• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.948-951
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• 1996

High-speed/high-accuracy control of robot manipulator becomes more and more stringent because of the external disturbance and nonlinear characteristics. To meet this ends, lots of control strategies were proposed in the past such as the computed torque control, the nonlinear decoupled feedback control, and adaptive control. These control methods need computations of the inverse dynamics and require much computational effort. Recently, a disturbance observer with unmodeled robot dynamics and simple algorithms to motion control have been widely studied. This paper proposes a motor control strategy based on the disturbance observer which estimate the disturbance of each joint from input-output relationship of the actuator and eliminate the estimated disturbance including the torque due to modeling errors, coupling force, nonlinear friction, and so on. To apply the disturbance observer to closedloop system like velocity servo pack, the modified control structure was constructed and shown that it is equivalent to a disturbance observer in open-loop system. Finally, using the proposed approach, simulation and experiments were carried out for a two-degree-of-freedom SCARA type direct drive robot, and show some results to verify the effectiveness of the proposed algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1161-1164
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• 1996

In this paper, a parameter optimization technique for a mobile robot navigation is discussed. Authors already have proposed a navigation algorithm for mobile robots with sonar sensors using fuzzy decision making theory. Fuzzy decision making selects the optimal via-point utilizing membership values of each via-point candidate for fuzzy navigation goals. However, to make a robot successfully navigate through an unknown and cluttered environment, one needs to adjust parameters of membership function, thus changing shape of MF, for each fuzzy goal. Furthermore, the change in robot configuration, like change in sensor arrangement or sensing range, invokes another adjusting of MFs. To accomplish an intelligent way to adjust these parameters, we adopted a genetic algorithm, which does not require any formulation of the problem, thus more appropriate for robot navigation. Genetic algorithm generates the fittest parameter set through crossover and mutation operation of its string representation. The fitness of a parameter set is assigned after a simulation run according to its time of travel, accumulated heading angle change and collision. A series of simulations for several different environments is carried out to verify the proposed method. The results show the optimal parameters can be acquired with this method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.250-255
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• 2005

For navigation of a service robot, mapping and localization are very important. To estimate the robot pose, the map of the environment is required and it can be built by exploration or SLAM. Exploration is the fundamental task of guiding a robot autonomously during mapping such that it covers the entire environment with its sensors. In this paper, an efficient exploration scheme based on the position probability of the end nodes of a topological map is proposed. In this scheme, a topological map is constructed in real time using the thinning-based approach. The robot then updates the position probability of each end node maintaining its position at the current location based on the Bayesian update rule using the range data. From this probability, the robot can determine whether or not it needs to visit the specific end node to examine the environment around this node. Various experiments show that the proposed exploration scheme can perform exploration more efficiently than other schemes in that, in most cases, exploration for the entire environment can be completed without directly visiting everywhere in the environment.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1039-1043
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• 2005

Despite the many significant advances made in robot architecture, the basic approaches are deliberative and reactive methods. They are quite different in recognizing outer environment and inner operating mechanism. For this reason, they have almost opposite characteristics. Later, researchers integrate these two approaches into hybrid architecture. In such architecture, Reactive module also called low-level motion control module have advantage in real-time reacting and sensing outer environment; Deliberative module also called high-level task planning module is good at planning task using world knowledge, reasoning and intelligent computing. This paper presents a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provide real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework is verified by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1054-1059
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• 2005

The artificial potential method uses a potential field to guide a robot from a start to a goal configuration respectively. The potential field consists of attractive potential used to pull a robot toward a goal and repulsive potential to keep it away from obstacles. However, there are two problems concerning local minimum and computational cost to be resolved in conventional artificial potential methods. This study proposes a method utilizing a spline surface that interpolates arbitrary boundaries and a domain reduction method that reduces the unnecessary area. The proposed spline surface interpolates arbitrary shaped boundaries and is used as an artificial potential to guide a robot for global motion planning of a mobile robot. A reduced domain process reduces the unnecessary domain. We apply a distance-weighted function as such a function, which blends distances from each boundary with a reduction in computational time compared with other analytical methods. As a result, this paper shows that an arbitrary boundary spline surface provides global planning and a domain reduction method reduces local minimum with quick operation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2237-2242
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• 2005

The original RRT is iteratively expanded by applying control inputs that drive the system slightly toward randomly-selected states, as opposed to requiring point-to-point convergence, as in the probabilistic roadmap approach. It is generally known that the performance of RRTs can be improved depending on the selection of the metrics in choosing the nearest vertex and bias techniques in choosing random states. We designed a path planning algorithm based on the RRT method for a remote-controlled mobile robot. First, we considered a bias technique that is goal-biased Gaussian random distribution along the command directions. Secondly, we selected the metric based on a weighted Euclidean distance of random states and a weighted distance from the goal region. It can save the effort to explore the unnecessary regions and help the mobile robot to find a feasible trajectory as fast as possible. Finally, the constraints of the actuator should be considered to apply the algorithm to physical mobile robots, so we select control inputs distributed with commanded inputs and constrained by the maximum rate of input change instead of random inputs. Simulation results demonstrate that the proposed algorithm is significantly more efficient for planning than a basic RRT planner. It reduces the computational time needed to find a feasible trajectory and can be practically implemented in a remote-controlled mobile robot.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.213-221
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• 2017

Utilizing the existing polishing robot prevents unrestricted change of direction, driving, and identification of driving pathway. To overcome this barrier, driving mechaism has been designed with Omniwheels with encoders and RSSI method of beacon system has been utilized to identify the driving path by position recognition. Due to the wheel characteristics, the Omniwheel mobile robot generates greater slip than the conventional mobile robot, which reduces its driving accuracy. Therefore, to improve the driving accuracy, the localization is conducted through the fusion of encoder and RSSI of beacon data to compensate for the errors caused by Dead Reckoning and inaccuracy of sensors. Finally, the localization accuracies of the proposed and conventional indoor localization method are compared to show effectiveness of the proposed driving control for a polishing robot.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.464-467
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• 1995

Autonomous Mobile Robot(AMR) is a field of study which is under active research along with rapid development of the engineering technology. The main reasons for the high interest in AMR are because of its ability to change work space freely and its capability to replace human being for difficult and dangerous jobs. Also the fact that AMR provides a variety of research fields, such as path planning, navigation algorithm, sensor fusion, image processing, and controller design is part of the reason for its popularity. But relatively few researches are concerned with controller. So in this paper, a control strategy of mobile robot with nonholonomic constraint for tracking ordered discontinuous motion is proposed. The proposed control strategy has been designed as a state feedback shape to allow the AMR to obtain continuous velocity and track the path which is composed of discontinuous motions. In order to design such controller, 3 states have been reduced to 2 states through coordinate projection. These ideas are tested for validity through simulation and simulation result is compared with experiments result.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.35-40
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• 2011

In this paper, an auto recharging system for a mobile robot based on the wireless power transmission and visual information is proposed. The existing recharging systems for mobile robot use mechanical contact while wireless power transmission transfers energy by electromagnetic induction method without contacts. For efficiency of charging, alignment of coils is important. In order to solve this problem, with the visual image, ellipticity of coil circle is recognized to control the pose of mobile robot.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.2
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• pp.271-280
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• 2011

This paper presents a navigation system based on the tactical communication and vision system in outdoor environments which is applied to unmanned robot for perimeter surveillance operations. GPS errors of robot are compensated by the reference station of C2(command and control) vehicle and WiBro(Wireless Broadband) is used for the communication between two systems. In the outdoor environments, GPS signals can be easily blocked due to trees and buildings. In this environments, however, vision system is very efficient because there are many features. With the feature MAP around the operation environments, the robot can estimate the position by the image matching and pose estimation. In the navigation system, thus, operation modes is switched by navigation manager according to some environment conditions. The experimental results show that the unmanned robot can estimate the position very accurately in outdoor environment.