Searching for Shortest and Safest Paths Along Obstacle Common Tangents

Abstract

This thesis describes a method for computing globally shortest paths for a point robot in a two-dimensional, orthogonal world composed of convex and concave polygons through the construction of obstacle common tangent visibility graphs. Visibility and intersection testing are based on the orientation of three or more points in the plane, and complex obstacle tangent visibility graphs are constructed using only these orientation relationships. Obstacle common tangents for convex and concave polygonal obstacles are implemented as a computational representation of locally shortest paths. A series of tangent sequences form global paths which equate to global path equivalence classes, effectively reducing the path finding problem to that of finding the shortest path in the path equivalence class. A simple and logical approach for processing concave polygons using convex subpolygons is implemented, allowing common tangent construction and path searching algorithms to process complex geometrical shapes in an efficient and symbolically unique fashion. Dijkstra's algorithm is implemented using heuristic control for optimal path searching. The framework for utilizing constant clearance strips for safe path planning along obstacle common tangents is presented but not fully implemented.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1991
Accession Number
ADA247929

Entities

People

  • Jerry A. Crane

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algebraic Topology
  • Application Software
  • Automata Theory
  • California
  • Cartesian Coordinates
  • Classification
  • Computer Programming
  • Computer Science
  • Computers
  • Coordinate Systems
  • Lisp Programming Language
  • Motion Planning
  • Operating Systems
  • Programming Languages
  • Robots
  • Test Methods
  • United States

Readers

  • Graph Algorithms and Convex Optimization.
  • Operations Research
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy