Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Lin, Yunhan; Min, Huasong; Wei, Hongxing

doi:10.1177/1687814015626850

Cited by 11 publications

(6 citation statements)

References 20 publications

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Section: Analysis Of Attitude Calculation Algorithm Based On Multi-in...mentioning

confidence: 99%

“…Anderson et al used improved complementary filtering to fuse the low-frequency noise heading signal and the high-frequency noise radio deviation signal to obtain accurate rate signal estimation. 24,25 The second-order complementary filter is shown in (6), which adds a PI regulator, but it is easy to overshoot and needs to be adjusted where, italicθ ^ is the output of the second-order complementary filter, ω is the angular velocity signal, italicθ a is the attitude angle calculated by acceleration fusion, and k p , k I are the amplification coefficients of the PI regulator respectively.…”

Section: Analysis Of Velocity Measurement and Positioning Algorithm B...mentioning

confidence: 99%

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Research on velocity measurement and relative positioning method of maglev train based on multi-sensor information fusion

Peng

Dou

2022

Measurement and Control

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This paper focuses on the optimal method of the non-contact velocity measurement and relative positioning system for medium and low speed maglev trains. By analyzing the working principle of the velocity measurement method based on counting sleepers and analyzing the speed system error and random error model, it is shown that the velocity measurement accuracy based on the counting sleeper speed measurement method needs to be further improved. Therefore, a method of using multi-sensor information fusion is proposed to improve the accuracy of velocity measurement and relative positioning. Firstly, aiming at the disturbance problem of traction, braking and suspension vibration in the attitude angle calculation and the cumulative error problem of attitude angle, a posture solution method combining the optimized second-order complementary filter and the velocity adaptation Unscented Kalman filter with maximum noise reduction is proposed; Then, in order to further reduce the accumulated error of the attitude angle and the high performance requirements of the gyroscope, the bias instability of the gyroscope is analyzed, and an adaptive wavelet de-noising algorithm based on threshold optimization is proposed; Finally, to weaken the colored noise interference caused by the suspension vibration and to weaken the velocity accumulation error, a fusion velocity measurement and positioning algorithm of multi-loop Kalman filter with acceleration fusion correction and velocity accumulation error correction is researched. The effectiveness of the proposed fusion method is verified through simulation comparison analysis and on-board engineering test. Compared with the velocity measurement method based on counting sleepers, the velocity measurement accuracy is improved by an order of magnitude, and its accuracy is comparable to the high-precision velocity measurement method based on the induction loop and GPS/INS. It has certain engineering applicability and application value.

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Section: Analysis Of Attitude Calculation Algorithm Based On Multi-in...mentioning

confidence: 99%

Section: Analysis Of Velocity Measurement and Positioning Algorithm B...mentioning

confidence: 99%

Research on velocity measurement and relative positioning method of maglev train based on multi-sensor information fusion

Peng

Dou

2022

Measurement and Control

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“…In this study, a trusted IMU device (LPMS-B, LP-Research, Tokyo, Japan) was used to compare the raw data with the sensors used in this study. LPMS-B is an accepted standard in many laboratories [ 25 , 26 ], and its raw data output is reliable. The raw data is verified by fixing the MCM and LPMS-B on the same board and swinging the board randomly and continuously.…”

Section: Verification Of Data Glovesmentioning

confidence: 99%

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation

Lin

Lee

Yang

et al. 2018

Sensors

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Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.

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“…Therefore, IMU-based motion capture systems have come to be a feasible and popular solution. [9][10][11][12][13] Tracking strategies such as force tracking and trajectory tracking have been widely used. 14 Trajectory tracking is inherently more stable and robust and has been widely used for various industrial applications.…”

Section: Introductionmentioning

confidence: 99%

Motion prediction and delay compensation for improved teleoperation of an exoskeletal robot

Duan

et al. 2018

Advances in Mechanical Engineering

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Delay is a major challenge in teleoperation. To teleoperate a robot in real-time with specific human motion such as walking, prediction and compensation algorithms are needed to minimize the tracking delay. Human walking possesses the inherent features of synergy and quasi-periodicity with nonlinearity. By analyzing these features, three prediction methods were designed. A delay-coordinate phase space reconstruction method is based on the delay embedding theorem and uses the historical data. The echo prediction method uses data from the coupling joints of the other body side and takes the Euclidean distances in the delay-coordinate phase space reconstruction method for data search and match. The fused prediction method combines the delay-coordinate phase space reconstruction and echo prediction methods, uses the best matching historical data of the same joint and the corresponding joint of the other limb. These methods were implemented for teleoperation of an exoskeletal robot with inertial measurement unit measurements of human walking. The predicted trajectories were used to compensate the teleoperation delay and improve the robot tracking performance. Experimental results demonstrated that the fused method brought apparent improvement over other methods and can serve as a promising solution for time delay estimation, prediction, and compensation of human walking tracking and teleoperation.

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Inertial measurement unit–based iterative pose compensation algorithm for low-cost modular manipulator

Cited by 11 publications

References 20 publications

Research on velocity measurement and relative positioning method of maglev train based on multi-sensor information fusion

Research on velocity measurement and relative positioning method of maglev train based on multi-sensor information fusion

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation

Motion prediction and delay compensation for improved teleoperation of an exoskeletal robot

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