Motion Planning and Controlling Algorithm for Grasping and Manipulating Moving Objects in the Presence of Obstacles

摘要

Many of the robotic grasping researches have been focusing on stationary objects. And for dynamic moving objects, researchers have been using real time captured images to locate objects dynamically. However, this approach of controlling the grasping process is quite costly, implying a lot of resources and image processing.Therefore, it is indispensable to seek other method of simpler handling In this paper, we are going to detail the requirements to manipulate a humanoid robot arm with 7 degree-of-freedom to grasp and handle any moving objects in the 3-D environment in presence or not of obstacles and without using the cameras. We use the OpenRAVE simulation environment, as well as, a robot arm instrumented with the Barrett hand. We also describe a randomized planning algorithm capable of planning. This algorithm is an extent of RRT-JT that combines exploration, using a Rapidly-exploring Random Tree, with exploitation, using Jacobian-based gradient descent, to instruct a 7-DoF WAM robotic arm, in order to grasp a moving target, while avoiding possible encountered obstacles . We present a simulation of a scenario that starts with tracking a moving mug then grasping it and finally placing the mug in a determined position, assuring a maximum rate of success in a reasonable time.