IJCTE 2016 Vol.8(1): pp. 24-31 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2016.V8.1014
Abstract—Many of researchers working on robotic grasping
tasks assume a stationary or fixed object, others have focused
on dynamic moving objects using cameras to record images of
the moving object and then they treated their images to estimate
the position to grasp it. This method is quite difficult, requiring
a lot of computing, image processing… Hence, it should be
sought more simple handling method. Moreover, the majorities
of robotic arms available for humanoid applications are
complex to control and yet expensive. In this paper, we are
going to detail the requirements to manipulating a 7-DoF WAM
robotic arm equipped with the Barrett hand to grasp and
handle any moving objects in the 3-D environment in the
presence of obstacles and without using the cameras. We used
the OpenRAVE simulation environment. We use an extension
of RRT-JT algorithm that interleaves exploration using a
Rapidly-exploring Random Tree with exploitation using
Jacobian-based gradient descent to control the 7-DoF WAM
robotic arm to avoid the obstacles, track a moving object, and
grasp planning. We present results in which a moving mug is
tracked, stably grasped with a maximum rate of success in a
reasonable time and picked up by the Barret hand to a desired
position.
Index Terms—Grasping, moving object, trajectory planning,
robot hand, obstacles.
The authors are with the National Institute of Applied Sciences and
Technology (INSAT), Tunisia (e-mail: chaabani.ali@gmail.com,
aroussia@insat.rnu.tn, mcfgsm@yahoo.fr).
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Cite:Ali Chaabaani, Mohamed Sahbi Bellamine, and Moncef Gasmi, "Controlling a Humanoid Robot Arm for Grasping and Manipulating a Moving Object in the Presence of Obstacles without Cameras," International Journal of Computer Theory and Engineering vol. 8, no. 1, pp. 24-31, 2016.