The paper exploits advantages of the genetic algorithm and fuzzy logic in identification and control of 2DOF nonlinear helicopter model. The genetic algorithm is proposed for identification of the helicopter system, which contains a helicopter body, main and tail motors and drivers. The quality of helicopter model achieved was validated through simulation and experimental modes. Then, this model is used to design of elevation and azimuth Mamdani type fuzzy controllers. The main objective of the paper is to obtain robust and stable controls for wide range of azimuth and elevation angles changing during the long time flight. The robustness and effectiveness of both fuzzy controllers were verified through both simulations and experiments. Also, a comparative analysis of proposed fuzzy and traditional PID controllers is performed.

After recording data sets using a 3D laser scanner, the logical step would be to reconstruct 3D model from given points. This paper proposes one solution to the reconstruction of 3D model. It combines splatting methods with polygonalization to achieve most accurate 3D model of an indoor mobile robot environment with fast execution and rendering time. The main objective of the work, which was done as a part of ThermalMapper project, was to generate an accurate mesh of the indoor environment based on laser scans with added temperature scalars acquired by 6D SLAM method. This is useful for generating meshes of museums, buildings, tunnels, etc. which can be used for inspection and different analyses. A series of experiments demonstrate the usefulness and effectiveness of the proposed 3D surface reconstruction methods.

This paper proposes an approach of digital controller design on microcontrollers based on control surface disretization. As experimental setup a simple system composed of a DC motor, the PWM drive and a encoder was built. Identification of this simple system was done using the first order linear model and the Hammerstein-Wiener model. The quality of these models was compared based on the fitness function and their ability to cope with system nonlinearities. A discrete PI speed controller was designed based on the Hammerstein-Wiener model and tuned by the Gauss-Newton optimization algorithm. The Fuzzy logic controller was designed on the basis of the PI controller behaviour with genetic algorithm parameter tuning. The control surface of the Fuzzy logic controller was discretized for microcontroller implementation. Both controllers were implemented on the Arduino Mega platform and their control performances were tested and compared.

This paper proposes a new algorithm for following a mobile robot target in an outdoor environment. This approach combines a fuzzy tracking control law and an inverse matching based algorithm for finding and following of the moving target. The inverse matching algorithm comprises local maps of a robot environment to identify the target and generate desire path toward it. The localization of the mobile robot is done by the triangulation method based on GPS measurements. In addition, previously developed software system for the mobile robot enables GPS guidance and obstacle avoidance which makes it suitable for creation of mobile convoys. Finally, the experimental verification is performed to confirm the effectiveness and practical value of the proposed approach.

In this paper we introduce a modification of histogramic in - motion mapping technique for mobile robots. This modification is based on the premise that precise sonar model is not required for accurate map building. We use uniform random distribution approach to replace the probabilistic model of sonar sensor. Problem of localization of the mobile robot is also discussed as it is very important for the precise mapping of the environment. For this purpose we used odometry measurements processed by Extended Kalman Filter for the robot localization. It is shown that this method gives precise maps of an environment in Player/Stage simulator, and also with real world scenarios.

Abstract Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency of the Commission of the European Communities (2008) estimates that the largest cost-effective energy savings potential lies in residential (≈ 27%) and commercial (≈ 30%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This paper presents our overall approach to map indoor environments with thermal data in 3D.

Abstract In the process of reconstructing the 3D environment from the point cloud acquired from 3D laser the main objective is to obtain the model that is as precise as possible. Reconstruction algorithms greatly rely on the input data precision. Unfortunately, the point clouds regularly contains points that are problematic for the reconstruction. They are mostly associated with the reflection of laser beams off the semi–transparent surfaces, e.g. windows. This paper proposes the method for eliminating such points based on K–means clustering in order to increase the accuracy of the reconstructed 3D model.

This work considers the whole process of making a path finding simulator for Pioneer 3DX mobile robot. This simulator needs to be provided implementation of various optimal path finding algorithms and make their comparisons. For this purpose a software solution (GUI in Matlab) has been designed and tested. The simulator allows selecting mazes, different starting and finishing nodes and algorithms. Five different algorithms were used to determine the shortest path between nodes for a mobile robot within various mazes: Breadth-first search, Depth-first search, Bellman-Ford algorithm, Dijkstra's algorithm and A∗ algorithm. The main objective of this paper was to obtain fully and precise information on routing and finding the shortest path between two nodes within a maze for the mobile robot. Validity and effectiveness of the used algorithms were verified through both simulations and experiments.

Different methods for position control of a DC servomotor are examined. Position is measured with a low-resolution incremental encoder that is a cheap solution that allows for free movement of motor shaft. This kind of measurement affects control and degrades its performance. Entire system is first identified using Matlab System Identification Toolbox. P and PD controllers, along with cascaded and observer-based controllers are synthesised and tested. Sugeno type fuzzy controller with two inputs and constant output membership functions shows the best results of the tested controllers in both simulation and testing done on a real system. Simulation is performed with Matlab Simulink. Control system prototyping is done using DS1104 board.

In this paper both hardware and software systems for GPRS communication and GPS navigation are developed. The hardware structure of GPS navigation module was build using Cinterion XT65 platform and appropriate electronic components. The overall navigation system is client-server based that uses GPS and GPRS communications. The GPS communication is used between client (mobile robot) and satellites, while GPRS communication connects server (PC) and client. The algorithm for mobile robot position estimation exploits a triangulation technique. Multiple algorithms (including a fuzzy regulator) for avoiding obstacles are implemented in order to provide safe and precise movement towards the destination point given to robot. The effectiveness and quality of proposed hardware and software structures are verified by experiments.

This paper deals with a design and implementation of a remote position control system for a mobile robot. The system is composed of the mobile robot (controlled object), PC as positioning controller, camera as sensor and ZigBee based wireless communication device. The camera captures images of the mobile robot. Developed image processing algorithms (Matlab platform) determine the robot's position and orientation. Based on this data the implemented system controls the robot's position. Control signals are sent via modules for wireless communication. The whole control system is realized and experimental results have been obtained. The experimental results confirm the robustness and effectiveness of the proposed control system.

This paper presents the control of induction motor via PROFINET network including a remote control using the OPC (OLE for Process Control) standard. This system is composed of induction motor, encoder, frequency converter, PLC (Programmable Logic Controller) and two PCs (server and client). The motor control is PLC based with PID (Proportional-Integral-Derivative) controller, while PCs are used as HMI (Human Machine Interface) devices for controlling and supervising the plant. PC which represents OPC server is connected with PLC via Ethernet network, while connection between frequency converter and PLC is established via PROFIBUS DP protocol. Two PCs are connected using OPC standard, where physical connection between them is achieved using LAN (Local Area Network). The obtained experimental results demonstrate a possibility to establish local and remote control over our system while ensuring system's stability and efficiency.

This paper proposes an algorithm for finding the optimal trajectory on a set of admissible paths based on the task tree approach. The space solution represents two-dimensional plane. A classical approach is based on Dubin's work that gives sufficient family of trajectories. Those trajectories satisfy the Pontryagin's Maximum Principle which generalize Lagrange's problem of the calculus of variation. Our paper demonstrates how to calculate feasible trajectories for finding the minimum length path. For this purpose a lot of computer resource is needed. It requires a very efficient algorithm for selection of the optimal trajectory based on logic reasoning. The software support for the proposed approach is designed on intuitive and effective way and it can be used for the time critical operations.