The complexity of robot motion planning
The complexity of robot motion planning
Algorithmic motion planning in robotics
Handbook of theoretical computer science (vol. A)
Gross motion planning—a survey
ACM Computing Surveys (CSUR)
Robot motion planning: a distributed representation approach
International Journal of Robotics Research
A convex polygon among polygonal obstacles: placement and high-clearance motion
Computational Geometry: Theory and Applications
Computational geometry in C
SCG '85 Proceedings of the first annual symposium on Computational geometry
An algorithm for planning collision-free paths among polyhedral obstacles
Communications of the ACM
Robot Motion Planning
Visible Decomposition: Real-Time Path Planning in Large Planar Environments
Visible Decomposition: Real-Time Path Planning in Large Planar Environments
Robust and Accurate Vectorization of Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Planning Algorithms
Vectorization of gridded urban land use data
ACM SIGGRAPH 2007 posters
Topologically-directed navigation
Robotica
Information Processing Letters
A new 2D tessellation for angle problems: The polar diagram
Computational Geometry: Theory and Applications
Technical Section: Collision detection using polar diagrams
Computers and Graphics
Visibility of point clouds and mapping of unknown environments
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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The Path Planning problem is a common topic for Robotics and Computational Geometry. Many important results have been found to this classic problem, some of them based on plane or space tessellation. The new approach we propose in this paper computes a partition of the plane called the Polar Diagram, using angle properties as criterion of construction. Compared to some other plane partitions as Voronoi Diagrams, this tessellation can be computed much more efficiently for different geometric objects. The polar diagram used as preprocessing can be applied to many geometric problems where the solution can be given by angle processing, such as Visibility or Path Planning problems.