Autonomous grasp of the embedded mobile manipulator with an eye-in-hand camera

This paper proposes an autonomous grasp method for the embedded mobile manipulator with an eye-in-hand CMOS camera. A three-stage scheme including object searching, approaching and grasping operation is adopted. With the help of visual information, the Bezier curve based approaching as well as vision-based approaching adjustment is applied, where an optimal Bezier path is obtained based on the evaluation of its length and curvature with constraints from the velocity, tangential acceleration and the minimum turning radius. When the mobile manipulator thinks that the object is within its grasping range, it executes the grasping operation according to image information and inverse kinematics. During the move-to-grasp process, the posture of the manipulator is adjusted in real time to endeavor to make the object be targeted. The validity of the proposed method is verified by experiments.