Year: 2007
Type: dissertation
Abstract: This paper describes development of autonomous navigation system based on Simultaneous Localization And Map building (SLAM).SLAM is possible for an autonomous vehicle to start in an unknown location in an unknown environment and, using relative observations only, incrementally build a perfect map of the world and to compute simultaneously a bounded estimate of mobile robot location by extended Kalman filter.This paper describes a new implementation of the SLAM algorithm for a mobile robot operating in an outdoor environment such as IGVC Navigation Challenge, using relative obstacle observation profile from laser rangefinder.The feature of proposed implementation is employing simple map management algorithm and obstacle data association based on the extended Kalman filter.To confirm the proposed SLAM method, an electric wheelchair based mobile robot is used for implementation and testing.
Author: 祐樹 樽床
Language: Japanese
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W335894052