issue for a climbing robot. This paper focuses on an inchworm-like climbing robot to plan its trajectory. The climbing process of the robot, especially the transitional gait when the robot is planned to climb over tree branches, is analyzed. Based on the gait analysis, the robot's geometrical path is determined, and its waypoints are described by joint angles. 3-5-3 type polynomial interpolation function is adopted to fit the robot's motion trajectory. To save the climbing time for the robot, its climbing transitional gaits for climbing over tree branches are optimized by using quantum-behaved particle swarm optimization algorithm to minimize the climbing time. Simulations are carried out to verify the developed trajectory planning, and the optimal results obtained from quantum-behaved particle swarm optimization are compared with the optimal solutions obtained by particle swarm optimization and genetic algorithm to further validate the effectiveness of the proposed method.
机译：由于九蚕的机器人可以在非结构化环境中表现出优异的流动性，因此它将广泛应用于农业，林业和高空操作。轨迹规划是攀登机器人的重要问题。本文重点介绍九虫式攀岩机器人，以规划其轨迹。分析了机器人的攀爬过程，特别是当机器人计划爬过树枝时的过渡步态，尤其是过渡步态。基于步态分析，确定机器人的几何路径，并且其航点由关节角描述。采用3-5-3型多项式插值函数来适合机器人的运动轨迹。为了节省机器人的攀爬时间，通过使用量子表现粒子群优化算法来优化其用于爬过树枝的攀爬过渡动态Ga，以最小化爬升时间。进行模拟以验证开发的轨迹规划，并将从量子行为粒子群优化获得的最佳结果与通过粒子群优化和遗传算法获得的最佳溶液进行比较，以进一步验证所提出的方法的有效性。

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