Research on motion planning for an indoor spray arm based on an improved potential field method

Autoři: Dongjie Zhao aff001;  Bin Zhang aff002;  Ying Zhao aff001;  Qun Sun aff001;  Chuanjun Li aff002;  Chong Wang aff001
Působiště autorů: School of Mechanical & Automotive Engineering, Liaocheng University, Liaocheng, China aff001;  College of Engineering, China Agricultural University, Beijing, China aff002
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0226912


The target spraying effect of spray robots mainly depends on the control performance of the spraying arm during the processes of aiming and tracking. To further improve the robustness of the endpoint control and positioning accuracy of the spray arm, an improved potential field algorithm for the motion planning and control of the spray arm is proposed based on prophase research. The algorithm introduces a velocity potential field, visual field constraints and joint position limit constraints into the traditional artificial potential field method. The velocity potential field is used to ensure that the target state of the spraying arm is at the same velocity as the target crop (relative velocity) to achieve stable target tracking. The visual field constraints and joint position limit constraints are utilized to ensure the efficiency of the visual servo control and the movement of the spray arm. The algorithm can plan a feasible trajectory for the spraying arm in Cartesian space and image space, and use the speed controller to control the spraying arm movement along the trajectory for aiming and tracking. Simulation analysis shows that the algorithm can plan better motion trajectories than the servo controller based on image moments in previous studies. In addition, the experimental results show that the algorithm can effectively improve the robustness of targeting and tracking control for the spray robot.

Klíčová slova:

Cameras – Crops – Image processing – Imaging techniques – Prototypes – Robots – Simulation and modeling – Target detection


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