Mobile Manipulator Motion Planning Towards Multiple Goal Configurations

A number of methods have been developed for finding collision free paths for a manipulator moving from one configuration to another. In each of these cases the desired goal configuration must be chosen beforehand. However, in most applications there may be more than one configuration that satisfies the desired position and orientation requirements of the end effector. One of these configurations must be chosen for the path planner; generally we want to select the configuration that results in the lowest cost movement from the manipulator's current position. Until the motion plan is calculated, we cannot know which goal configuration to choose. This paper demonstrates a method for selecting the lowest cost path without needing to calculate a motion plan from the start position to all of the possible goal configurations. Generating motion plans is computationally expensive and it is desirable to limit these computations where ever possible. This is especially true in the case of mobile manipulators where the surrounding terrain for the motion planning calculation changes at each step, meaning that computational savings of reusing calculations from previous runs cannot be realised. The method demonstrated in this paper is shown to be much more suited to these types of applications than more traditional motion planning methods

[1]  Stefano Carpin,et al.  Robot motion planning using adaptive random walks , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[2]  Xu Dianguo,et al.  Development & Application of Wall-Climbing Robots , 1999, ICRA.

[3]  C. S. G. Lee,et al.  Robotics: Control, Sensing, Vision, and Intelligence , 1987 .

[4]  Daniela Rus,et al.  Task-reconfigurable robots: navigators and manipulators , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[5]  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).

[6]  Kazuhiko Kawamura,et al.  A Rubbertuator-based structure-climbing inspection robot , 1997, Proceedings of International Conference on Robotics and Automation.

[7]  E. Krause,et al.  Taxicab Geometry: An Adventure in Non-Euclidean Geometry , 1987 .

[8]  Jindong Tan,et al.  Multi-sensor referenced gait control of a miniature climbing robot , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[9]  J. Latombe,et al.  Adaptive dynamic collision checking for single and multiple articulated robots in complex environments , 2005, IEEE Transactions on Robotics.

[10]  Tomoaki Yano,et al.  Development of a self-contained wall climbing robot with scanning type suction cups , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[11]  Mark H. Overmars,et al.  Sampling and node adding in probabilistic roadmap planners , 2006, Robotics Auton. Syst..

[12]  Mark A. Minor,et al.  Design, implementation, and evaluation of an under-actuated miniature biped climbing robot , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[13]  G. Swaminathan Robot Motion Planning , 2006 .

[14]  Akira Nishi A biped walking robot capable of moving on a vertical wall , 1992 .

[15]  M. Murakami,et al.  Development of a semi self-contained wall climbing robot with scanning type suction cups , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.