• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.26-34
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• 2015

In this paper, a fuzzy compensated PID control system is proposed for formation control of mobile robots. The control system consists of a kinematic controller based on the leader-follower approach and a dynamic controller to handle dynamics effects of mobile robots. To maintain the desired formation of mobile robots, the dynamic controller is equipped with a PID controller; however, the PID controller has poor performance in nonlinear and changing environments. In order to improve these problem, we applied the additional fuzzy compensator. Finally, the proposed control system has been evaluated through computer simulation to demonstrate the improved results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.449-452
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• 1996

In this paper, a robust.adaptive control scheme is presented for precise trajectory tracking of nonholonomic mobile robots. In the controller, a set of desired trajectory is defined and used in constructing the control input which constitutes the main part of the proposed controller. The stable operating characteristics such as precise trajectory tracking, parameter estimation, disturbance suppression, tec., are shown through experiments as well as computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1177-1180
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• 1996

In this paper, we propose an algorithm that realizes cooperative behavior by construction of autonomous mobile robot system. Each robot is able to sense other robots and obstacles, and it has the rule of behavior to achieve the goal of the system. In this paper, to improve performance of the whole system, we use Genetic Programming based on Natural Selection. Genetic Programming's chromosome is a program of tree structure and it's major operators are crossover and mutation. We verify the effectiveness of the proposed scheme from the several examples.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.183-190
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• 2022

Accurate kinematic parameters of mobile robots are essential because inaccurate kinematic model produces considerable uncertainties on its odometry and control. Especially, kinematic parameters of caster type mobile robots are important due to their complex kinematic model. Despite the importance of accurate kinematic parameters for caster type mobile robots, few research dealt with the calibration of the kinematic model. Previous study proposed a calibration method that can only calibrate double-wheeled caster type mobile robot and requires direct-measuring of robot center point and distance between casters. This paper proposes a calibration method based on geometric approach that can calibrate single-wheeled caster type mobile robot with two or more casters, does not require direct-measuring, and can successfully acquire all kinematic parameters required for control and odometry. Simulation and hardware experiments conducted in this paper validates the proposed calibration method and shows its performance.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.104.3-104
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• 2001

This paper develops a control approach to generic formation tasks of multiple mobile robots with inaccurate sensor information. Inaccurate sensor information means that all the robots have only local sensors which cannot accurately measure absolute distances and directions of objects. The control logic is developed considering generic situations in order to adapt to increasing number of robots which participate in the formation. Petri nets are used for modeling and design of the control logic, which can visualize the control models and make it easy to check the states of each robot. Physically homogenous mobile robots are designed and built to evaluate the developed logic. Each robot is equipped with eighteen infrared sensors and a UHF transceiver module. The developed control ...

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.389-397
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• 2011

The global dynamic window approach (DWA) is widely used to generate the shortest path of mobile robots considering obstacles and kinematic constraints. However, the dynamic constraints of robots should be considered to generate the minimum-time path. We propose a modified global DWA considering the dynamic constraints of robots. The reference path is generated using A* algorithm and smoothed by cardinal spline function. The trajectory is then generated to follows the reference path in the minimum time considering the robot dynamics. Finally, the local path is generated using the dynamic window which includes additional terms of speed and orientation. Simulation and experimental results are presented to verify the performance of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.114-120
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• 2017

The work present in this paper deals with a navigation problem for multiple mobile robots in unknown indoor environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. The environments simulated in this work are dynamic ones which contain not only static but also moving obstacles. In order to guide the robot to move along a collision-free path and reach the goal, this paper presented a navigation method based on fuzzy approach. Then genetic algorithms were applied to optimize the membership functions and rules of the fuzzy controller. The simulation results verified that the proposed method effectively addresses the mobile robot navigation problem.

• Advances in robotics research
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• v.1 no.1
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• pp.41-59
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• 2014

This paper deals with the problem of steering a group of mobile robots along a reference path while maintaining a desired geometric formation. To solve this problem, the overall formation is decomposed into numerous geometric patterns composed of pairs of robots, and the state of the geometric patterns is defined. A control algorithm for the problem is proposed based on the Nash equilibrium strategies incorporating receding horizon control (RHC), also known as model predictive control (MPC). Each robot calculates a control input over a finite prediction horizon and transmits this control input to its neighbor. Considering the motion of the other robots in the prediction horizon, each robot calculates the optimal control strategy to achieve its goals: tracking a reference path and maintaining a desired formation. The performance of the proposed algorithm is validated using numerical simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.819-824
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• 1997

This paper presents a cell-based motion control strategy for soccer playing mobile robots. In the central robot motion planner, the planar ground is divided into rectangular cells with variable sizes and motion indices to which direction the mobile robot should move. At every time the multiple objects-the goal gate, ball, and robots-detected, integer values of motion indices are assigned to the cells occupied by mobile robots. Once the indices being calculated, the most desirable state-action pair is chosen from the state and action sets to achieve successful soccer game strategy. The proposed strategy is computationally simple enough to be used for fast robotic soccer system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.818-829
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• 2003

A cooperating control algorithm for two nonholonomic mobile robots is proposed. The task is composed of collision avoidance against obstacles and carrying a ladder. The front robot and the rear robot are called the leader and the follower, respectively. Each robot has a nonholonomic constraint so it cannot move in perpendicular directions. The environment is initially supposed to be unknown except target position. The torque that drives leader is determined by distance between the leader and the target position or the distance between it and the obstacles. The torque by target is attractive and the torque by obstacles is repulsive. The two mobile robots are supposed to be connected by link that can be expanded and contracted. The follower computes its torque using position and orientation information from the leader by communication. Simulation results show that the robots can drive to target position without colliding into the obstacles and maintain the distance in the allowable range.