Obstacle avoidance for mobile manipulation by real-time sensor-based redundancy resolution

Mobile manipulators provide manipulation operations with mobility capacity and have wide potentials in many applications. However, due to the high redundancy, the planning and control become more complicated and difficult, especially when obstacles occur. Most existing methods are based on the off-line algorithms and most of them mainly focus on planning a new collision-free path, which are not appropriate for some applications, such as teleoperation, and cost many system resources as well. Therefore this paper presents an online planning and control method for obstacle avoidance of mobile manipulators using the real-time sensor-based redundancy resolution. This method is implemented on a mobile manipulator with a 7-DOF manipulator and a 4-wheel drive mobile base. The experimental results demonstrate the effectiveness of this method.

[1]  Aiguo Song,et al.  Image based approach to obstacle avoidance in mobile manipulators , 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

[2]  Tomás Lozano-Pérez,et al.  Spatial Planning: A Configuration Space Approach , 1983, IEEE Transactions on Computers.

[3]  Charles A. Klein,et al.  A new formulation of the extended Jacobian method and its use in mapping algorithmic singularities for kinematically redundant manipulators , 1995, IEEE Trans. Robotics Autom..

[4]  Jon Rigelsford Introduction to Robotics: Analysis, Systems, Applications , 2003 .

[5]  Sukhan Lee,et al.  An extension to operational space for kinematically redundant manipulators: kinematics and dynamics , 2000, IEEE Trans. Robotics Autom..

[6]  A. Liegeois,et al.  Automatic supervisory control of the configuration and behavior of multi-body mechanisms , 1977 .

[7]  James J. Kuffner,et al.  Randomized statistical path planning , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Ning Xi,et al.  An online motion planning algorithm for a 7DOF redundant manipulator , 2010, 2010 IEEE International Conference on Robotics and Biomimetics.

[9]  Marc Toussaint,et al.  Robot trajectory optimization using approximate inference , 2009, ICML '09.

[10]  Oliver Brock,et al.  Toward Optimal Configuration Space Sampling , 2005, Robotics: Science and Systems.

[11]  Steven M. LaValle,et al.  RRT-connect: An efficient approach to single-query path planning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).