Name
Abstract | ||
|---|---|---|
This paper introduces the principle of biologically inspired neural network and analyzes the deficiency of this algorithm. Then, the road edge recognition algorithm and both static and moving obstacles detection method are described. On the basis of comparing the differences between indoor full coverage cleaning and outdoor, some improved full coverage path planning methods based on biologically inspired neural network and a novel concept of ¿fictitious frontier¿ are proposed. Finally, the computer simulation and cleaning experiments are conducted, and the results show the proposed improved method to be effective. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICNSC.2010.5461585 | ICNSC |
Keywords | Field | DocType |
moving obstacles detection method,neurocontrollers,static obstacles detection method,mobile robots,fictitious frontier,road edge recognition algorithm,edge detection,complete coverage path planning,biologically inspired neural network,road cleaning robot,computer simulation,collision avoidance,robot vision,neural network,navigation,mechanical engineering,robot kinematics,neural networks,path planning,sensors | Computer science,Edge detection,Real-time computing,Control engineering,Artificial intelligence,Recognition algorithm,Artificial neural network,Motion planning,Computer vision,Robot vision,Robot kinematics,Robot,Mobile robot | Conference |
Volume | Issue | ISBN |
null | null | 978-1-4244-6450-0 |
Citations | PageRank | References |
2 | 0.53 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guoqing Hu | 1 | 16 | 6.77 |
| Zhengwei Hu | 2 | 2 | 0.87 |
| Hongbo Wang | 3 | 4 | 3.74 |