• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1960-1961
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• 2006

In this paper, The trajectory control of robot manipulator is proposed. It divides by trajectory planning and tracking control. A trajectory planning and tracking control of robot manipulator is used to the neural network and evolutionary algorithm. The trajectory planning provides not only the optimal trajectory for a given cost function through evolutionary algorithm but also the configurations of the robot manipulator along the trajectory by considering the robot dynamics. The computed torque method (C.T.M) using the model of the robot manipulators is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. The Radial Basis Function Networks(RBFN) is used not to learn the inverse dynamic model but to compensate the uncertainties of robot manipulator. The computer simulations show the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1271-1279
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• 2017

A highly accurate model-free controller is proposed for trajectory tracking control of robot manipulators. The proposed controller incorporates time-delay estimation (TDE) to estimate and cancel continuous nonlinearities of robot dynamics, and exploits fuzzy logic systems to suppress the effect of the TDE error, which is due to discontinuous nonlinearities such as friction. To this end, integral sliding mode is defined using desired error dynamics, and a Mamdani-type fuzzy inference system is constructed. As a result, the proposed controller achieves the desired error dynamics well. Implementation of the proposed controller is easy because the design of the controller is intuitive and straightforward, and calculations of the complex robot dynamics are not required. The tracking performance of the proposed controller is verified experimentally using a 3-degree of freedom PUMA-type robot manipulator.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.121-130
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• 2021

Foot bionic robot could be supported and towed through a series of discrete footholds and be adapted to rugged terrain through attitude adjustment. The vibration isolation of the robot could decouple the fuselage from foot-end trajectories, thus, the robot walked smoothly even if in a significant terrain. The gait programming and foot end trajectory algorithm were simulated. The quadruped robot of parallel five linkages with eight degrees of freedom were tested. The kinematics model of the robot was established by setting the corresponding coordinate system. The forward and inverse kinematics of both supporting and swinging legs were analyzed, and the angle function of single leg driving joint was obtained. The trajectory planning of both supporting and swinging phases was carried out, based on the control strategy of compound cycloid foot-end trajectory planning algorithm with zero impact. The single leg was simulated in Matlab with the established kinematic model. Finally, the walking mode of the robot was studied according to bionics principles. The diagonal gait was simulated and verified through the foot-end trajectory and the kinematics.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.107-110
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• 2001

Recently, there are lots of concerning on robot agent system working for itself with the trends of the research of bio-mimetic system and intelligent robot. In this paper, a virtual 3D interface system is proposed based on Internet for remote controlling and monitoring of mobile robot. The proposed system is constructed as manager-agent model. A worker can order the robot agent move to a new position by clicking the destination on virtual space of 3D graphic interface in manager. Then the robot agent move to the position automatically with avoiding collision by using range finding and autonomous control algorithm. The proposed robot agent system lets us control the mobile robot remotely located more conveniently.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.1
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• pp.8-17
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• 1988

This paper describes a robot simulator which enables a user to model a robot geometrically, and to evaluate performances of various robot control algorithms as well as to obtain physical understanding of robot and acruator dynamics. To achieve these goals, the kinematics and dynamics of a robot and interactive 3-D computer graphics which visulaize the motion of the robot were studied. The developed robot simulator consists of two parts:a dynamic simulator and a graphic simulator. To evaluate the robot simulator PUMA-560, Stanford arm, and RHINO robot were considered and a DG MV/10000 super mini-computer and an IBM-PC/XT personal computer were used.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.104-115
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• 2013

For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.

• The Journal of Korea Robotics Society
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• v.11 no.4
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• pp.226-234
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• 2016

In this study, a model-referenced underwater navigation algorithm is proposed for high-precise underwater navigation using monocular vision near underwater structures. The main idea of this navigation algorithm is that a 3D model-based pose estimation is combined with the inertial navigation using an extended Kalman filter (EKF). The spatial information obtained from the navigation algorithm is utilized for enabling the underwater robot to navigate near underwater structures whose geometric models are known a priori. For investigating the performance of the proposed approach the model-referenced navigation algorithm was applied to an underwater robot and a set of experiments was carried out in a water tank.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.158-167
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• 1994

The design concept of varaiable structure control is useful not only to stochasic systems but also to adaptive control systems. The Dynamic equation of vertical three linkage robot was derived. And it was simplyfied according to the scheme of control strategy. And we specify the form of model. Thereafter the error dynamic equation was derived between the real state of the plant and state of the model. Some simulations were performed to control robot manipulator applying the methodology of the variable structure model following adaptive control.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.429-434
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• 2013

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1771-1776
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• 2003

In mobile robot navigation, one of the key problems is the pose estimation of the mobile robot. Although the odometry can be used to describe the motions of the mobile robots quite simple and accurately, the validities of the models are limited by a number of error sources contaminating the encoder outputs so that applying the conventional extended Kalman filter to these nominal model does not yield the satisfactory performance. As a remedy for this problem, we consider the uncertain nonlinear kinematic model of the mobile robot that contains the norm bounded uncertainties and also propose a new robust extended Kalman filter based on the Krein space approach. The proposed robust filter has the same recursive structure as the conventional extended Kalman filter and can hence be readily designed to effectively account for the uncertainties. The computer simulations will be given to verify the robustness against the parameter variation as well as the reliable performance of the proposed robust filter.