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Investigation of Branch Accessibility with a Robotic Pruner for Pruning Apple Trees

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Transactions of the ASABE. 64(5): 1459-1474. (doi: 10.13031/trans.14132) @2021
Authors:   Azlan Zahid, Long He, Daeun Choi, James Schupp, Paul Heinemann
Keywords:   Agricultural robotics, Collision-free path, Manipulator, Path planning, Robotic pruning, Virtual tree environment.


A branch accessibility simulation was performed for robotic pruning of apple trees.

A virtual tree environment was established using a kinematic manipulator model and an obstacle model.

Rapidly-exploring random tree (RRT) was combined with smoothing and optimization for improved path planning.

Effects on RRT path planning of the approach angle of the end-effector and cutter orientation at the target were studied.

Abstract. Robotic pruning is a potential solution to reduce orchard labor and associated costs. Collision-free path planning of the manipulator is essential for successful robotic pruning. This simulation study investigated the collision-free branch accessibility of a six rotational (6R) degrees of freedom (DoF) robotic manipulator with a shear cutter end-effector. A virtual environment with a simplified tall spindle tree canopy was established in MATLAB. An obstacle-avoidance algorithm, rapidly-exploring random tree (RRT), was implemented for establishing collision-free paths to reach the target pruning points. In addition, path smoothing and optimization algorithms were used to reduce the path length and calculate the optimized path. Two series of simulations were conducted: (1) performance and comparison of the RRT algorithm with and without smoothing and optimization, and (2) performance of collision-free path planning considering different approach poses of the end-effector relative to the target branch. The simulations showed that the RRT algorithm successfully avoided obstacles and allowed the manipulator to reach the target point with 23 s average path finding time. The RRT path length was reduced by about 28% with smoothing and by 25% with optimization. The RRT smoothing algorithm generated the shortest path lengths but required about 1 to 3 s of additional computation time. The lowest coefficient of variation and standard deviation values were found for the optimization method, which confirmed the repeatability of the method. Considering the different end-effector approach poses, the simulations suggested that successfully finding a collision-free path was possible for branches with no existing path using the ideal (perpendicular cutter) approach pose. This study provides a foundation for future work on the development of robotic pruning systems.

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