High-density genetic linkage map plays an important role in genome assembly and quantitative trait loci (QTL) fine mapping. Since the coming of next-generation sequencing, makes the structure of high-density linkage maps much more convenient and practical, which simplifies SNP discovery and high-throughput genotyping. In this research, a high-density linkage map of cucumber was structured using specific length amplified fragment sequencing, using 153 F2 populations of S1000 × S1002. The high-density genetic map composed 3,057 SLAFs, including 4,475 SNP markers on seven chromosomes, and spanned 1061.19 cM. The average genetic distance is 0.35 cM. Based on this high-density genome map, QTL analysis was performed on two cucumber fruit traits, fruit length and fruit diameter. There are 15 QTLs for the two fruit traits were detected.
The complexity of the kinematics and dynamics of a manipulator makes it necessary to simplify the modeling process. However, the traditional representations cannot achieve this because of the absence of coordinate invariance. Therefore, the coordinate invariant method is an important research issue. First, the rigid-body acceleration, the time derivative of the twist, is proved to be a screw, and its physical meaning is explained. Based on the twist and the rigid-body acceleration, the acceleration of the end-effector is expressed as a linear-bilinear form, and the kinematics Hessian matrix of the manipulator(represented by Lie bracket) is deduced. Further, Newton-Euler's equation is rewritten as a linear-bilinear form, from which the dynamics Hessian matrix of a rigid body is obtained. The formulae and the dynamics Hessian matrix are proved to be coordinate invariant. Referring to the principle of virtual work, the dynamics Hessian matrix of the parallel manipulator is gotten and the detailed dynamic model is derived. An index of dynamical coupling based on dynamics Hessian matrix is presented. In the end, a foldable parallel manipulator is taken as an example to validate the deduced kinematics and dynamics formulae. The screw theory based method can simplify the kinematics and dynamics of a manipulator, also the corresponding dynamics Hessian matrix can be used to evaluate the dynamical coupling of a manipulator.
As one of the most direct indicators of the transparency between a human and an exoskeleton, interactive force has rarely been fused with electromyography (EMG) in the control of human-exoskeleton systems, the performances of which are largely determined by the accuracy of the continuous joint angle prediction. To achieve intuitive and naturalistic human intent learning, a state space model (SSM) for continuous angle prediction of knee joint is developed. When the influence of the interactive force is often ignored in the existing models of human-exoskeleton systems, interactive force is applied as the measurement model output of the proposed SSM, and the EMG signal is used as the state model input signal to indicate muscle activation. The forward dynamics of joint motion and the human-machine interaction mechanism, i.e., the biomechanical interpretations of the interactive force generation mechanism, are derived as the bases for the state model and measurement model based on Hill’s muscle model and semiphenomenological (SP) muscular model, respectively. Gaussian process (GP)-based nonlinear autoregressive with the exogenous inputs (NARX) model and back-propagation neural network (BPNN) are applied to provide better adaptivity for the SSM in practical applications. Corresponding experimental results demonstrate the validity and superiority of the method.
Exoskeletons can assist the daily life activities of the elderly with weakened muscle strength, but traditional rigid exoskeletons bring parasitic torque to the human joints and easily disturbs the natural movement of the wearer’s upper limbs. Flexible exoskeletons have more natural human-machine interaction, lower weight and cost, and have great application potential. Applying assist force according to the patient’s needs can give full play to the wearer’s remaining muscle strength, which is more conducive to muscle strength training and motor function recovery. In this paper, a design scheme of an elbow exoskeleton driven by flexible antagonistic cable actuators is proposed. The cable actuator is driven by a nonlinear series elastic mechanism, in which the elastic elements simulate the passive elastic properties of human skeletal muscle. Based on an improved elbow musculoskeletal model, the assist torque of exoskeleton is predicted. An assist-as-needed (AAN) control algorithm is proposed for the exoskeleton and experiments are carried out. The experimental results on the experimental platform show that the root mean square error between the predicted assist torque and the actual assist torque is 0.00226 Nm. The wearing experimental results also show that the AAN control method designed in this paper can reduce the activation of biceps brachii effectively when the exoskeleton assist level increases.
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