Papers by Keyword: Mobile Robotics

Abstract: River Formation Dynamics is a heuristic optimization algorithm based on the manner, in which drops of water form the river bed. The idea is to imitate the movement of drops on the edges between given nodes thus performing a search based on their height, which is modified through the mechanism of soil erosion and sediment deposition. In this way decreasing gradients are constructed, and these are followed by subsequent drops to compose new gradients and reinforce the best ones. This paper presents implementation of the method in wheeled mobile robot path searching task in an environment with obstacles. At first, a concise introduction to the RFD algorithm is presented, along with the problems requirements. In the main part a simulation test has been performed using the algorithm to find the shortest route from the starting point to the goal. The tests were made with different landscape layouts, measuring the computation time. The last section presents a real life implementation of the algorithm using a Pioneer P3-DX mobile robot. The validity of this solution is discussed, as well as any modifications, along with a brief comparison with a similar, popular search path algorithm.

Abstract: In the paper the behavior based control system of an autonomous mobile robot SCORPION is presented to execute the one of the most difficult navigation task, which is the complete coverage task of unknown area with static obstacles in the environment. The main principle assumed to design control system was that the robot should cover all area only once, if it possible, to optimize the length of path and energy consumption. All commercial robots like Roomba, Trilobite or IVO move using structured templates combined with random movement. Therefore the path of coverage is not optimal directions of movement are often chosen randomly, so robot covers the same area many times wasting time and energy. In paper the five main developed templates of movement were described to fulfill main task in ordered manner using primarily the way of the ox template of coverage [1, 2, 5, 1. The behavioral control system is implemented in a computer application written in Python [5]. In the paper the test methodology of the developed system on real mobile robot ERSP SCORPION equipped with IR sensors is presented. Graphical and quantitative results of tests of accomplishment of complete coverage task are given for 6 different configurations of obstacles in the robots environment. Conclusions are presented and discussed [5]. Ways to improve the quality indicators [1, of the task of complete coverage of a unknown area are also showed.

Abstract: Designing a visual tracking system to pick-and-place an object is a complex task because a large amount of video data must be transmitted and processed in real time. In this work, a mobile robot visual control system is proposed which uses a stereo vision to acquire the 3D positions of a target color ball and to control an end-effector to pick the ball up and place it in the specified location. This mobile robotic system is based on the Open Source Computer Vision Library for programming framework with portable components, off-the-shelf commercial hardware, and minimal programming. Two calibrated web cameras are used to track the color ball and a 2-axis end-effector is controlled to pick up the tracked color ball. The visual tracking and servo system as designed in this work is less sensitive to lighting influences and thus performs more efficiently. Experimental results show that the open platform based robot vision system successfully finishes the pick-and-place task and could be scalable to many diverse areas of robotics research

Abstract: In paper the methodology of complete coverage of unknown area by autonomous mobile robot is described. The main principles of complete coverage task using sensory data only are given. The shape of coverage area is defined. The modified "the way of the ox" algorithm is proposed to realize this task and its following stages are described. Definitions of two quality indicators of realization of complete coverage task are given. The behaviour based control methodology imitated reactions of animals, realized the robot's movement, is presented. The general structure of reactive and proactive behaviours is showed. The example structures of defined reactive and proactive beheaviours, which allow to achive given task, are described. The example structure of complex behaviour implemented in Matlab-Simulink environment is presented. Graphical results of simulations of complete coverage task are presented. Values of quality indicators D and E are given and discussed.