A new virtual-real gravity compensated inverted pendulum model and ADAMS simulation for biped robot with heterogeneous legs

Xie, Hualong; Zhao, Xiaofei; Sun, Qiancheng; Yang, Kun; Li, Fēi

doi:10.1007/s12206-019-1239-4

Cited by 11 publications

(3 citation statements)

References 10 publications

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“…To verify the accuracy of the mathematical model for the dynamic weighing of straw bales, the model was simulated in this research based on ADAMS software [ 15 ], using SolidWorks software to build a 3D model of the dynamic weighing table, and then imported into ADAMS software to generate a dynamics model [ 16 ]. To simplify the model and to ensure that the height of the center of the bearing table spindle corresponds to the actual dimensions, and to realize the movement of the model of the bearing table, a stationary base was used instead of a round baler which was coaxially connected to the dynamic weighing bearing table spindle.…”

Section: Methodsmentioning

confidence: 99%

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

Yin

Chen

Liu

et al. 2023

Sensors

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Bale density is one of the main performance indicators to measure the quality of baler operation. In this study, a real-time baler bale density monitoring system was designed for the problem of difficult real-time measurement of bale density on round balers. Firstly, a weighing calculation model for the rolling and sliding stage of the bale was established, and the dynamic characteristics during the contact between the bale and the inclined surface were analyzed based on ADAMS dynamics simulation. Then, a real-time monitoring system for the bale density based on the contact pressure of the inclined surface, attitude angle measurement and hydraulic monitoring of the cylinder was constructed, and the accuracy of the weighing model was confirmed. The system was used to observe and analyze the changes in the pitch angle of the carrier table and the oil pressure in the rod chamber of the backpack cylinder during the operation of the round baler. Finally, the monitoring system was calibrated and the dynamic calibration equations were obtained. The results show that the maximum error between the calculated value of the original weighing model and the actual weight was 3.63%, the maximum error of the calculated value of the weighing model corrected by the calibration equations was 3.40% and the measurement accuracy could be satisfied. The results show that the system was highly accurate and met the practical needs of bale weighing in the field.

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Section: Methodsmentioning

confidence: 99%

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

Yin

Chen

Liu

et al. 2023

Sensors

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“…Under assumption (3), M h ′′ is also ignored. Then g ′ = cos (η) g is defined according to the equivalent gravity [37], [38]. As derived in [11], [12], [39], σ ≜ c b tan (ϕ) and the constrained Lagrangian of the bicycle is calculated as follows:…”

Section: Dynamicsmentioning

confidence: 99%

Online Series-Parallel Reinforcement-Learning- Based Balancing Control for Reaction Wheel Bicycle Robots on a Curved Pavement

et al. 2023

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The reaction wheel bicycle robot is a kind of unmanned mobile robot with great potential. However, the control of such bicycle robots on a curved pavement under inaccurate model parameters, model uncertainties and disturbances is challenging due to the lateral instability and udneractuated characteristic. Applying conventional control methods to this problem often results in brittle and inaccurate controllers. In this paper, an online serial-parallel combination reinforcement learning with conventional control methods is designed to achieve the path tracking and banlancing control for a reaction wheel bicycle robot on curved pavements. The parallel part of the controller refers to compensate the equilibrium point and the serial part of the controller refers to adjust the parameters of a sliding mode controller that tracks the target roll equilibrium point. The comparison between the proposed controller and several existing controllers in experimental test built in Matlab Simscape illustrates stronger robustness and better control performances.INDEX TERMS reaction wheel bicycle robot, reinforcement learning, robustness, sliding model control.

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“…The issue of human-machine coordination has become one of the most important research problems in the field of robotics, especially for exoskeleton applications [1][2][3][4]. To achieve consistency and coordination of human-machine coordination, continuous prediction of the joint angle of the lower limbs is required.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Limb Joint Angles Based on Multi-Source Signals by GS-GRNN for Exoskeleton Wearer

Xie

Zhao

et al. 2020

Sensors

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To enable exoskeleton wearers to walk on level ground, estimation of lower limb movement is particularly indispensable. In fact, it allows the exoskeleton to follow the human movement in real time. In this paper, the general regression neural network optimized by golden section algorithm (GS-GRNN) is used to realize prediction of the human lower limb joint angle. The human body hip joint angle and the surface electromyographic (sEMG) signals of the thigh muscles are taken as the inputs of a neural network to predict joint angles of lower limbs. To improve the prediction accuracy in different gait phases, the plantar pressure signals are also added into the input. After that, the error between the prediction result and the actual data decreases significantly. Finally, compared with the prediction result of the BP neural network, GRNN shows splendid prediction performance for its less processing time and higher prediction accuracy.

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A new virtual-real gravity compensated inverted pendulum model and ADAMS simulation for biped robot with heterogeneous legs

Cited by 11 publications

References 10 publications

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

Online Series-Parallel Reinforcement-Learning- Based Balancing Control for Reaction Wheel Bicycle Robots on a Curved Pavement

Prediction of Limb Joint Angles Based on Multi-Source Signals by GS-GRNN for Exoskeleton Wearer

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