• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.698-707
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• 2017

This paper deals with predictive control methods of mobile robots for reference trajectory tracking control. Predictive control methods using predictive model are known as effective schemes that minimize the future errors between the reference trajectories and system states; however, the amount of real-time computation for the predictive control are huge so that their applications were limited to slow dynamic systems such as chemical processing plants. Lately with high computing power due to advanced computer technologies, the predictive control methods have been applied to fast systems such as mobile robots. These predictive controllers have some control parameters related to control performance. But these parameters have not been optimized. In this paper we employed the genetic algorithm to optimize the control parameters of the predictive controller for mobile robots. The improved performances of the proposed control method are demonstrated by the computer simulation studies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.551-554
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• 2001

A necessity of remote control robots or various searching robots etc. that accomplish works given instead of human under long distance and extreme environment such as volcano, universe, deep-sea exploration and nuclear power plant etc. is increasing, and so the development and the research regarding these mobile robots are actively progressing. The wheel mobile robot or the track mobile robot have a sufficient energy efficiency under this en, but also have a lot of limits to accomplish works given which are caused from the restriction of mobile ability. Therefore, recently many researches for the walking robot with superior mobility and energy efficiency on the terrain, which is uneven or where obstacles, inclination and stairways exist, have been doing. The research for these walking robots is separated into fields of mechanism and control system, gait research, circumference environment and system condition recognition etc. greatly. It is a research field that the gait research among these is the centralist in actual implementation of walking robot unlike different mobile robots. A research field for gait of walking robot is classified into two parts according to the nature of the stability and the walking speed, static gait or dynamic gait. While the speed of a static gait is lower than that of a dynamic gait, a static gait which moves the robot to maintain a static stability guarantees a superior stability relatively. A dynamic gait, which make the robot walk controlling the instability caused by the gravity during the two leg supporting period and so maintaining the stability of the robot body spontaneously, is suitable for high speed walking but has a relatively low stability and a difficulty in implementation compared with a static gait. The quadruped walking robot has a strong point that can embody these gaits together. In this research, we will develope an autonomous quadruped robot with an asaptibility to the environment by selectry appropriate gait, element such as duty factor, stride, trajectory, etc.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.4
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• pp.167-174
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• 2018

Presently, the exploration of an unknown environment is an important task for the development of mobile robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems, In mobile robotics, multi-sensor data fusion(MSDF) became useful method for navigation and collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within indoor environments. Simulation results with a mobile robot will demonstrate the effectiveness of the discussed methods.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.12
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• pp.1321-1330
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• 2012

This paper describes an advanced formation algorithm of clustered multiple robots for their navigation using flexible formation method for collision avoidance under static environment like narrow corridors. A group of clustered multiple robots finds the lowest path cost for navigation by changing its formation. The suggested flexible method of formation transforms the basic group of mobile robots into specific form when it is confronted by particular geographic feature. In addition, the proposed method suggests to choose a leader robot of the group for the obstacle avoidance and path planning. Firstly, the group of robots forms basic shapes such as triangle, square, pentagon and etc. depending on number of robots. Secondly, the closest to the target location robot is chosen as a leader robot. The chosen leader robot uses $A^*$ for reaching the goal location. The proposed approach improves autonomous formation characteristics and performance of all system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.305-314
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• 2015

The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots' bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors' data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the "infinite repetition" or "dead cycle" situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.237-246
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• 2011

Robots have been used in many fields due to its performance improvement and variety of its functionality, to the extent which robots can replace human tasks. Individual feature and better performance of robots are expected and required to be created. As their performances and functions have increased, systems have gotten more complicated. Multi mobile robots can perform complex tasks with simple robot system and algorithm. But multi mobile robots face much more complex driving problem than singular driving. To solve the problem, in this study, driving algorithm based on the energy method is applied to the individual robot in a group. This makes a cluster be in a formation automatically and suggests a cluster the automatic driving method so that they stably arrive at the target. The energy method mentioned above is applying attractive force and repulsive force to a special target, other robots or obstacles. This creates the potential energy, and the robot is controlled to drive in the direction of decreasing energy, which basically satisfies lyapunov function. Through this method, a cluster robot is able to create a formation and stably arrives at its target.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.532-535
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• 1997

This paper describes the design of a fuzzy-logic controller for a differential-drive mobile robots. This controller uses absolute position information to modify control parameters to compensate the orientation error. CC-Control method is compensated for the internal error by wheel encoders and the fuzzy-logic control provides compensation for external errors. The validities of the proposed scheme is evaluated using simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.530-542
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• 2005

We proposed a robust localization algorithm for mobile robots using LRF. A novel cost function for localization is suggested, which was used for calculating correct rotation angle and translation vector. We examined validity of our algorithm with various simulations and experiments, and also revealed robustness and accuracy compared to previous localization algorithms.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.106-108
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• 2009

In this paper, we handle automatic estimation of mechanical parameters for mobile robots. Most estimation methods are based on the sequence and move-measurement-estimation. Estimated accuracy is largely dependent on the paths. Mathematical conditions minimizing estimation errors are derived, and then a method finding optimal paths for mechanical parameters estimation is proposed.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1829-1830
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• 2008

The paper deals with leader-follower formations of nonholonomic mobile robots using least square method in order to maintain the formation constantly. The nonholonomic property of the mobile robot cause us to use the least square method. Then, the performance of the developed formation controller is verified by simulation results.