• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1679-1683
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• 2005

This paper suggests the new type of a joint torque sensor which is attached at each joint of a manipulator for making compliance. Previous six axis force/torque sensors are high cost and installed end-effector of the manipulator. However, torque on links of previous an end-effector cannot be measured. We design a joint torque sensor that can be fully integrated with an actuator in order to measure applying torque of the manipulator. The sensor system is designed through the structural analysis. The proposed joint torque sensors are installed to the 6 DOF manipulator of a mobile robot for hazardous works and we implemented experiments of measuring applied torque to the manipulator. By the experiment, we proved that the proposed low-cost joint torque sensor gives acceptable performance when we control a manipulator.

• Journal of Sensor Science and Technology
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• v.27 no.2
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• pp.105-111
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• 2018

In this paper, a torque sensor is designed and fabricated to measure the knee joint torque of a walking assist robot for stroke patients. The torque sensor sensing part was modeled on the link of the part connected to the knee joint motor. The torque capacity of the knee joint was calculated by simulation and the size of the torque sensor sensing part was designed using the finite element method. The torque sensor was fabricated by attaching a strain gauge to the sensing part. Characteristic experiments were conducted to characterize the torque sensor, and the torque sensor was calibrated to utilize it for the control of the walking assist robot. As a result of the characteristics test, the reproducibility error and the nonlinearity error of the torque sensor were 0.03% and 0.04%, respectively. Therefore, it is considered that the developed torque sensor can be used to measure the torque applied to the knee joint when walking on a walking assist robot.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.2
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• pp.133-138
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• 2016

Force control and collision detection for a robot are usually conducted using a 6-axis force/torque sensor mounted at the end-effector. However, this scheme suffers from high-cost and the inability to detect collisions at the robot body. As an alternative, joint torque sensors embedded in each joint were used, which also suffered from various errors in torque measurement. To resolve this problem, a robot joint module with an improved joint torque sensor is proposed in this study. In the proposed torque sensor, a cross-roller bearing and disk-type coupling are added to prevent the moment load from adversely affecting the measurement of the joint torque under consideration. This joint design also aims to reduce the stress induced during the assembly process of the sensor. The performance of the proposed joint torque sensor was verified through various experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.524-529
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• 2016

We describe the design and fabrication of a two-axis force/torque sensor with parallel-plate beams (PPBs) and single beams for measuring force and torque in hip-joint rehabilitation exercise using a lower rehabilitation robot. The two-axis force/torque sensor is composed of an Fz force sensor and a Tz torque sensor, which detect z direction force and z direction torque, respectively. The two-axis force/torque sensor was designed using the FEM (Finite Element Method) and manufactured using strain gages. The characteristics experiment of the two-axis force/torque sensor was carried out. The test results show that the interference error of the two-axis force/torque sensor was less than 0.64% and the repeatability error and the non-linearity of the two-axis force/torque sensor were less than 0.03%. It is thought that the developed two-axis force/torque sensor could be used for a lower rehabilitation robot.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.6
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• pp.670-677
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• 2011

This study is to estimate the joint torques without torque sensor using the EMG (Electromyogram) signal of agonist/antagonist muscle with Neural Network Back Propagation Algorithm during the elbow motion. Command Signal can be guessed by EMG signal. But it cannot calculate the joint torque. There are many kinds of field utilizing Back Propagation Learning Method. It is generally used as a virtual sensor estimated physical information in the system functioning through the sensor. In this study applied the algorithm to obtain the virtual senor values estimated joint torque. During various elbow movement (Biceps isometric contraction, Biceps/Triceps Concentric Contraction (isotonic), Biceps/Triceps Concentric Contraction/Eccentric Contraction (isokinetic)), exact joint torque was measured by KINCOM equipment. It is input to the (BP)algorithm with EMG signal simultaneously and have trained in a variety of situations. As a result, Only using the EMG sensor, this study distinguished a variety of elbow motion and verified a virtual torque value which is approximately(about 90%) the same as joint torque measured by KINCOM equipment.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.11-19
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• 2014

In this paper, an external torque estimation problem in one-degree-of-freedom (1-DOF) flexible-joint robot equipped with a joint-torque sensor is revisited. Since a sensor torque from the joint-torque sensor is distorted by two dynamics having a spring connection, i.e., motor dynamics and link dynamics of a flexible-joint robot, a model-based estimation, rather than a simple linear spring model, should be required to extract external torques accurately. In this paper, an external torque estimation algorithm for a 1-DOF flexible-joint robot is proposed. This algorithm estimates both an actuating motor torque from the motor dynamics and an external link torque from the link dynamics simultaneously by utilizing the flexible-joint robot model and the Kalman filter estimation based on random-walk model. The basic structure of the proposed algorithm is explained, and the performance is investigated through a custom-designed experimental testbed for a vertical situation under gravity.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.55-62
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• 2018

In this paper, a method for estimation of external force on an end-effector using joint torque sensor is proposed. The method is based on portion of measure torque caused by external force. Due to noise in the torque measurement data from the torque sensor, a recursive least-square estimation algorithm is used to ensure a smoother estimation of the external force data. However it is inevitable to create a delay for the sensor to detect the external force. In order to reduce the delay, modified recursive least-square is proposed. The performance of the proposed estimation method is evaluated in an experiment on a developed six-degree-of-freedom robot. By using NI DAQ device and Labview, the robot control, data acquisition and The experimental results output are processed in real time. By using proposed modified RLS, the delay to estimate the external force with the RLS is reduced by 54.9%. As an experimental result, the difference of the actual external force and the estimated external force is 4.11% with an included angle of $5.04^{\circ}$ while in dynamic state. This result shows that this method allows joint torque sensors to be used instead of commonly used external sensory system such as F/T sensors.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.218-222
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• 2011

This paper proposes a single-joint optical torque sensor with one body structure. Conventional optical torque sensors consist of three parts, two plates and an elastic structure. They have slightly slipping problem between plates and elastic structure due to the manufacturing tolerance. Since the order of measurement range of optical sensor is about ten micrometers, the slipping problem causes large measurement error, especially in the case of vibrational or high speed plant. This problem does not occur in the proposed design due to the one body structure. The proposed sensor has advantage of low cost, light weight, and small size. And it is easy to design and manufacture. Simulation works that analysis of stress and strain are performed accurately. To demonstrate the performance of proposed sensor, experiments were implemented to compare with a commercial force/torque sensor (ATI Mini45).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.233-234
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• 2010

• The Journal of Korea Robotics Society
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• v.15 no.2
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• pp.169-176
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• 2020

This paper studied the collision detection of robot manipulators for safe collaboration in human-robot interaction. Based on sensor-based collision detection, external torque is detached from subtracting robot dynamics. To detect collision using joint torque sensor data, a comparative study was conducted using data-based machine learning algorithm. Data was collected from the actual 3 degree-of-freedom (DOF) robot manipulator, and the data was labeled by threshold and handwork. Using support vector machine (SVM), decision tree and k-nearest neighbors KNN method, we derive the optimal parameters of each algorithm and compare the collision classification performance. The simulation results are analyzed for each method, and we confirmed that by an optimal collision status detection model with high prediction accuracy.