Paper Info
Title
A Hybrid System For Multi-Goal Navigation And Map Building Of An Autonomous Vehicle In Unknown Environments
Abstract
A solution by hybrid algorithms is proposed in this paper for real-time map building and navigation for multiple goals purpose. In real world applications, an intelligent mobile vehicle is required to reach multiple goals with a shortest path that, in this paper, is capable of being implemented in TSP (Traveling Salesman Problem) by a Genetic Algorithm (GA) with minimized overall distance. A D*-Lite-based algorithm is applied to generate path while a mobile vehicle explores through a terrain and builds a map in unknown environments. After the global path is planned, it creates a breadcrumb trail leading to the multiple goals. A LIDAR-based local navigation algorithm is employed to plan a collision-free path along breadcrumbs. In this paper, simulation and experimental results demonstrate that the real-time concurrent map building and multi-goal navigation of an autonomous vehicle is successfully performed under unknown environments.
Year
DOI
Venue
2013
10.1109/ROBIO.2013.6739632
2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO)
Keywords
Field
DocType
remotely operated vehicles,mobile robots,path planning,genetic algorithms
Remotely operated underwater vehicle,Real-time computing,Control engineering,Travelling salesman problem,Artificial intelligence,Genetic algorithm,Motion planning,Computer vision,Shortest path problem,Mobile robot navigation,Engineering,Hybrid system,Mobile robot
Conference
Citations 
PageRank 
References 
1
0.36
6
Authors
5
Name
Order
Citations
PageRank
Chaomin Luo118619.40
Simon X. Yang21029124.34
N. Mohan Krishnan311.71
Mark J. Paulik463.52
Yue Chen510.36