The K-Framed Quadtrees Approach for Path Planning Through a Known Environment

One of the most important tasks for a mobile robot is to navigate in an environment. The path planning is required to design the trajectory that generates useful motions from the original to the desired position. There are several methodologies to perform the path planning. In this paper, a new method of approximate cells decomposition, called K-Framed Quadtrees is present, to which the algorithm A\(\star \) is applied to determine trajectories between two points. To validate the new approach, we made a comparative analysis between the present method, the grid decomposition, quadtree decomposition and framed quadtree decomposition. Results and implementation specifications of the four methods are presented.

[1]  Han-Pang Huang,et al.  Dynamic visibility graph for path planning , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[2]  Edwar Jacinto Gomez,et al.  A comparative study of geometric path planning methods for a mobile robot: Potential field and voronoi diagrams , 2013, 2013 II International Congress of Engineering Mechatronics and Automation (CIIMA).

[3]  Weilin Li,et al.  Probabilistic roadmap with self-learning for path planning of a mobile robot in a dynamic and unstructured environment , 2013, 2013 IEEE International Conference on Mechatronics and Automation.

[4]  Jean-Jacques E. Slotine,et al.  Real-time path planning using harmonic potentials in dynamic environments , 1997, Proceedings of International Conference on Robotics and Automation.

[5]  Howie Choset,et al.  Principles of Robot Motion: Theory, Algorithms, and Implementation ERRATA!!!! 1 , 2007 .

[6]  Roland Siegwart Introduction to Autonomous Mobile Robots second , 2011 .

[7]  Alberto Ortiz,et al.  A Bug-inspired algorithm for efficient anytime path planning , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Barry Brumitt,et al.  Framed-quadtree path planning for mobile robots operating in sparse environments , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).