Grasping the object with collision avoidance of wheeled mobile manipulator in dynamic environments

In this paper, the authors proposed a local motion planner with robot controller of the mobile manipulator to grasp the object in dynamic environments without any prior knowledge of environments. Our local motion planner is based on the concept of potential field and composed of the attractive and repulsive vectors. Then, the local motion planner decides the potential vector according to the attractive and repulsive vectors in various situations. Also, an approach to deal with the drawback of local minima is contained. The attractive and repulsive vectors are generated by the distances between the target, obstacles and the manipulator. For robot control, we take the end-effector as the control point and apply the potential vector with joint-level control, and moreover evaluate the mobility and the kinematic constraints of the robot to modify the joint velocities. The experiment platform is a wheeled mobile robot with a 5-DOF manipulator using Softkinetic DS325 which is a close range RGB-D camera as our sensor. Through several experiments, the results show that our framework is fast enough and valid to grasp the object in dynamic environments.