Implementation of Fuzzy Logic in FPGA for Maze Tracking of a Mobile Robot Based on Ultrasonic Distance Measurement

This paper describes an application of fuzzy logic to solve the problem of an autonomous mobile robot in tracking the path within a maze. The robot equipped with ultrasonic transceivers to measure the distance between robot and the wall. The information of distance then will be processed using fuzzy-based algorithm and implemented in two chips FPGA. The FPGA has responsibility to formulize the rule of the fuzzy and generate the PWM signals for robot's motors as the result of fuzzy inference. Implementing all necessary fuzzy logic algorithms will require many FPGA resources. Therefore, we use two FPGAs: XC4010E and XC4005XL. The first one for the fuzzification and rule base evaluation, and it consumes 98% of its resources (CLBs). The second one for defuzzification and PWM output generation, which utilizes 78% of all its CLBs. By implementing fuzzy logic using FPGA, the robot achieves relatively safe tracking the path in real-time sense

An integrated diagnostic architecture for autonomous robots

Abstract unavailable please refer to PD

Path Planning of Anti ship Missile based on Voronoi Diagram and Binary Tree Algorithm

The path planning of anti-ship missile should be considered both cruising in safety and striking in quick, which is an intractable problem. In particular, it is difficult to consider the safety of each missile path in the path planning of multiple missiles. To solve this problem, the “AREA Algorithm” is presented to divide the relative relations of areas：relative security area of the threat areas and fast-attack area of target approaching. Specifically，it is a way to achieve area division through the relationship between the target and the center of the operational area. The Voronoi diagram topology network, Dijkstra algorithm and binary tree algorithm have been used in the above process as well. Finally, Simulations have verified the feasibility and obvious advantages of “AREA Algorithm” compared with the single algorithm, and the tactical meaning in path planning of multiple missiles

Navigation of mobil robot using fuzzy logic controller

This chapter gives an overview of the research work reported in the thesis. First, the background of the research and the chosen problem domain are outlined. Then, the objectives of this research work are described. Finally, an outline of the thesis content is provided

Navigation Techniques for Control of Multiple Mobile Robots

The investigation reported in this thesis attempt to develop efficient techniques for the control of multiple mobile robots in an unknown environment. Mobile robots are key components in industrial automation, service provision, and unmanned space exploration. This thesis addresses eight different techniques for the navigation of multiple mobile robots. These are fuzzy logic, neural network, neuro-fuzzy, rule-base, rule-based-neuro-fuzzy, potential field, potential-field-neuro-fuzzy, and simulated-annealing- potential-field- neuro-fuzzy techniques. The main components of this thesis comprises of eight chapters. Following the literature survey in Chapter-2, Chapter-3 describes how to calculate the heading angle for the mobile robots in terms of left wheel velocity and right wheel velocity of the robot. In Chapter-4 a fuzzy logic technique has been analysed. The fuzzy logic technique uses different membership functions for navigation of the multiple mobile robots, which can perform obs..

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available