A Hybrid Mapping Method with Position and Stiffness for Manipulator Teleoperation

Jiang, Zainan; Ni, Fenglei; Yang, Dapeng; Li, Chongyang; Yang, Fan; Hong, Li

doi:10.3390/app9235005

Cited by 7 publications

(2 citation statements)

References 21 publications

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“…kNN is a simple and widely used classification method [40]. kNN is a non-parametric approach that was widely applied to statistics in the early 1970s [41][42][43].…”

Section: Classification Algorithmmentioning

confidence: 99%

Detection and Imaging of Underground Objects for Distinguishing Explosives by Using a Fluxgate Sensor Array

2019

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Active and passive techniques are two different techniques with which to detect buried explosives. In practice, the most preferred active method works by broadcasting a signal underground. This signal may stimulate the buried explosive and cause it to explode. It is important to eliminate or minimize this drawback to ensure the safety of the detector operator. In this respect, it is important to increase the studies on the passive detection technique which is not currently used in practice. The aim of this study was to passively detect improvised explosive devices without stimulating them, and to classify underground objects as explosive or non-explosive. A fluxgate sensor array having 33 components was used for passive magnetic field measurements, and the nearest neighborhood algorithm was preferred for classifying the resulting data. In experimental studies, 33 different samples having different amounts of ferromagnetic properties were used. Successful imaging and classification were achieved for the measurements up to 20 cm below the surface of soil. Data were recorded as 32 × 25 matrices, and then they were reduced to 32 × 2 matrices having the same features. Samples having explosive properties were distinguished from other underground objects with success rates of 86% and 95% for 32 × 25 and 32 × 2 data matrices, respectively. Classification times for 32 × 25 and 32 × 2 data matrices were 42 ms and 3.62 ms, respectively. For data groups where the best results were obtained for the data matrices, frame numbers classified in one second were calculated as 23.80 and 276.2, respectively. False alarm rate achieved was 5.31%. The experimental results proved the successes of the matrices reduction and classification approach. One of the most common problems encountered in passive detecting techniques is that the sensor position affects the measurements negatively. In this paper, a solution has been proposed for this important problem.

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“…kNN is a simple and widely used classification method [40]. kNN is a non-parametric approach that was widely applied to statistics in the early 1970s [41][42][43].…”

Section: Classification Algorithmmentioning

confidence: 99%

Detection and Imaging of Underground Objects for Distinguishing Explosives by Using a Fluxgate Sensor Array

2019

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“…This involves the application of common spacecraft ground tests to overcome gravity ( Xu et al, 1994 , Carignan and Akin, 2000 , How et al, 2001 ). For example, the space manipulator can accomplish many dexterous tasks in space ( Jiang et al, 2019a , b ), but in the ground test, the test equipment plays a major role in balancing the weight of the space manipulator itself. In the process of testing the docking mechanism on the ground, the spacecraft matters in simulating the load of the docking mechanism.…”

Section: Introductionmentioning

confidence: 99%

Actuation delay compensation of robots in semi-physical test

Zhang

He²,

Xu³

et al. 2023

Front. Neurorobot.

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In general, the traditional spacecraft semi-physical docking tests include the evaluation of docking and separation performance. However, these tests often rely on “specific” equipment, such as specially designed actuators and fast-response hydraulic systems, to meet the stringent dynamic response requirements of semi-physical testing. In this paper, a novel docking test platform is designed based on a general-purpose industrial manipulator using 3-D force and 3-D torque sensors. Different from the traditional solution, this novel platform is well-assembled and cost-effective. Furthermore, an actuation delay compensation method is introduced to improve the performance. Finally, the proposed method is evaluated using simulations. The results show that the novel method is with promising performance in terms of actuation delay compensation.

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Development of Variable Scaling Teleoperation Framework for Improving Teleoperation Performance

Lee,

Han,

Yang

2024

Int. J. Control Autom. Syst.

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A Hybrid Mapping Method with Position and Stiffness for Manipulator Teleoperation

Cited by 7 publications

References 21 publications

Detection and Imaging of Underground Objects for Distinguishing Explosives by Using a Fluxgate Sensor Array

Detection and Imaging of Underground Objects for Distinguishing Explosives by Using a Fluxgate Sensor Array

Actuation delay compensation of robots in semi-physical test

Development of Variable Scaling Teleoperation Framework for Improving Teleoperation Performance

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