In response to the requirements of “high speed, high precision, and low damage” in tea fresh leaf sorting using a Delta parallel robot, this study conducts workspace simulation based on the MATLAB platform. The objective is to determine the optimal reachable workspace under given structural parameter constraints, analyze the influence of structural parameters on the workspace, and optimize parameter combinations through orthogonal experiments to enhance the robot’s adaptability to the sorting path (a gate-shaped trajectory). Firstly, the forward and inverse kinematic models of the Delta robot were established to derive the mapping relationship between the rotation angles of the active arms and the pose of the moving platform, thereby defining the mathematical representation of the workspace. Subsequently, key structural parameters—including the length of the active arms (L), the length of the passive arms (l), the circumradius of the base platform (R), and the circumradius of the moving platform (r)—were selected as influencing factors. An L9 orthogonal array was employed to design the experiments. The workspace volume for each parameter set was computed via MATLAB simulations, and the coverage of a gate-shaped trajectory (200 mm × 400 mm × 200 mm) was qualitatively assessed through visualization. Finally, the range analysis method was employed to determine the influence weight of each structural parameter on the workspace, leading to the identification of an optimal parameter set. The results demonstrated that the order of parameter influence was l > L > R > r. The optimized combination of the four parameters was obtained, which achieved complete coverage of the gate-shaped trajectory required for tea fresh leaf sorting. This study clarifies the quantitative relationship between structural parameters and the workspace, providing a scientific basis for the optimized design of Delta robots in tea leaf sorting applications. The proposed approach effectively addresses the long-standing issues of poor path adaptability and high damage rate of buds and leaves in conventional sorting robots.
Ren et al. (Thu,) studied this question.