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首页> 外文期刊>Computers and Electronics in Agriculture >RRT-based path planning for an intelligent litchi-picking manipulator
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RRT-based path planning for an intelligent litchi-picking manipulator

机译：基于RRT的智能荔枝采摘机械手的路径规划

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摘要

Aiming to realize the obstacle avoidance of the litchi-picking robot in dynamic and unstructured environments, an improved rapidly exploring random tree (RRT) algorithm is presented in this study. By establishing the collision detection model of the manipulator and obstacles, the obstacle avoidance path planning is carried out. The idea of target gravity was adopted to accelerate the path search speed. To optimize the path generated by RRT, a genetic algorithm (GA) and smooth processing were proposed. Performance tests in a virtual environment showed that the optimal combination of step sizes in the path search were 1.6 degrees for step size 1 and 2 degrees for step size 2. The time to achieve the path was 0.47 s, and the success rate was 100%. The path length was shortened by 20% after optimization. Experiments in the real environment were carried out for the 6 degrees of freedom (DOF) picking manipulator to pick litchi, and the results showed that the collision-free path planned by the proposed algorithm could successfully drive the manipulator from its initial position to the goal position without any collision.
机译：旨在实现动态和非结构化环境中的荔枝拣选机器人的障碍物，在本研究中介绍了一种改进的快速探索随机树（RRT）算法。通过建立操纵器和障碍物的碰撞检测模型，执行避免避免路径规划。采用目标重力的思想加速路径搜索速度。为了优化RRT产生的路径，提出了遗传算法（GA）和平滑处理。虚拟环境中的性能测试显示，步进搜索中的步进尺寸的最佳组合为步长为1.6度，用于步长2.实现路径的时间为0.47 s，成功率为100％ 。优化后，路径长度缩短了20％。实际环境中的实验是为挑选荔枝的6度自由（DOF）拣选机械手进行了实际环境，结果表明，所提出的算法计划的防撞路径可以成功地将机械手从其初始位置驱动到目标位置没有任何碰撞。

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