In different weed distributions, the dynamic coverage algorithm for mechanical selective weeding robot

A weeding robot's working range and accuracy are vital indicators of the robot. Selective weeding robots can accurately weed and have higher control requirements. We designed the dynamic coverage algorithm for mechanical selective weeding robot in different weed distributions. The robot comprises a control, actuator, and mobile module. The actuator module includes a four-degree-of-freedom mechanical work device. It removes weeds under crops. The mechanical work device was resolved through the D-H matrix. It provided a reference for robot control and verified the feasibility of the mechanism by trajectory simulation. The dynamic coverage algorithm autonomously selects the best algorithm by the coverage of each area. The result shows the coverage path for different percentages of weeds. The dynamic coverage algorithm demonstrates good dynamic performance in different weed distributions. The result compares the dynamic coverage algorithm with the other three algorithms (BCD algorithm, Greedy algorithm, and Segmentation-based algorithm). Our algorithm reduces the average path of 10.9%, 16.5%, and 21.5%. Finally, we tested the robot in an indoor environment. It could successfully avoid the crop to complete the precise weeding work. The dynamic coverage algorithm offers a solution for selective weeding robots.