Path Planning Optimization Algorithm of Track Translation Fruit and Vegetable Picking Manipulator - Zhu, Fengwu; Zhang, Weijian; Meng, Xianzhang; Zhao, Qinglai (International Journal of Industrial Engineering: Theory, Applications and Practice, 2024)
The uncertainty of the environment has brought some difficulties to the path planning of the robot arm. In order to improve the path planning effect of the fruit and vegetable picking robot arm, an optimization algorithm for the path planning of the fruit and vegetable picking robot arm with track translation is proposed. By improving the convolution layer of a convolutional neural network, increasing the number of convolution layers and reducing the calculation parameters, the target fruit and vegetable position detection results are obtained to reduce the computational complexity. TOF camera and binocular vision technology are used to judge whether there are obstacles around fruits and vegetables, and SLAM positioning technology is introduced to obtain the three-dimensional position coordinates of target fruits and vegetables and different kinds of obstacles around them, which provides complete information for path planning. The discrete guiding points are obtained by the semantic label map of the road area, and the road guiding lines are obtained by fitting the discrete guiding points with B-spline curves. Through the evaluation function, the guideline information is introduced into the dynamic window method to develop the path planning of the track translation fruit and vegetable picking manipulator so as to achieve the goal of path optimization. The test results show that the proposed algorithm can quickly and effectively realize the path planning of the track translation fruit and vegetable picking manipulator.