Cláudio Rodrigo Torres

Intelligent paraconsistent logic controller and autonomous mobile robot emmy II

In this work we present a logic controller based on Paraconsistent Annotated Logic named Paracontrol, which can be applied to resolve conflicts and to deal with contradictions and/or paracompleteness, by implementing a decision-making in the presence of uncertainties. Such controller was implemented in a real autonomous mobile robot Emmy II.

A sensing system for an autonomous mobile robot based on the paraconsistent artificial neural network

This paper shows a sensing system for an autonomous mobile robot. The Sensing System is based on the Paraconsistent Neural Network. The type of artificial neural network used in this work is based on the Paraconsistent Evidential Logic - Eτ. The objective of the Sensing System is to inform the other robot components the position where there is an obstacle. The reached results have been satisfactory.

Autonomous Mobile Robot Emmy III

This work presents some improvements regarding to the autonomous mobile robot Emmy based on Paraconsistent Annotated Evidential Logic Eτ. A discussion on navigation system is presented.

Intelligent System of Paraconsistent Logic to Control Autonomous Moving Robots

This paper shows a controller based on the evidential annotated paraconsistent logic E - Paracontrol. The Paracontrol is a variation of the logic analyzer. This work also shows an autonomous mobile robot, which is named Emmy II, in order to demonstrate the Paracontrols new properties. As an innovation, the Paracontrol presents besides the characteristics of the previous controller (manipulation of uncertainties, contradiction and paracompleteness information), the speed control in the various robots actions

The sensing system for the autonomous mobile robot Emmy III

This paper shows the results of the sensing system which was designed for the autonomous mobile robot Emmy III. The proposed Sensing System has as its mean part the Paraconsistent Neural Network. This artificial neural network is based on the Paraconsistent Evidential Logics — Et. The objective of the Sensing System is to inform the other robot components about the obstacle position. The reached results have been satisfactory.

Results of a sensing system for an autonomous mobile robot based on the paraconsistent artificial neural network

This paper shows the results of a sensing system for an autonomous mobile robot. The sensing system is based on the paraconsistent neural network. The type of artificial neural network used in this work is based on the paraconsistent evidential logic (Eτ). The objective of the sensing system is to inform the other robot components the obstacle position. The reached results have been satisfactory.

An Algorithmic Method Supported by Paraconsistent Annotated Logic Applied to the Determination of Friction Factors for Turbulent Flow in Smooth Pipes

The high complexity of the study of fluid flow is due to the existence of an excessive number of formulas to determine analytically the friction factor in pipelines. Currently, with more than a dozen formulas and the obligation of using graphics with readings on logarithmic scales for this purpose, the results are obtained with some degree of uncertainty. Recent work, with treatment of uncertainties, suggests that these complex calculations can be better performed with the basis of non-classical logic, such as the paraconsistent annotated logic (PAL) which has as a fundamental property the acceptance of contradictions. In this chapter we present a method that uses algorithms of PAL to make analysis in tests of fluid flow in smooth pipes. The PAL algorithms select and classify various results originating from the various equations for the obtaining of friction factor and, according to the Reynolds number, they optimize the calculation application of hydraulic projects in smooth pipes.