Paper Info
Title
Bioinspired cognitive model for autonomous behavior applied to obstacles avoidance in global navigation of a holonomic robot in a dynamic environment
Abstract
In this paper, we introduce a cognitive model inspired in a rough description of the human cognition process to provide a more efficient parallel architecture for autonomous reactions in real systems. The model is a non-hierarchical structure composed of three main parallel blocks-mind, reason, action-in a nested double closed-loop configuration for control and supervision; the mind is a practical representation of the system immersed in its environment, the reason an algorithmic problem solver and task planner with a supervisory close-loop, and the motion, is the set of actuators and their feedback controllers used to track the solution. This approach essentially keeps the main elements of other cognitive models but, instead of hierarchic layers, it introduces priority tasks in a parallel function, emulating the human mind. We describe the cognitive model and its implementation to solve the problem of obstacles avoidance in global navigation with a holonomic robot, specifically using an omnidirectional mobile robot in a changing-obstacle environment. We present some experimental results and we discuss about the observed properties of the proposed cognitive model, and we conclude with some final comments.
Year
DOI
Venue
2017
10.1109/ICEEE.2017.8108893
2017 14th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)
Keywords
Field
DocType
cognitive model,autonomous robotics,parallel processing,autonomous mobile robots
Holonomic,Control theory,Computer science,Control engineering,Vehicle dynamics,Solver,Mobile robot navigation,Cognitive model,Cognition,Robot,Mobile robot
Conference
ISBN
Citations 
PageRank 
978-1-5386-3407-3
0
0.34
References 
Authors
1
2
Name
Order
Citations
PageRank
Abelardo Gonzalez-Garcia100.34
Francisco Ruiz-Sanchez283.30