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Proceedings ArticleDOI

Central action selection using sensor fusion

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TLDR
By integrating infrared, odometry and visual information within a reactive navigation scheme, this work uses sensor fusion to produce action selection in a rat-like fashion.
Abstract
A computational model of central action selection has been successfully embedded in a robotic platform. The proposed model, allows action selection between basic behaviors in a rat-like fashion. These behaviors imitate some home cage activities of a laboratory rat. The behavioral setting ranges from: search-'food', 'food'-pickup, 'food'-deposit, wall-finding and look-around. There is evidence that the switching of multiple sensorimotor systems in the vertebrate brain is similar to the concept of action oriented sensor fusion in AI robotics. In this work, by integrating infrared, odometry and visual information within a reactive navigation scheme, we use sensor fusion to produce action selection. Following this approach, initial experiments were conducted using a robot simulation software. Subsequent tests were carried out to evaluate the functionality of the model in a Khepera robot.

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Book

Nondestructive Measurement in Food and Agro-products

Jiewen Zhao, +1 more
TL;DR: In this paper, the authors present an 8-chapter book focusing on optical, acoustic and biological non-destructive techniques for food and agricultural applications, which is aimed at graduate students, senior undergraduate students, and researchers in academia and industry.
Book ChapterDOI

An effective robotic model of action selection

TL;DR: This paper presents a concise analysis of the requirements for effective action selection, and a centralized action selection model that fulfills most of these requirements.
Book ChapterDOI

Action Selection and Obstacle Avoidance Using Ultrasonic and Infrared Sensors

TL;DR: This paper is proposing to expand the basic sensing capabilities of the robot by the development of a rapid ultrasonic detection turret for the Khepera II robot, equipped with ultrasonic and infrared sensing capabilities.
Journal ArticleDOI

The Evolution of Motivated and Modulated Robot Selection

TL;DR: A selection model that allows a robot to select pre-evolved behaviour in a motivated environment and the results of varying, by hand and evolution, the levels of reward by the mesolimbic-cortical tone are described.
References
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Book

A robust layered control system for a mobile robot

TL;DR: A new architecture for controlling mobile robots is described, building a robust and flexible robot control system that has been used to control a mobile robot wandering around unconstrained laboratory areas and computer machine rooms.
Journal ArticleDOI

A robust layered control system for a mobile robot

TL;DR: In this paper, a new architecture for controlling mobile robots is described, which is made up of asynchronous modules that communicate over low-bandwidth channels, each module is an instance of a fairly simple computational machine.
Journal ArticleDOI

Color indexing

TL;DR: In this paper, color histograms of multicolored objects provide a robust, efficient cue for indexing into a large database of models, and they can differentiate among a large number of objects.
Book

An Behavior-based Robotics

TL;DR: Following a discussion of the relevant biological and psychological models of behavior, the author covers the use of knowledge and learning in autonomous robots, behavior-based and hybrid robot architectures, modular perception, robot colonies, and future trends in robot intelligence.
Book

Behavior-Based Robotics

TL;DR: Whence behaviour? animal behaviour robot behaviour behaviour based architectures representational issues for behavioural systems hybrid deliberative/rective architectures perceptual basis for behaviour-based control adaptive behaviour social behaviour fringe robotics - beyond behaviour.