Elliptical Features for Image-Based Visual Servoing Toward Control of UR5 Robot Arm Manipulator

Robots are increasingly prevalent in various applications, such as farming, where they undertake multiple tasks, including monitoring, sorting, and fruit picking. Effective control of these robots is essential for successful task execution. Visual Servoing (VS) is a control scheme employed for controlling these robots, wherein control is based on visual feedback. Image-Based Visual Servoing (IBVS) utilizes visual features to control the robot’s movements. Appropriate visual features and control schemes selection is crucial for the successful implementation of IBVS controlled applications. Image moments have demonstrated its usefulness in the selection of effective visual features. This study concentrates on defining robust features for the IBVS of a 6-degree-of-freedom (DOF) robot manipulator, with validation conducted using the condition number. The results indicate that the proposed features are effective for IBVS applications.