A cell based voronoi roadmap for motion planning of articulated robots using movement primitives

The manufacturing industry today is still focused on the maximization of production. A possible development able to support the global achievement of this goal is the implementation of a new support system for trajectory-planning, specific for industrial robots. This paper describes the trajectory-planning algorithm, able to generate trajectories manageable by human operators, consisting of linear and circular movement primitives. First, the world model and a topology preserving roadmap are stored in a probabilistic occupancy octree by applying a cell extension based algorithm. Successively, the roadmap is constructed within the free reachable joint space maximizing the clearance to the obstacles. A search algorithm is applied on robot configuration positions within the roadmap to identify a path avoiding static obstacles. Finally, the resulting path is converted through an elastic net algorithm into a robot trajectory, which consists of canonical ordered linear and circular movement primitives. The algorithm is demonstrated in a real industrial manipulator context.

[1]  L. Dubins.  On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents , 1957 .

[2]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[3]  Charles W. Warren,et al.  Global path planning using artificial potential fields , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[4]  M. Overmars,et al.  Approximating generalized Voronoi diagrams in any dimension , 1995 .

[5]  Hongyan Wang,et al.  Nonuniform Discretization for Kinodynamic Motion Planning and its Applications , 2000, SIAM J. Comput..

[6]  Peter Norvig,et al.  Artificial intelligence - a modern approach, 2nd Edition , 2003, Prentice Hall series in artificial intelligence.

[7]  Aude Billard,et al.  Special Issue on Robot Learning by Observation, Demonstration, and Imitation , 2007, IEEE Trans. Syst. Man Cybern. Part B.

[8]  John Norrish,et al.  Recent Progress on Programming Methods for Industrial Robots , 2010, ISR/ROBOTIK.

[9]  Mark H. Overmars,et al.  A Comparative Study of Probabilistic Roadmap Planners , 2002, WAFR.

[10]  Joost N. Kok,et al.  Motion planning using a colored Kohonen network , 1993 .

[11]  A.G. Pipe,et al.  Nonholonomic Motion Planning by Means of Particles , 2006, 2006 International Conference on Mechatronics and Automation.

[12]  Thomas A. Fuhlbrigge,et al.  Automated industrial robot path planning for spray painting process: A review , 2008, 2008 IEEE International Conference on Automation Science and Engineering.

[13]  Steven Fortune,et al.  A sweepline algorithm for Voronoi diagrams , 1986, SCG '86.

[14]  P. Strevens.  Iii , 1985 .

[15]  Heinz Wörn,et al.  Online path planning with optimal C-space discretization , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[16]  Ellips Masehian,et al.  A voronoi diagram-visibility graph-potential field compound algorithm for robot path planning , 2004, J. Field Robotics.

[17]  Marina L. Gavrilova,et al.  Roadmap-Based Path Planning - Using the Voronoi Diagram for a Clearance-Based Shortest Path , 2008, IEEE Robotics & Automation Magazine.

[18]  Pascal Vasseur,et al.  Introduction to Multisensor Data Fusion , 2005, The Industrial Information Technology Handbook.

[19]  C. Kohrt,et al.  A robot manipulator communications and control framework , 2008, 2008 IEEE International Conference on Mechatronics and Automation.

[20]  Gerd Hirzinger,et al.  Capturing robot workspace structure: representing robot capabilities , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  Yoshifumi Kitamura,et al.  3-D path planning in a dynamic environment using an octree and an artificial potential field , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[22]  Yoram Koren,et al.  Potential field methods and their inherent limitations for mobile robot navigation , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[23]  Li Tao,et al.  Virtual engineering: challenges and solutions for intuitive offline programming for industrial robot , 2008, 2008 IEEE Conference on Robotics, Automation and Mechatronics.

[24]  Pierre Payeur.  Improving robot path planning efficiency with probabilistic virtual environment models , 2004, 2004 IEEE Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2004. (VCIMS)..

[25]  Dinesh Manocha,et al.  Interactive motion planning using hardware-accelerated computation of generalized Voronoi diagrams , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[26]  Marina L. Gavrilova,et al.  Voronoi diagram in optimal path planning , 2007, 4th International Symposium on Voronoi Diagrams in Science and Engineering (ISVD 2007).

[27]  Kyu Ho Park,et al.  A fast path planning by path graph optimization , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[28]  Irene Gargantini,et al.  Linear octtrees for fast processing of three-dimensional objects , 1982, Comput. Graph. Image Process..

[29]  Michael Jenkin,et al.  Exploiting Hierarchical Probabilistic Motion Planning for Robot Reachable Workspace Estimation , 2011 .