| Abstract: | 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 input/output 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. |
