Optimization of the PID coefficients for the line-follower mobile robot controller employing genetic algorithm

O b j e c t i v e s. To develop a control system for the movement of a mobile robot along a color-contrast line, as well as to find the values of the coefficients of a proportional-integral-differentiating (PID) controller that allows the robot to move along the line at a given speed.M e t ho d s. To adjust the values of the coefficients of the PID controller, methods of enumeration, automatic tuning and a genetic algorithm are used.Re s u l t s. A software package for tuning the PID controller of the educational mobile robot RoboCake, designed to move along a closed color-contrast line at a given speed, has been developed. The software package consists of a simulation model of the specified robot in the Simulink environment, several virtual traces-polygons and a specialized solver based on the developed genetic algorithm. With the help of the proposed fitness function, a mobile robot control system that satisfies the stated conditions is implemented. Based on the conducted model experiments, the desired values of the parameters of the PID controller are obtained.Co n c l u s i o n. A comparison of the effectiveness of various methods of tuning the PID controller is carried out. The developed software package is designed to solve the practical problem of moving a mobile robot along a color-contrast line at a speed of 1 m/s. The results obtained can be used to study methods of evolutionary tuning of stabilization systems for transport robots, ensuring their movement without overshoot.

Approximation Possibilities of Fuzzy Control Surfaces for Purpose of Implementation into Microcontrollers

The main contribution of the paper is the simplification of the computational process of fuzzy control of a mobile robot controlled by a microcontroller. We present a way to implement this control method with a reduced computation time of control actions and memory demand. Our way to accomplish this, was to replace the fuzzy controller with the approximation of its resulting control surfaces. In the paper, we use the previously presented approximation by the table and describe other methods of approximation of the control area through polynomial and exponential function. We tested all approximation methods in simulations and with a real mobile robot. Based on the measured trajectory of the EN20 mobile robot, we found that approximation through the table is the most accurate in terms of the fuzzy surface but delivers noticeable oscillations of mobile robot control in real conditions. Polynomial and exponential functions fuzzy surface approximations were less accurate than the table, but provide smoother control based on robot trajectories and are much more appropriate in terms of microcontroller implementation due to lower demand on memory.

3D Environment Exploration with SLAM for Autonomous Mobile Robot Control

In the paper a solution for building of 3D map of unknown terrain for the purposes of control of wheeled autonomous mobile robots operating in an isolated and hard-access area is described. The work environment is represented by a three-dimensional occupancy grid map built with SLAM techniques using LIDAR sensor system. Probabilistic methods such as adaptive Monte Carlo localization and extended Kalman filter are used to concurrently build a map of surroundings and a robot’s pose estimation. A robot’s displacement and orientation are obtained from odometry and inertial navigation system. All algorithms and sub-systems have been implemented and verified with Robot Operation System with a framework for exploration tasks in multi-level buildings

Android Application Design with MIT App Inventor for Bluetooth Based Mobile Robot Control

In this study, a Bluetooth-based Android application interface is developed to perform a manual and automatic control of a four-wheel-driven mobile robot designed for education, research, health, military, and many other fields. The proposed application with MIT App Inventor consists of three components: the main screen, the manual control screen, and the automatic control screen. The main screen is where the actions of the control preference selection such as manual control and automatic control and the Bluetooth connection between the mobile robot and Android phone occur. When the robot is operated manually for calibration or manual positioning purposes, the manual control screen is employed to adjust the desired robot movement and speed by hand. In the case of the need for automatic motion control, the desired robot position and speed data are inserted into the mobile robot processor through the automatic control screen. At the first stage of the work, the proposed Android application is developed with the design and block editors of the MIT App Inventor. The compiled application is then installed on the Android phone. Next, the communication between the Arduino microcontroller used for the robot control with the Bluetooth protocol and the Android application is established. The accuracy of the data dispatched to the Arduino is tested on the serial connection screen. It is validated that the data from the Android application is transferred to Arduino smoothly. At the end of this study, the manual and automatic controls of the proposed mobile robot are performed experimentally and success of the coordination between the Android application and the mobile robot are demonstrated.

Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

This paper describes and illustrates the optimization of a safe mobile robot control process in collision situations using the model of a multistep matrix game of many participants in the form of a dual linear programming problem. The synthesis of non-cooperative and cooperative game control software was performed in Matlab/Simulink software to determine the safe path of the robot when passing a greater number of other robots and obstacles. The operation of the game motion control algorithm of a mobile robot is illustrated by computer simulations made in the Matlab/Simulink program of two real previously recorded navigation situations while passing dozens of other autonomous mobile robots.