• 로봇학회논문지
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• 제16권1호
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• pp.49-55
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• 2021

Recently, a smart farm technology is drawing attention as an alternative to the decline of farm labor population problems due to the aging society. Especially, there is an increasing demand for automatic harvesting system that can be commercialized in the market. Pre-harvest crop detection is the most important issue for the harvesting robot system in a real-world environment. In this paper, we proposed a real-time tomato instance tracking algorithm by using deep learning and probability models. In general, It is hard to keep track of the same tomato instance between successive frames, because the tomato growing environment is disturbed by the change of lighting condition and a background clutter without a stochastic approach. Therefore, this work suggests that individual tomato object detection for each frame is conducted by YOLOv3 model, and the continuous instance tracking between frames is performed by Kalman filter and probability model. We have verified the performance of the proposed method, an experiment was shown a good result in real-world test data.

• 로봇학회논문지
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• 제11권4호
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• pp.248-255
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• 2016

Machining error makes the uncertainty of dimensional accuracy of the kinematic structure of a parallel robot system, which makes the uncertainty of kinematic accuracy of the end-effector of the parallel robot system. In this paper, the tendency of trajectory tracking error caused by the tolerance of design parameters of the parallel robot is analyzed. For this purpose, all the position errors are analyzed as the manipulator is moved on the target trajectory. X, Y, Z components of the trajectory errors are analyzed respectively, as well as resultant errors, which give the designer of the manipulator the intuitive and deep understanding on the effects of each design parameter to the trajectory tracking errors caused by the uncertainty of dimensional accuracy. The research results shows which design parameters are critically sensitive to the trajectory tracking error and the tendency of the trajectory tracking error caused by them.

• 제어로봇시스템학회논문지
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• 제20권12호
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• pp.1238-1245
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• 2014

This paper proposes an RBFN-based adaptive tracking controller for an electrically driven mobile robot with parametric uncertainties and external disturbances. A mobile robot model considered in this paper includes all models of the robot body and actuators with uncertain kinematic and dynamic parameters, and uncertain frictions and external disturbances. The proposed controller consists of an RBFN(Radial Basis Function Network) and a robust adaptive controller. The presented RBFN is used to approximate unknown nonlinear robot dynamic functions. The proposed controller is adjusted by the adaptation laws obtained through the Lyapunov stability analysis. The proposed control scheme does not a priori need the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. Also, nominal parameter values are not required in the controller. The global stability of the closed-loop robot control system is guaranteed using the Lyapunov stability theory. Simulation results show the validity and robustness of the proposed control scheme.

• Transactions on Control, Automation and Systems Engineering
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• 제3권4호
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• pp.223-228
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• 2001

We have been developed an intelligent mobile robot with an artificial olfactory function to recognize odours and to track odour source location. This mobile robot also has ben installed an engine for speech recognition and synthesis and is controlled by wireless communication. An artificial olfactory system based on array of 7 gas sensors has been installed in the mobile robot for odour recognition, and 11 gas sensors also are located in the obttom of robot to track odour sources. 3 optical sensors are also in cluded in the intelligent mobile robot, which is driven by 2 D. C. motors, for clash avoidance in a way of direction toward an odour source. Throughout the experimental trails, it is confirmed that the intelligent mobile robot is capable of not only the odour recognition using artificial neural network algorithm, but also the tracking odour source using the step-by-step approach method. The preliminary results are promising that intelligent mobile robot, which has been developed, is applicable to service robot system for environmental monitoring, localization of odour source, odour tracking of hazardous areas etc.

• 한국통신학회논문지
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• 제40권4호
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• pp.723-730
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• 2015

본 논문에서는 전시장에 사용되는 도슨트 로봇 (Docent Robot)의 자율주행 정밀도 향상을 위하여 최소자승법을 적용한 위치추적 보정 알고리즘 (Location tracking Compensation Algorithm based on Least-Squares Method, $LCA_{LSM}$)을 제안하고, 도슨트 로봇을 사용한 실험을 통하여 그 성능을 분석하였다. 제안한 $LCA_{LSM}$은 전시장에서 도슨트 로봇의 자율주행에서 엔코더/자이로 (encoder/gyro, E/G)에서 발생하는 누적오차를 줄이고 위치추적 정확도를 개선하기 위하여 수집된 로봇의 위치좌표를 최소자승법 (Least-Squares Method, LSM)에 적용하여 보정한다. 실험결과, 제안한 $LCA_{LSM}$의 위치추적 평균 오차 감소율은 시나리오 1 (S1) 및 시나리오 2 (S2)에서 $LCA_{KF}$(Location tracking Compensation Algorithm based on Kalman Filter, $LCA_{KF}$) 보다 4.85% 더 높음을 확인하였다. 또한, 제안한 $LCA_{LSM}$의 측정오차에 따른 표준 편차는 S1 및 S2에서 E/G와 $LCA_{KF}$에 비해 훨씬 낮을 뿐 아니라 균일함을 확인하였다. 따라서 제안한 $LCA_{LSM}$은 도슨트 로봇이 S1 및 S2의 직선 이동을 할 때 E/G 및 $LCA_{KF}$ 보다 더 안정적임을 알 수 있다.

• 대한임베디드공학회논문지
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• 제13권1호
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• pp.33-43
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• 2018

In this paper, we describe an sound tracking mobile robot suitable for areas where GPS is not available. Sound sensors are attached to four sides of the robot in order to locate the person in a danger, and the robot is supposed to move to the yelling person. The traveling distance of the mobile robot is calculated by the encoder attached to the wheel of the mobile robot. The moving direction of the mobile robot is measured by a gyro sensor on the robot. When the person in danger pushes a button of the mobile robot, the mobile robot transmits the trajectory data to a designated server.

• 한국지능시스템학회논문지
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• 제23권1호
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• pp.51-56
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• 2013

이족 보행 로봇을 실생활에 적용하기 위해서는 다양한 환경에서의 강인한 보행 뿐만 아니라, 현재 위치를 인식하여 목표 위치로의 경로를 생성하고, 경로를 추종하는 기능이 요구된다. 최근에 많이 사용되고 있는 RFID는 이동 로봇의 위치인식 및 경로 생성에 손쉽게 활용이 가능하다. 그러나 이족 로봇은 보행시에 불안정성을 내포하고 있어 주어진 경로에서 벗어나기 쉽다. 본 논문에서는 FSR(Force Sensing Resistor)센서, 자이로와 가속도 센서를 이용하여 이족 보행 로봇의 보행 안정화 방법을 제안하였다. 또한 양발에 RFID 센서를 장착하여 이족 보행 로봇의 위치 인식 후 경로를 추종하는 알고리즘을 제안하였다. 제안된 보행 안정화 알고리즘은 실제 제작된 이족 보행 로봇을 이용하여 비평탄 지형에서 실험하여 검증하였으며, 경로 추종 실험은 RFID센서를 로봇의 발바닥에 장착하여 평탄 지형에서 보행실험을 통해 검증하였다.

• 한국항행학회논문지
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• 제7권2호
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• pp.162-170
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• 2003

In this paper, we propose a robust controller for trajectory control of n-link robot manipulators using feature based on visual feedback. In order to reduce tracking error of the robot manipulator due to parametric uncertainties, integral action is included in the dynamic control part of the inner control loop. The desired trajectory for tracking is generated from feature extraction by the camera mounted on the end effector. The stability of the robust state feedback control system is shown by the Lyapunov method. Simulation and experimental results on a 5-link robot manipulator with two degree of freedom show that the proposed method has good tracking performance.

• 제어로봇시스템학회논문지
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• 제8권10호
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• pp.890-897
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• 2002

This paper deals with the reduction of trajectory tracking error by changing the initial postures of a biped robot. Gait of a biped robot depends on the constraints of mechanical kinematics and the initial states including the posture. Also the dynamic walking stability in a biped robot system is analyzed by zero moment point(ZMP) among the stabilization indices. Path trajectory, in which knee joint is bent forward like human's cases, is applied to most cases considered with above conditions. A new initial posture, which is similar to bird's gait, is proposed to decrease trajectory tracking error and it is verified through real experimental results.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.745-750
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• 2008

Uncertain dynamic parameters and joint flexibility have been problem to control robot manipulator precisely. Hence, even if the controller tracks the desired trajectory well with the feedback of the motor encoders, it is hard to achieve the desired behavior at the end-effector. In this paper, robot trajectory is taught by a general heuristic iterative learning control (ILC) algorithm in order to reduce tracking error of the tool center point (TCP) and the results of tracking with 6 DOF industrial robot manipulator are presented. The performance is verified based on ISO 9283.