Title
On the construction of a RoboCup small size league team
Abstract
The Robot Soccer domain has become an important artificial intelligence test bench and a widely studied research area. It is a domain with real, dynamic, and uncertain environment, where teams of robots cooperate and face adversarial competition. To build a RoboCup Small Size League (SSL) team able to compete in the world championship requires multidisciplinary research in fields like robotic hardware development, machine learning, multi-robot systems, computer vision, control theory, and mechanics, among others. This paper intends to provide insights about the aspects involved on the development of the RoboFEI RoboCup SSL robot soccer team and to present the contributions produced over its course. Among these contributions, a computer vision system employing an artificial neural network (ANN) to recognize colors, a heuristic algorithm to recognize partially detected objects, an implementation of the known rapidly-exploring random trees (RRT) path planning algorithm with additional rules, enabling the angle of approach of the robot to be controlled, and a layered strategy software system. Experimental results on real robots demonstrate the high performance of the vision system and the efficiency of the RRT algorithm implementation. Some strategy functions are also experimented, with empirical results showing their effectiveness.
Year
DOI
Venue
2011
10.1007/s13173-011-0028-4
J. Braz. Comp. Soc.
Keywords
Field
DocType
robotic soccer · computer vision · neural networks · rrt path planning · omnidirectional control,software systems,computer vision,heuristic algorithm,vision system,machine learning,artificial neural network,path planning,neural network,artificial intelligent,control theory,rapidly exploring random tree
Data mining,Data structure,Multidisciplinary approach,Test bench,Computer science,League,Human–computer interaction,Artificial intelligence,Robot,Artificial neural network,World championship,Adversarial system
Journal
Volume
Issue
ISSN
17
1
1678-4804
Citations 
PageRank 
References 
2
0.41
24
Authors
4