Complex Motion Modeling and State Estimation in Road Coordinates

Constrained modeling and state estimation have attracted much attention in recent years. This paper focuses on target motion modeling and tracking in road coordinates. An improved initialization method,which uses the optimal fusion of the position measurements in different directions,is presented for the constraint coordinate Kalman filter(CCKF). The CCKF is evaluated with a comprehensive comparison to the state-of-art linear equality constraint estimation methods. Numerical simulation results demonstrate the better performance of the CCKF. Then the interacting multiple model CCKF(IMM-CCKF) is proposed to manifest the advantages of the CCKF in complex motion modeling and state estimations. The effectiveness of the IMM-CCKF in maneuvering target tracking with spatial equality constraints is demonstrated by numerical experiments.

Dlung:Unsupervised Few-Shot Diffeomorphic Respiratory Motion Modeling

Lung image registration plays an important role in lung analysis applications,such as respiratory motion modeling.Unsupervised learning-based image registration methods that can compute the deformation without the requirement of supervision attract much attention.However,it is noteworthy that they have two drawbacks:they do not handle the problem of limited data and do not guarantee diffeomorphic(topologypreserving)properties,especially when large deformation exists in lung scans.In this paper,we present an unsupervised few-shot learning-based diffeomorphic lung image registration,namely Dlung.We employ fine-tuning techniques to solve the problem of limited data and apply the scaling and squaring method to accomplish the diffeomorphic registration.Furthermore,atlas-based registration on spatio-temporal(4D)images is performed and thoroughly compared with baseline methods.Dlung achieves the highest accuracy with diffeomorphic properties.It constructs accurate and fast respiratory motion models with limited data.This research extends our knowledge of respiratory motion modeling.

Wearable sensors for 3D upper limb motion modeling and ubiquitous estimation

Human motion capture technologies are widely used in interactive game and learning, animation, film special effects, health care, and navigation. Because of the agility, upper limb motion estimation is the most difficult problem in human motion capture. Traditional methods always assume that the movements of upper arm and forearm are independent and then estimate their movements separately; therefore, the estimated motion are always with serious distortion. In this paper, we propose a novel ubiquitous upper limb motion estimation method using wearable microsensors, which concentrates on modeling the relationship of the movements between upper arm and forearm. Exploration of the skeleton structure as a link structure with 5 degrees of freedom is firstly proposed to model human upper limb motion. After that, parameters are defined according to Denavit-Hartenberg convention, forward kinematic equations of upper limb are derived, and an unscented Kalman filter is invoked to estimate the defined parameters. The experimental results have shown the feasibility and effectiveness of the proposed upper limb motion capture and analysis algorithm.

Motion/Posture Modeling and Simulation Verification of Physically Handicapped in Manufacturing System Design

Non-obstacle design is critical to tailor physically handicapped workers in manufacturing system. Simultaneous consideration of variability in physically disabled users, machines and environment of the manufacturing system is extremely complex and generally requires modeling of physically handicapped interaction with the system. Most current modeling either concentrates on the task results or functional disability. The integration of physical constraints with task constraints is far more complex because of functional disability and its extended influence on adjacent body parts. A framework is proposed to integrate the two constraints and thus model the specific behavior of the physical handicapped in virtual environment generated by product specifications. Within the framework a simplified model of physical disabled body is constructed, and body motion is generated based on 3 levels of constraints（effecter constraints, kinematics constraints and physical constraints）. The kinematics and dynamic calculations are made and optimized based on the weighting manipulated by the kinematics constraints and dynamic constraints. With object transferring task as example, the model is validated in Jack 6.0. Modelled task motion elements except for squatting and overreaching well matched with captured motion elements. The proposed modeling method can model the complex behavior of the physically handicapped by integrating both task and physical disability constraints.

A Multi-Task Motion Generation Model that Fuses a Discriminator and a Generator

The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spatial-temporal structures,and the deep learning model can fully describe the potential semantic structure of human motion.To improve the authenticity of the generated human motion sequences,we propose a multi-task motion generation model that consists of a discriminator and a generator.The discriminator classifies motion sequences into different styles according to their similarity to the mean spatial-temporal templates from motion sequences of 17 crucial human joints in three-freedom degrees.And target motion sequences are created with these styles by the generator.Unlike traditional related works,our model can handle multiple tasks,such as identifying styles and generating data.In addition,by extracting 17 crucial joints from 29 human joints,our model avoids data redundancy and improves the accuracy of model recognition.The experimental results show that the discriminator of the model can effectively recognize diversified movements,and the generated data can correctly fit the actual data.The combination of discriminator and generator solves the problem of low reuse rate of motion data,and the generated motion sequences are more suitable for actual movement.

Numerical study on wave loads and motions of two ships advancing in waves by using three-dimensional translating-pulsating source

A frequency domain analysis method based on the three-dimensional translating-pulsating （3DTP） source Green function is developed to investigate wave loads and free motions of two ships advancing on parallel course in waves. Two experiments are carried out respectively to mea- sure the wave loads and the free motions for a pair of side-by- side arranged ship models advancing with an identical speed in head regular waves. For comparison, each model is also tested alone. Predictions obtained by the present solution are found in favorable agreement with the model tests and are more accurate than the traditional method based on the three dimensional pulsating （3DP） source Green function. Numer- ical resonances and peak shift can be found in the 3DP pre- dictions, which result from the wave energy trapped in the gap between two ships and the extremely inhomogeneous wave load distribution on each hull. However, they can be eliminated by 3DTP, in which the speed affects the free sur- face and most of the wave energy can be escaped from the gap. Both the experiment and the present prediction show that hydrodynamic interaction effects on wave loads and free motions are significant. The present solver may serve as a validated tool to predict wave loads and motions of two ves- sels under replenishment at sea, and may help to evaluate the hydrodynamic interaction effects on the ships safety in replenishment operation.

Motion Error Compensation of Multi-legged Walking Robots

Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.

Improvement of the prediction accuracy of polar motion using empirical mode decomposition

Previous studies revealed that the error of pole coordinate prediction will significantly increase for a prediction period longer than 100 days, and this is mainly caused by short period oscillations. Empirical mode decomposition （EMD）, which is increasingly popular and has advantages over classical wavelet decomposition, can be used to remove short period variations from observed time series of pole co- ordinates. A hybrid model combing EMD and extreme learning machine （ELM）, where high frequency signals are removed and processed time series is then modeled and predicted, is summarized in this paper. The prediction performance of the hybrid model is compared with that of the ELM-only method created from original time series. The results show that the proposed hybrid model outperforms the pure ELM method for both short-term and long-term prediction of pole coordinates. The improvement of prediction accuracy up to 360 days in the future is found to be 24.91% and 26.79% on average in terms of mean absolute error （MAE） for the xp and yp components of pole coordinates, respectively.

Bionic Attitude Transformation Combined with Closed Motion for a Free Floating Space Robot

In order to realize the small error attitude transformation of a free floating space robot,a new method of three degrees of freedom（ DOF） attitude transformation was proposed for the space robot using a bionic joint. A general kinematic model of the space robot was established based on the law of linear and angular momentum conservation. A combinational joint model was established combined with bionic joint and closed motion. The attitude transformation of planar,two DOF and three DOF is analyzed and simulated by the model,and it is verified that the feasibility of attitude transformation in three DOF space. Finally,the specific scheme of disturbance elimination in attitude transformation is presented and simulation results are obtained.Therefore,the range of application field of the bionic joint model has been expanded.

Online interactive identification method based on ESO disturbance estimation for motion model of double propeller propulsion unmanned surface vehicle

In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.

Research on Hydrodynamics Model Test for Deepsea Open-Framed Remotely Operated Vehicle

This paper presents the features of newly designed hydrodynamics test for the scaled model of 4500 m deepsea open-framed remotely operated vehicle （ROV）, which is being researched and developed by Shanghai Jiao Tong University. Accurate hydrodynamics coefficients measurement and spatial modeling of ROV are significant for the maneuverability and control algorithm. The scaled model of ROV was constructed by 1：1.6. Hydrodynamics coefficients were measured through VPMM and LAHPMM towing test. And dynamics model was derived as a set of equations, describing nonlinear and coupled 5-DOF spatial motions. Rotation control motion was simulated to verify spatial model proposed. Research and application of hydrodynamics coefficients are expected to enable ROV to overcome uncertainty and disturbances of deepsea environment, and accomplish some more challengeable and practical missions.

Rolling Shutter Camera:Modeling,Optimization and Learning

Most modern consumer-grade cameras are often equipped with a rolling shutter mechanism,which is becoming increasingly important in computer vision,robotics and autonomous driving applications.However,its temporal-dynamic imaging nature leads to the rolling shutter effect that manifests as geometric distortion.Over the years,researchers have made significant progress in developing tractable rolling shutter models,optimization methods,and learning approaches,aiming to remove geometry distortion and improve visual quality.In this survey,we review the recent advances in rolling shutter cameras from two aspects of motion modeling and deep learning.To the best of our knowledge,this is the first comprehensive survey of rolling shutter cameras.In the part of rolling shutter motion modeling and optimization,the principles of various rolling shutter motion models are elaborated and their typical applications are summarized.Then,the applications of deep learning in rolling shutter based image processing are presented.Finally,we conclude this survey with discussions on future research directions.

Method of target tracking with Doppler blind zone constraint

Doppler blind zone （DBZ） has a bad influence on the airborne early warning radar, although it has good detection performance for low altitude targets with pulse Doppler （PD） technology. In target tracking, the blind zone can cause target tracking breakage easily. In order to solve this problem, a parallel particle filter （PF） algorithm based on multi-hypothesis motion models （MHMMs） is proposed. The algorithm produces multiple possible target motion models according to the DBZ constraint. Particles are updated with the constraint in each motion model. Once the first measurement from the target which reappears from DBZ falls into the particle cloud formed by any model, the measurementtrack association succeeds and track breakage is avoided. The simulation results show that on the condition of different DBZ ranges, a high association ratio can be got for targets with different maneuverability levels, which accordingly improves the tracking quality.

Attitude control of spacecraft during propulsion of swing thruster

As for orbit transfer vehicle (OTV) with multiple satellites/payloads carried,the release of each payload will bring serious change to the mass center of OTV and the thrust produced by the swing thruster will form a rather large disturbance to the attitude of OTV. Steering the nozzle to track the estimated center of mass (ECM) of OTV can reduce but not remove the disturbance due to the difference between the ECM and the practical mass center (PCM) of OTV. The practical propelling direction will change with the internal motion during the propulsion process and attitude control system should be enabled to guarantee that the propelling direction is collinear with the command. Since the structural parameters have changed,which is due to internal motion and fuel consumption,the dynamic model have to be formulated to determine these time-varying parameters and the required attitude of OTV should be determined as well. Modulating attitude quaternion results in quasi Euler angles. Based on the resulting quasi Euler angles,a novel attitude switching control law is introduced to control the variable-mass OTV. Simulation results show that,even in the case of structural asymmetry,control torque matrix asymmetry,attitude disturbance and strong coupling between the channels,the attitude of OTV can be controlled perfectly,and the proposed attitude control law is effective for the variable-mass OTV with swing thruster.

Particle-filter-based walking prediction model for occlusion situations

In the field of mobile robotics,human tracking has emerged as an important objective for facilitating human-robot interaction.In this paper,we propose a particle-filter-based walking prediction model that will address an occlusion situation.Since the target being tracked is a human leg,a motion model for a leg is required.The validity of the proposed model is verified experimentally.

Valuing Credit Default Swap under a double exponential jump diffusion model

This paper discusses the valuation of the Credit Default Swap based on a jump market, in which the asset price of a firm follows a double exponential jump diffusion process, the value of the debt is driven by a geometric Brownian motion, and the default barrier follows a continuous stochastic process. Using the Gaver-Stehfest algorithm and the non-arbitrage asset pricing theory, we give the default probability of the first passage time, and more, derive the price of the Credit Default Swap.

Impacts of space-time-frequency synchronization errors onwide-band target echo characteristics of bistatic/multistatic radar

Bistatic/multistatic radar has great potential advantages over its monostatic counterpart. However, the separation of a transmitter and a receiver leads to difficulties in locating the target position accurately and guaranteeing space-timefrequency synchronization of the transmitter and the receiver.The error model of space-time-frequency synchronization in a motion platform of bistatic/multistatic radar is studied. The relationship between the space synchronization error and the transmitter platform position, receiver platform position, moving state, and beam pointing error, is analyzed. The effect of space synchronization error on target echo power is studied. The target scattering characteristics are restructured by many separate scattering centers of the target in high frequency regions. Based on the scattering centers model of the radar target, this radar target echo model and the simulation method are discussed. The algorithm of bistatic/multistatic radar target echo accurately reflects the scattering characteristics of the radar target, pulse modulation speciality of radar transmitting signals, and spacetime-frequency synchronization error characteristics between the transmitter station and the receiver station. The simulation of bistatic radar is completed in computer, and the results of the simulation validate the feasibility of the method.

A rotating elastic plate/block model for Eurasia

On the assumption that a plate is elastically deformable and may rotate as a whole, we found that Eurasian area may be divided into an Eurasian plate and three blocks of the Xiyu, the North China and the Southeast Asia according to tectonic frame of the East and Southeast Asia and the ITRF2008 velocity field in Eurasian area. F tests show that the accuracy of this elastic-plate/block model is significantly higher than the corresponding rigid-plate models; the area covered is notably larger also.

The Voice of Physics in Finance:A Glance on the Theoretical Application of Heat Equation to Stock Price Diffusions

Stock price volatility is considered the main matter of concern within the investment grounds.However,the diffusivity of these prices should as well be considered.As such,proper modelling should be done for investors to stay healthy-informed.This paper suggest to model stock price diffusions using the heat equation from physics.We hypothetically state that,our model captures and model the diffusion bubbles of stock prices with a better precision of reality.We compared our model with the standard geometric Brownian motion model which is the wide commonly used stochastic differential equation in asset valuation.Interestingly,the models proved to agree as evidenced by a bijective relation between the volatility coefficients of the Brownian motion model and the diffusion coefficients of our heat diffusion model as well as the corresponding drift components.Consequently,a short proof for the martingale of our model is done which happen to hold.

Wash Waves Generated by High Speed Displacement Ships

It is difficult to compute far-field waves in a relative large area by using one wave generation model when a large calculation domain is needed because of large dimensions of the waterway and long distance of the required computing points. Variation of waterway bathymetry and nonlinearity in the far field cannot be included in a ship fixed process either. A coupled method combining a wave generation model and wave propagation model is then used in this paper to simulate the wash waves generated by the passing ship. A NURBS-based higher order panel method is adopted as the stationary wave generation model; a wave spectrum method and Boussinesq-type equation wave model are used as the wave propagation model for the constant water depth condition and variable water depth condition, respectively. The waves calculated by the NURBS-based higher order panel method in the near field are used as the input for the wave spectrum method and the Boussinesq-type equation wave model to obtain the far-field waves. With this approach it is possible to simulate the ship wash waves including the effects of water depth and waterway bathymetry. Parts of the calculated results are validated experimentally, and the agreement is demonstrated. The effects of ship wash waves on the moored ship are discussed by using a diffraction theory method. The results indicate that the prediction of the ship induced waves by coupling models is feasible.