Paper Info
Title
Simulated Visual Perception-Based Control for Autonomous Mobile Agents
Abstract
Autonomous robots, such as automatic vacuum cleaners, toy robot dogs, and autonomous vehicles for the military, are rapidly becoming a part of everyday life. As a result the need for effective algorithms to control these agents is becoming increasingly important. Conventional path finding techniques rely on a representation of the world that can be analysed mathematically to find the best path. However, when an agent is placed into the real world in a place it has not seen be- fore, conventional techniques frequently fail and a fundamen- tally different approach to path finding is required. The agent must rely on its senses, such as the input from a mounted camera, using this information to get around. We are espe- cially interested in algorithms for use in highly interactive virtual environments such as computer games. In this paper we devise and analyse a technique which enables autonomous agents to navigate their way around a virtual city by using only what they see from their point of view. Since the scenes are computer generated we can use for the player's view and the agent's view representations with different visual com- plexity and hence improve the efficiency and effectiveness of the neural network. We show that by using neural networks agents can learn how to avoid obstacles, to follow the road, and we demonstrate that this method might even be useful for integration in path finding algorithm.
Year
Venue
Keywords
2006
FLAIRS Conference
path finding,autonomous agent,visual perception,mobile agent,neural network
Field
DocType
Citations 
Visual complexity,Autonomous agent,Everyday life,Computer science,Human–computer interaction,Artificial intelligence,Artificial neural network,Robot,Multimedia,Machine learning,Visual perception
Conference
0
PageRank 
References 
Authors
0.34
9
3
Name
Order
Citations
PageRank
Daniel Flower100.34
Burkhard Wünsche214724.91
Hans W. Guesgen354376.69