For a lately constructed disease detection field robot, the segregation of unhealthy leaves from strawberry plants is a major task. In field operations, the picking mechanism is actuated via three previously derived inverse kinematic algorithms and their performances are compared. Due to the high risk of rapid and unexpected deviation from the target position under field circumstances, some compensation is considered necessary. For this purpose, an image-based visual servoing method via the camera-in-hand configuration is activated when the end-effector is nearby to the target leaf subsequent to performing the inverse kinematics algorithms.

In this study, a bio-inspired trajectory optimization method is proposed for visual servoing and the method is constructed based on a prey-predator relationship observed in nature (“motion camouflage”). In this biological phenomenon, the predator constructs its path in a certain subspace while catching the prey. The proposed algorithm is tested both in simulations and in hardware experiments.

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