Sun-Gi Hong

Designing a robust adaptive dynamic controller for nonholonomic mobile robots under modeling uncertainty and disturbances

Abstract The main stream of researches on the mobile robot is planning motions of the mobile robot under nonholonomic constraints. Much has been written about the problem of motion planning under nonholonomic constraints using only a kinematic model of a mobile robot. Those methods, however, assume that there is some kind of a dynamic controller that can produce perfectly the same velocity that is necessary for the kinematic controller. Also there is little literature on the robustness of the controller when there are uncertainties or external disturbances in the dynamical model of a mobile robot. In this paper, we proposed a robust adaptive controller that can achieve perfect velocity tracking while considering not only a kinematic model but also a dynamic model of the mobile robot. The proposed controller can overcome uncertainties and external disturbances by robust adaptive technique. The stability of the dynamic system will be shown through the Lyapunov method.

Generating artificial force for feedback control of teleoperated mobile robots

One of the most important issues in the teleoperation is to provide the sense of telepresence so as to conduct the task more reliably. In particular, teleoperated mobile robots need to have some kind of backup system when the operator is blind to the remote situation owing to failure of the vision system. In Hong S-G et al. (see Mechatronics), the idea of artificial force reflection was proposed to enhance the reliability of operation when the mobile robot travels over plain ground. We extend these results to help the teleoperator even when the robot climbs stairs. The extended artificial force reflection method has two modes: traveling on plain ground and climbing stairs. When traveling over plain ground, the force information is artificially generated using range data from the environment while generating the impulse force when climbing stairs. To verify the validity of our algorithm, we develop a simulator which consists of a joystick and visual display system. Through experiments using this system, we confirm the validity and effectiveness of our new artificial force reflection in teleoperated mobile robots.

Dynamical path-planning algorithm of a mobile robot using chaotic neuron model

This paper describes a dynamical local path-planning algorithm of an autonomous mobile robot available for stationary obstacle avoidance using nonlinear friction. Dynamical path-planning algorithm is considered to accommodate the mobile robot to the dynamic situation of the path-planning nature. Together with the previous virtual force field method, the path of the mobile robot is a solution of a path-planning equation. Local minima problems in stationary environments are solved by introducing nonlinear friction into the chaotic neuron. Because of the nonlinear friction, the proposed path-planner reveals chaotic dynamics in some parameter regions. This new path-planner is feasible to guide, in real-time, the mobile robot to avoid stationary obstacles and to reach the goal. Computer simulations are presented to show the effectiveness of the proposed algorithm.

Evolutionary design of fuzzy system for various problems including vision based mobile robot control

In this paper, a new evolutionary scheme for designing fuzzy logic system is proposed. We have developed a new fitness function for optimizing membership functions of antecedent parts of FLS. The proposed fitness function considers not only mean squared error, but also calculates some penalty based on the overlapping degree of adjacent membership functions for the same input. Consequent parts of the FLS are calculated using pseudo-inverse method. To show the effectiveness of the proposed algorithm, we have applied the proposed algorithm to various problems: Iris classification problem, Mackay-Glass time-series prediction problem and vision-based mobile robot control problem. It has been proven that, without much modification, the proposed algorithm can be used in various problem fields efficiently.

Developing Soccer-Playing Robots Based on the Centralized Approach

ABSTRACTThis paper presents the design procedure for soccer-playing robots based on the centralized approach. Using a fast vision system, we obtain the configuration of each robot, then the host computer computes the desired motion and commands each robot directly via RF communication. The robot soccer game has a lot of challenging problems such as coordination between robots, motion planning of robots, visual recognition of objects, and so on. To implement such functions, we think that the centralized approach may be more powerful than the distributed approach. We describe the technical tips for developing the robots in detail here and explain our strategy for getting the scores.

Information processing using chaos with application to mobile robot navigation problems

Throughout this study on information processing using an artificial neural network (ANN) and chaos we are attempting to devise a memory model that resembles human behavioral characteristics. For that purpose we construct a framework of the macroscopic model of the responding process in biological systems. Incoming stimuli are applied to the sensory receptors and preprocessed. A pattern-matching block allows one of the chaotic memories to find a feasible response in an associative way. After the chaotic memory is stabilized on one of the stable equilibrium points or limit cycles, its performance is evaluated. Since chaotic memory and the performance evaluation block form a feedback loop, they can handle features of the information blocks and store newly updated information blocks. Two kinds of chaotic memories are established in this paper: one is a 1-D map in which many information blocks can be stored as unstable periodic orbits, and the other is the famous Lozi attractor with rich dynamics. Simulations are performed for the mobile robot navigation problem in each case.