Intelligent mobile manipulator navigation using adaptive neuro-fuzzy systems

This paper describes reactive control of a mobile robot using fuzzy logic in a distributed environment. Simulation results of the reactive fuzzy controller in a particular maze problem illustrate the effectiveness of the proposed approach. The mobile robot is able to solve the maze problem with the use of fuzzy rules designed with expert knowledge.

Reactive control of a mobile robot in a distributed environment using fuzzy logic

This paper describes reactive and tracking control of a mobile robot using integration methods to combine the response of both types of controls based on fuzzy logic. Simulation and experimental results of the complete system demonstrates the effectiveness of the proposed approach.

Reactive and tracking control of a mobile robot in a distributed environment using fuzzy logic

During the actual application of ANN (Artificial Neural Network), the sample functions needed to be learned often present subsection attributes. It is very difficult to simulate such kinds of sample functions only with single structure ANNs. We are inspired by the running principle of human's intelligent activities which can only be accomplished with the support of different brain function subareas. The multiple subareas cooperate with each other, and then the high quality intelligent activities of humans can be performed. In this paper a kind of largescale ANN, with heterogeneous function subnets, is proposed in order to overcome the shortages of traditional ANNs. At last, the capability of the largescale ANN is evaluated with a typical example, and its performances are also contrasted with traditional ANNs.

Largescale Artificial Neural Network Owning Function Subnets

We present a support system for changes detection in fundus images of the same patient taken at different time intervals. This process is useful for monitoring pathologies lasting for long periods of time, as are usually the ophthalmologic. We propose a flow of preprocessing, processing and postprocessing applied to a set of images selected from a public database, presenting pathological advances. A test interface was developed designed to select the images to be compared in order to apply the different methods developed and to display the results. We measure the system performance in terms of sensitivity, specificity and computation times. We have obtained good results, higher than 84% for the first two parameters and processing times lower than 3 seconds for 512x512 pixel images. For the specific case of detection of changes associated with bleeding, the system responds with sensitivity and specificity over 98%.

http://iopscience.iop.org/article/10.1088/1742-6596/332/1/012036/pdf

Analysis and Implementation of Methodologies for the Monitoring of Changes in Eye Fundus Images

The purpose of this paper is to introduce a cost-effective way to design robot vision and control software using Matlab for an autonomous robot designed to compete in the 2004 Intelligent Ground Vehicle Competition (IGVC). The goal of the autonomous challenge event is for the robot to autonomously navigate an outdoor obstacle course bounded by solid and dashed lines on the ground. Visual input data is provided by a DV camcorder at 160 x 120 pixel resolution. The design of this system involved writing an image-processing algorithm using hue, satuaration, and brightness (HSB) color filtering and Matlab image processing functions to extract the centroid, area, and orientation of the connected regions from the scene. These feature vectors are then mapped to linguistic variables that describe the objects in the world environment model. The linguistic variables act as inputs to a fuzzy logic controller designed using the Matlab fuzzy logic toolbox, which provides the knowledge and intelligence component necessary to achieve the desired goal. Java provides the central interface to the robot motion control and image acquisition components. Field test results indicate that the Matlab based solution allows for rapid software design, development and modification of our robot system.

Autonomous robot vision software design using Matlab toolboxes

Autonomous robotics projects encompass the rich nature of integrated systems that includes mechanical, electrical, and computational software components. The availability of smaller and cheaper hardware components has helped make possible a new dimension in operational autonomy. This paper describes a mobile robotic platform consisting of several integrated modules including a laptop computer that serves as the main control module, microcontroller-based motion control module, a vision processing module, a sensor interface module, and a navigation module. The laptop computer module contains the main software development environment with a user interface to access and control all other modules. Programming language independence is achieved by using standard inputsoutput computer interfaces including RS-232 serial port, USB, networking, audio input and output, and parallel port devices. However, with the same hardware technology available to all, the distinguishing factor in most cases for intelligent systems becomes the software design. The software for autonomous robots must intelligently control the hardware so that it functions in unstructured, dynamic, and uncertain environments while maintaining an autonomous adaptability. This paper describes how we introduced fuzzy logic control to one robot platform in order to solve the 2003 Intelligent Ground Vehicle Competition (IGVC) Autonomous Challenge problem. This paper also describes the introduction of hybrid software design that utilizes Fuzzy Evolutionary Artificial Neural Network techniques. In this design, rather than using a control program that is directly coded, the robot's artificial neural net is first trained with a training data set using evolutionary optimization techniques to adjust weight values between neurons. The trained neural network with a weight average defuzzification method was able to make correct decisions to unseen vision patterns for the IGVC Autonomous Challenge. A comparison of the Lawrence Technological University robot designs and the design of the other competing schools shows that our platforms were the most affordable robot systems to use as tools for computer science and engineering education. © 2004 Wiley Periodicals, Inc.

Maurice Tedder

Papers

Autonomous robot vision software design using Matlab toolboxes

An affordable modular mobile robotic platform with fuzzy logic control and evolutionary artificial neural networks