Rami Al-Jarrah

Multi Objective Optimization of Trajectory Planning of Non-holonomic Mobile Robot in Dynamic Environment Using Enhanced GA by Fuzzy Motion Control and A*

a new hybrid approach based on Enhanced Genetic Algorithm by modified the search A* algorithm and fuzzy logic system is proposed to enhance the searching ability greatly of robot movement towards optimal solution state in static and dynamic environment. In this work, a global optimal path with avoiding obstacles is generated initially. Then, global optimal trajectory is fed to fuzzy motion controller to be regenerated into time based trajectory. When unknown obstacles come in the trajectory, fuzzy control will decrease the robot speed. The objective function for the proposed approach is for minimizing travelling distance, travelling time, smoothness and security, avoiding the static and dynamic obstacles in the robot workspace. The simulation results show that the proposed approach is able to achieve multi objective optimization in dynamic environment efficiently.

Blimp based on Embedded Computer Vision and Fuzzy Control for Following Ground Vehicles

Abstract This paper mainly covers the development of a fuzzy controller and a robust embedded visual system to follow a ground robot target by an indoor blimp robot. The presented control strategy is based on the visual information given by embedded computer vision. To realize the autonomous ground target following, an efficient vision-based object detection and localization algorithm is proposed by using Speeded Up Robust Features technique. The vision feedback is optimized by fuzzy set model to correct the prediction position information and then it is integrated with the blimps flight control system to guide it to follow the ground target. The fuzzy control system was implemented to make blimp robot complete the whole navigation performance and approaching the target. The overall vision system has been tested in actual flight missions, and the results show that the system is effective, robust and suitable for complex controls task.

Cooperative Space Time Coding for Semi Distributed Detection in Wireless Sensor Networks

Parallel distributed detection in wireless sensor networks (WSNs) is considered in this paper. In parallel architecture, sensors process the observations to make local decisions and send them to a central device called fusion center. Parallel architecture is assumed in this paper with cooperative sensors in order to obtain Alamouti space time block codes (STBCs). A similar idea was discussed by Vosoughi and Ahmadi (2009). Although the likelihood ratio provided in that paper is correct, the simulation results don’t make sense. In this paper, we are going to prove that the results provided in (Vosoughi & Ahmadi, 2009) are not correct. Upper bound for the detection performance is also derived. Furthermore, suboptimal fusion rules are derived to support our results. Moreover, correct results are shown in this paper.

Visual Fuzzy Control for Blimp Robot to Follow 3D Aerial Object

This works presents a novel visual servoing system in order to follow a 3D aerial moving object by blimp robot and to estimate the metric distances between both of them. To realize the autonomous aerial target following, an efficient vision-based object detection and localization algorithm is proposed by using Speeded Up Robust Features technique and Inverse Perspective Mapping which allows the blimp robot to obtain a bird’s eye view. The fuzzy control system is relies on the visual information given by the computer vision algorithm. The fuzzy sets model were introduced imperially based on possibilities distributions and frequency analysis of the empirical data. The system is focused on continuously following the aerial target and maintaining it within a fixed safe distance. The algorithm showing robustness against illumination changes , rotation invariance as well as size invariance. The results indicate that the proposed algorithm is suitable for complex control missions.