Robot navigation algorithms using learned spatial graphs

Autor:	C.R. Weisbin, S U N Rao, S. Sitharama Iyengar, C. Jorgensen
Rok vydání:	1986
Předmět:	business.industry Computer science General Mathematics Terrain Robotics Global Map Mobile robot navigation Computer Science Applications Control and Systems Engineering Obstacle Path (graph theory) Robot Computer vision Artificial intelligence business Voronoi diagram Software
Zdroj:	Robotica. 4:93-100
ISSN:	1469-8668 0263-5747
DOI:	10.1017/s0263574700008559
Popis:	SUMMARYFinding optimal paths for robot navigation in a known terrain has been studied for some time but, in many important situations, a robot would be required to navigate in completely new or partially explored terrain. We propose a method of robot navigation which requires no pre-learned model, makes maximal use of available information, records and synthesizes information from multiple journeys, and contains concepts of learning that allow for continuous transition from local to global path optimality. The model of the terrain consists of a spatial graph and a Voronoi diagram. Using acquired sensor data, polygonal boundaries containing perceived obstacles shrink to approximate the actual obstacles surfaces, free space for transit is correspondingly enlarged, and additional nodes and edges are recorded based on path intersections and stop points. Navigation planning is gradually accelerated with experience since improved global map information minimizes the need for further sensor data acquisition. Our method currently assumes obstacle locations are unchanging, navigation can be successfully conducted using two-dimensional projections, and sensor information is precise.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::cf9de45883eb9cb3adb1e1fa7efeeb28 https://doi.org/10.1017/s0263574700008559 Zobrazit plný text záznamu