Towards Incremental A-r-Star

Graph search based path planning is popular in mobile robot applications and video game programming. Previously, we developed the A-r-Star pathfinder, a suboptimal variant of the A-Star pathfinder with performance that scales linearly with increasing the resolution (size) and hence sparseness of the grid map of a given continuous world. This paper presents the study of the direct acyclic graph (tree structure) formed by the A-r-Star and outlines steps to developing an incremental version of the A-r-Star. The incremental version of A-r-Star is able to replan faster using information from previous searches to speed up subsequent searches.

[1]  David Furcy,et al.  Lifelong Planning A , 2004, Artif. Intell..

[2]  SungHwan Ahn,et al.  On-board odometry estimation for 3D vision-based SLAM of humanoid robot , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[4]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[5]  Edward Tunstel,et al.  The A-r-Star (Ar) Pathfinder , 2013 .

[6]  William E. Lorensen,et al.  Decimation of triangle meshes , 1992, SIGGRAPH.

[7]  Anthony Stentz.  Optimal and Efficient Path Planning for Unknown and Dynamic Environments , 1993 .

[8]  Y. Matsumotot,et al.  Development of intelligent wheelchair system with face and gaze based interface , 2001, Proceedings 10th IEEE International Workshop on Robot and Human Interactive Communication. ROMAN 2001 (Cat. No.01TH8591).

[9]  Ch. Roumenin,et al.  Occupancy grids building by sonar and mobile robot , 2007, Robotics Auton. Syst..

[10]  Maxim Likhachev,et al.  D*lite , 2002, AAAI/IAAI.