Kinematic-Based Multi-Objective Design Optimization of a Grapevine Pruning Robotic Manipulator

Annual cane pruning of grape vineyards is a time-consuming and labor-intensive job, but no mechanized or automatic way has been developed to do it yet. Robotic can be perfect alternative human labor. This article proposes systematic seven-stage procedure design kinematically optimized manipulator, named ‘Prubot’, manage vineyards’ pruning. The manipulator structure was chosen, resulting in 7R (Revolute) with spherical shoulder wrist. To obtain the constraints, task space modeled. robot’s second third link lengths were determined by optimizing global translational version measure manipulability isotropy arm section. Finally, simulations confirmed appropriateness workspace. Furthermore, sampling-based path planning carried out evaluate manipulator’s kinematic performance. Results illustrated impressive performance robot terms success rate (≅100%). also suggest that among eight single-query algorithms used simulations, Lazy RRT KPIECE are best (≤5 s & ~100%) worst ≥5 &≤25% for such computation time rate, respectively. proposed this paper offers foundation task-based manipulator. It could promisingly designing similar agricultural manipulators.