• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.78-84
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• 2004

To optimize movement of a multi-joint robot arm is known to be a difficult problem, because it is a kind of redundant system. Although the end-effector is set its position by each angle of the joints, the angle of each joint cannot be uniquely determined by the position of the end-effector. There exist the infinite number of different sets of joint angles which represent the same position of the end-effector. This paper describes how to manage the angle of each joint to move its end-effector preferably on an X-Y plane with obstacles in the end-effector’s reachable area, and how to optimize the movement of a multi-joint robot arm, evading obstacles. The definition of “preferable” movement depends upon a purpose of robot operation. First, we divide viewpoints of preference into two, 1) the standpoint of the end-effector, and 2) the standpoint of joints. Then, we define multiple objective functions, and formulate it into a multi-objective programming problem. Finally, we solve it using multi-purpose genetic algorithm, and obtain reasonable results. The method described here is possible to add appropriate objective function if necessary for the purpose.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.221-229
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• 2022

Sliding mode control (SMC) is a robust control method to control a robot arm with nonlinear properties. A high switching gain of SMC causes chattering problems, although the SMC allows the adequate control performance by giving high switching gain, without the exact robot model containing nonlinear and uncertainty terms. In order to solve this problem, SMC with sliding perturbation observer (SMCSPO) has been researched, where the method can reduce the chattering by compensating the perturbation, which is estimated by the observer, and then choosing a lower switching control gain of SMC. However, optimal gain tuning is necessary to get a better tracking performance and reducing a chattering. This paper proposes a method that the Q-learning automatically tunes the control gains of SMCSPO with an iterative operation. In this tuning method, the rewards of reinforcement learning (RL) are set minus tracking errors of states, and the action of RL is a change of control gain to maximize rewards whenever the iteration number of movements increases. The simple motion test for a 7-DOF robot arm was simulated in MATLAB program to prove this RL tuning algorithm. The simulation showed that this method can automatically tune the control gains for SMCSPO.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.181-190
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• 2015

This paper presents a new approach to control the position of robot arm in workspace a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme was applied. Since parameters of the robot arm such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters was considered as a external disturbance force. To identify the known parameters, an improved robust control algorithm is directly derived from the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing forces coming from the difference between the actual and the estimated system parameters. Numerical examples are shown using SCARA arm with four joints.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.3
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• pp.7-16
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• 2011

This study proposes the compensation method for the mechanical deflection error of a SCARA robot. While most studies on the related subject have dealt with the development of a control algorithm for improvement of robot accuracy, this study presents the control method reflecting the mechanical deflection error which is predicted in advance. The deflection at the end of the gripper of SCARA robot is caused by the self-weights and payloads of Arm 1, Arm 2 and quill. If the deflection is constant even though robot's posture and payload vary, there may not be a big problem on robot accuracy because repetitive accuracy, that is relative accuracy, is more important than absolute accuracy in robot. The deflection in the end of the gripper varies as robot's posture and payload change. That's why the moments $M_x$, $M_y$ and $M_z$ working on every joint of a robot vary with robot's posture and payload size. This study suggests the compensation method which predicts the deflection in advance with the variations in robot's posture and payload using neural network. To do this, I chose the posture of robot and the payloads at random, found the deflections by the FEM analysis, and then on the basis of this data, made compensation possible by predicting deflections in advance successively with the variations in robot's posture and payload through neural network learning.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.12-17
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• 1991

In this paper, a variable structure system control method is proposed to the trajectory control of robot arm. A proposed method uses nonlinear switching function and saturation function. Furthermore, learning control method uses to decrease of the following error. The computer simulation results show that the chattering and the following error decrease and is improved the control the performance by a proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.386-390
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• 1998

A master-slave system is proposed as a teaching device for a dual arm robot. The slave robots are remotely controlled by two delta-type master arms. In order to help the operator to observe the target object from the desired position and desired direction, cameras are mounted on a specialized manipulator, Movements of two slave arms are coordinated with that of the cameras. Due to this coordinated movements, the operator needs not to care the geometrical relation between the cameras and the slave robots.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.300-305
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• 2007

This study developed a human robot master arm, which has a structure similar to the human arm, with the object of taking over human works. The robot arm was structured to reproduce human actions using three axes on each of the shoulder and the wrist based on mechanics, and the actuator of each axis adopted an ordinary DC motor. The servo system of the actuator is a one body type employing an amp for electric power, and it was designed to be small and lightweight for easy installation. We examined the posture control characteristics of the developed robot master arm in order to test its interlocking, continuous notions and reliability.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.3
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• pp.34-40
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• 2001

Robot manipulator has highly nonlinear dynamics. Therefore the control of multi-link robot arms is a challenging and difficult problem. In this paper a decentralized adaptive fuzzy sliding mode scheme is developed for control of robot manipulators. The proposed scheme does not require an accurate manipulator dynamic model, yet it guarantees asymptotic trajectory tracking despite gross robot parameter variations. Numerical simulation for decentralized control of a 3-axis PUMA arm will also be included.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.756-759
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• 1997

Multi-arm cooperation robot system is required for more specific and dextrous jobs such as transferring very large or heavy objects, or grasping work piece while processing on it. There is little research on 3-dimensional multi-arm robot. Here we propose two performance indices presenting isotropy of end-effector's acceleration and velocity capabilities with constraints of joint torques, that is Isotropic Acceleration Radius [IAR] and Isotropic Velocity Radius [IVRI. Also the procedure to find 3-dimensional IAR, IVR is proposed, where available acceleration set concept is used. The case of 3-dimensional two 3 joint robot system was simulated and the distributions of IAR, IVR was studied.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1179-1185
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• 2010

This paper deals with a robust controller design problem for a small one-link robot arm system subject to input time delay and load variations. The uncertain parameters of the system are considered as a disturbance input. A disturbance observer(DOB) has been designed to alleviate disturbance effects and to compensate performance degradation owing to the time-delay. This paper employs a new DOB structure for non-minimum phase systems together with the Smith predictor. We propose a new controller for reducing the both effects of disturbance and time-delay. In order to test the performance of proposed controller, four different other control laws are compared with the proposed one by computer simulations. The simulation results show the effectiveness of the proposed control method.