Control structure for a car-like robot using artificial neural networks and genetic algorithms

The idea of improving human’s life quality by making life more comfortable and easy is nowadays possible using current technologies and techniques to solve complex daily problems. The presented idea in this work proposes a control strategy for autonomous robotic systems, specifically car-like robots. The main objective of this work is the development of a reactive navigation controller by means of obstacles avoidance and position control to reach a desired position in an unknown environment. This research goal was achieved by the integration of potential fields and neuroevolution controllers. The neuro-evolutionary controller was designed using the (NEAT) algorithm “Neuroevolution of Augmented Topologies” and trained using a designed training environment. The methodology used allowed the vehicle to reach a certain level of autonomy, obtaining a stable controller that includes kinematic and dynamic considerations. The obtained results showed significant improvements compared to the comparison workCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQNão te

Behavior-based Fuzzy Control For A Mobile Robot With Non-holonomic Constraints

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2005Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2005Bu çalışmada robotik alanında yeni yaklaşımlar olan davranış temelli robotik ve bulanık mantık konuları gerçek zamanda mobil robot uygulamaları bakımından incelenmiş, dört ilerlemeli, dört yönelmeli bir mobil robot için Engelden Sakın , Hedefe Git , Duvarı İzle , Yola Teğet İlerle , Avare Gez davranışları oluşturulmuştur. Bu davranışların içinden Engelden Sakın , Hedefe Git ve Duvarı İzle davranışları için sonar sensör matematik modelleri oluşturulmuş ve bu davranışların yapısında bulanık mantık yaklaşımı kullanılmıştır. Mobil robot, kinetik ve dinamik olarak holonomik olmayan kısıtları kullanılarak modellenmiştir ve simülasyon sırasında mobil robotun pozisyonu, tekerlek ve robot yönelimleri, tekerlek ve robot hızları, tekerlek torkları gibi parametreler izlenebilmektedir. Davranışlar da, simülasyon ortamında kazanımları, bulanık mantık işleme yapıları, gerçek zaman uygulanabilirliği ve davranışların koordine edilmeleri bakımından incelenmiştir. Bu çalışma gerçek bir robotta yapılacak deneyler için temel teşkil etmektedir.In this study, the new approaches to the robotics subject, behavior-based robotics and fuzzy logic control are investigated for the real-time applications of mobile robots, Avoid Obstacle , Move to Goal , Wall Following , Head-on , Wander behaviors are built up for a four-wheel driven and four-wheel steered mobile robot. Sonar sensor mathematical models are formed for Avoid Obstacle , Move to Goal and Wall Following behaviors and fuzzy logic concepts are used in the structure of these behaviors. The mobile robot is modelled kinematically and dynamically considering the non-holonomic constraints. The posture and speed of the robot and the configurations, speeds and torques of the wheels can be obtained from the simulation. The behaviors are investigated regarding their gains, fuzzy inference structures, real-time applicabilities and thein coordination. This study constitutes basis for the experiments on a real mobile robot.Yüksek LisansM.Sc

An hybridization of global-local methods for autonomous mobile robot navigation in partially-known environments

This paper deals with the navigation problem of an autonomous non-holonomic mobile robot in partially-known environment. In this proposed method, the entire process of navigation is divided into two phases: an off-line phase on which a distance-optimal reference trajectory enables the mobile robot to move from an initial position to a desired target which is planned using the B-spline method and the Dijkstra algorithm. In the online phase of the navigation process, the mobile robot follows the planned trajectory using a sliding mode controller with the ability of avoiding unexpected obstacles by the use of fuzzy logic controller. Also, the fuzzy logic and fuzzy wall-following controllers are used to accomplish the reactive navigation mission (path tracking and obstacle avoidance) for a comparative purpose. Simulation results prove that the proposed path planning method (B-spline) is simple and effective. Also, they attest that the sliding mode controller track more precisely the reference trajectory than the fuzzy logic controller (in terms of time elapsed to reach the target and stability of two wheels velocity) and this last gives best results than the wall-following controller in the avoidance of unexpected obstacles. Thus, the effectiveness of our proposed approach (B-spline method combined with sliding mode and fuzzy logic controllers) is proved compared to other techniques

Fuzzy Logic Controller Design for Leader-Follower Robot Navigation

Mobile robots are applied everywhere in the human's life, starting from industries to domestics. This phenomenon makes it one of the most studied subjects in electronics engineering. Navigation is always an issue for this kind of robot, to ensure it can finish its task safely. Giving it a “brain” is one of the ways to create an autonomous navigating robot. The Fuzzy logic controller is a good choice for the “brain” since it does not need accurate mathematical modeling of the system. Only by utilizing the inputs from sensors are enough to design an effective controller. This paper presents an FLC design for leader-follower robot. This FLC design is the improvement of FLC application in a single two differential-driven mobile robot. The relation between leader and follower robot is modeled linearly as a spring-damper system. Simulation proves the feasibility of the proposed method in several environment setting, and this paper also shows that the method can be easily extended to one leader and more than one follower's formation. The research in this paper has introduced in the classroom as the teaching-learning media to improve students' involvement and interest in robotics and robotics related class. This paper is also part of our campaign and encouragement for teachers and students to use low-cost and open source software since not all the universities in developing country can afford the expensive high-end software

Coordinated multi-robot formation control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

Navigation of Automatic Vehicle using AI Techniques

In the field of mobile robot navigation have been studied as important task for the new generation of mobile robot i.e. Corobot. For this mobile robot navigation has been viewed for unknown environment. We consider the 4-wheeled vehicle (Corobot) for Path Planning, an autonomous robot and an obstacle and collision avoidance to be used in sensor based robot. We propose that the predefined distance from the robot to target and make the robot follow the target at this distance and improve the trajectory tracking characteristics. The robot will then navigate among these obstacles without hitting them and reach the specified goal point. For these goal achieving we use different techniques radial basis function and back-propagation algorithm under the study of neural network. In this Corobot a robotic arm are assembled and the kinematic analyses of Corobot arm and help of Phidget Control Panel a wheeled to be moved in both forward and reverse direction by 2-motor controller have to be done. Under kinematic analysis propose the relationships between the positions and orientation of the links of a manipulator. In these studies an artificial techniques and their control strategy are shown with potential applications in the fields of industry, security, defense, investigation, and others. Here finally, the simulation result using the webot neural network has been done and this result is compared with experimental data for different training pattern