Visual Servoing Design and Control for Agriculture Robot; a Review

At the beginning of its application, arm-robot manipulator worked blindly in completing the assigned task, and along with the improvement of camera technology as it is getting cheaper and smaller, the application of visual sensor lead to visual servoing control which utilized target detection as the input to control/move the end-effector of an arm-robot. The application of camera in arm-robot manipulator is divided into eye-in-hand where a camera is mounted to the robot, and eye-to-hand where the camera is fixed elsewhere. Visual control involves kinematics modeling and target position in image plane provided by image processing to ensure the motion accuracy in grasping and harvesting the fruit. The end-effector movement for harvesting relies heavily on the accuracy of target position detection that can be obtained by image processing method. This paper is a review study that discusses the design of visual servoing control of an arm-robot manipulator applied in agriculture starting from kinematics and inverse kinematics for controlling the motion and trajectory of the robot, and image processing for target detecting. An example of an image processing method is given by using Edge Detection method for detecting a dragon fruit simulated in SCILAB.