Lifting motion simulation using a hybrid approach

In this study, a hybrid dynamic model for lifting motion simulation is presented. The human body is represented by a two-dimensional (2D) five-segment model. The lifting motions are predicted by solving a nonlinear optimisation problem, the objective function of which is defined based on a minimal-effort performance criterion. In the optimisation procedure, the joint angular velocities are bounded by time-functional constraints that are determined by actual motions. Symmetric lifting motions performed by younger and older adults under varied task conditions were simulated. Comparisons between the simulation results and actual motion data were made for model evaluation. The results showed that the mean and median joint angle errors were less than 10°, which suggests the proposed model is able to accurately simulate 2D lifting motions. The proposed model is also comparable with the existing motion simulation models in terms of the prediction accuracy. Strengths and limitations of this hybrid model are discussed.     

Simulating Human Lifting Motions Using Fuzzy-Logic Control

Human motion simulation is an ill-posed problem. In order to predict unique lifting motion trajectories, a motion simulation model based on fuzzy-logic control is presented. The human body was represented by a 2-D five-segment model, and the neural controller was specified by fuzzy logic. Fuzzy rules were defined with their antecedent part describing the fuzzy variables of scaled positional error and velocity, and with their consequent part describing scaled angular velocity. These rules were generated according to certain trends in the fuzzy variable trajectories observed from actual lifting motions. An optimization procedure was performed to specify the parameters of the membership functions by minimizing the differences between the simulated and actual final postures. Simulations were obtained for 14 novel lifting motions from seven participants. Overall, results indicated that the presented model simulated lifting motions with an accuracy that was at least comparable to some previous human motion simulation models. The accuracy of the simulations differed between joints and was highest near the beginning and end of the motions. Strengths and limitations of the modeling approach are discussed. The use of fuzzy-logic control appears to be a fruitful basis for future simulations of lifting and other human tasks.      

Human lifting simulation using a multi-objective optimization approach

This paper presents a multiobjective optimization (MOO) approach to predicting dynamic lifting for a three-dimensional, highly redundant digital human model with 55 degrees of freedom. The optimization problem is formulated to optimize two objective functions simultaneously—dynamic effort and stability—subject to basic physical and kinematical constraints. The predictive dynamics approach is used to solve for the joint angles, torque profiles, and ground reaction forces. The weighted sum approach of MOO is used to aggregate the two objective functions, and the Pareto optimal set for the problem is generated by systematically varying the weighting parameters for the objective functions. Experimental data are used to validate the final simulation. Several examples are presented to demonstrate the effect of the weighting parameters for the two objective functions on the predicted box-lifting strategies. The results show that the proposed MOO approach improves the simulation results compared to the single objective optimization formulation. Also, the formulation is less sensitive to the weighting coefficient for the stability criterion.     

Simulation of lifting motions using a novel multi-objective optimization approach

In this study, a novel lifting motion simulation model was developed based on a multi-objective optimization (MOO) approach. Two performance criteria, minimum physical effort and maximum load motion smoothness, were selected to define the multi-objective function in the optimization procedure using a weighted-sum MOO approach. Symmetric lifting motions performed by younger and older adults under varied task conditions were simulated. The results showed that the proposed MOO approach led to up to 18.9% reductions in the prediction errors compared to the single-objective optimization approach. This finding suggests that both minimum physical effort and maximum load motion smoothness play an important role in lifting motion planning. Age-related differences in the mechanisms for planning lifting motions were also investigated. In particular, younger workers tend to rely more on the criterion of minimizing physical effort during lifting motion planning, while maximizing load motion smoothness seems to be the dominant objective for older workers.Relevance to industryLifting tasks are closely associated with occupational low back pain (LBP). In this study, a novel lifting motion simulation model was developed to facilitate the analysis of lifting biomechanics and LBP prevention. Age-related differences in lifting motion planning were discussed for better understanding LBP injury mechanisms during lifting.     

Dynamic motion planning of overarm throw for a biped human multibody system

We propose a motion planning formulation of overarm throw for a 55-degree-of-freedom biped human multibody system. The unique characteristics of the throwing task—highly redundant, highly nonlinear, and highly dynamic—make the throwing motion simulation challenging in the literature and are addressed within the framework of multibody dynamics and optimization. To generate physically feasible throwing motions in a fully predictive method without input reference from motion capture or animation, rigorous dynamics modeling, such as dynamic balance based on Zero-Moment Point (ZMP) and ground reaction loads, is associated with the constraints. Given the target location and the object mass, the algorithm outputs the motion, required actuator torques, release conditions, and projectile and flight time of the object. Realistic human-like motions of throwing are generated for different input parameters, which demonstrate valid cause–effect relations in terms of both kinematic and kinetic outputs.     

无人车辆轨迹规划与跟踪控制的统一建模方法

无人车辆的轨迹规划与跟踪控制是实现自动驾驶的关键.轨迹规划与跟踪控制一般分为两个部分，即先根据车辆周边环境信息以及自车运动状态信息规划出参考轨迹，再依此轨迹来调节车辆纵横向输出以实现跟随控制.本文通过对无人车辆的轨迹规划与跟踪进行统一建模，基于行车环境势场建模与车辆动力学建模，利用模型预测控制中的优化算法来选择人工势场定义下的局部轨迹，生成最优的参考轨迹，并在实现轨迹规划的同时进行跟踪控制.通过CarSim与MATLAB/Simulink的联合仿真实验表明，该方法可在多种场景下实现无人车辆的动态避障.     

A 2-D simulation model for lifting activities

Occupational biomechanics models deal with the evaluation of physical activities such as lifting of loads. This allows the user to determine the stresses imposed on the musculoskeletal system while holding or moving a load. These models are useful tools in estimating these stresses especially those imposed on the lumbar spine. dynamic biomechanical models, as opposed to static models require the displacement-time information to obtain the kinematics needed to estimate the kinetics of the motion. However, the collection of this displacement data is both tedious and can require expensive equipment.

Simulation models on the other hand can provide an indirect means of performing the biomechanical analyses without having to collect the displacement-time data. A typical simulation model for 2-D lifting activities will be presented. The basis for this is the hypothesis that the body will perform the activity in such a manner so as to minimize the work done. Using this assumption an objective function was developed subject to a set of constraints. These constraints relate to the human movement, the physical workplace layout, and maintenance of balance. Using this model, it was possible to generate the lifting motion patterns, as well as the kinematics and kinetics of motion. The paper discusses the model development, the model output and the kinematics and kinetics of the simulation of the lifting action.     

On Trajectory Tracking Model Predictive Control of an Unmanned Quadrotor Helicopter Subject to Aerodynamic Disturbances

In this article a model predictive control (MPC) strategy for the trajectory tracking of an unmanned quadrotor is presented. The quadrotor's dynamics are modeled using a hybrid systems approach and, specifically, a set of piecewise affine (PWA) systems around different operating points of the translational and rotational motions. The proposed control scheme is dual and consists of an integral MPC for the translational motions, followed by an MPC scheme for the tracking of the quadrotor's attitude motions. By the utilization of PWA representations, the controller is computed for a larger part of the quadrotor's flight envelope, which provides more control authority for aggressive maneuvering. The proposed dual control scheme is able to calculate optimal control actions with robustness against atmospheric disturbances (e.g. wind gusts) and with respect to the physical constraints of the quadrotor (e.g. maximum lifting forces or fixed thrust limitations in order to extend flight endurance). Extended simulation studies indicate the efficiency of the MPC scheme, both in trajectory tracking and aerodynamic disturbance attenuation.     

Editing and Synthesizing Two‐Character Motions using a Coupled Inverted Pendulum Model

This study aims to develop a controller for use in the online simulation of two interacting characters. This controller is capable of generalizing two sets of interaction motions of the two characters based on the relationships between the characters. The controller can exhibit similar motions to a captured human motion while reacting in a natural way to the opponent character in real time. To achieve this, we propose a new type of physical model called a coupled inverted pendulum on carts that comprises two inverted pendulum on a cart models, one for each individual, which are coupled by a relationship model. The proposed framework is divided into two steps: motion analysis and motion synthesis. Motion analysis is an offline preprocessing step, which optimizes the control parameters to move the proposed model along a motion capture trajectory of two interacting humans. The optimization procedure generates a coupled pendulum trajectory which represents the relationship between two characters for each frame, and is used as a reference in the synthesis step. In the motion synthesis step, a new coupled pendulum trajectory is planned reflecting the effects of the physical interaction, and the captured reference motions are edited based on the planned trajectory produced by the coupled pendulum trajectory generator. To validate the proposed framework, we used a motion capture data set showing two people performing kickboxing. The proposed controller is able to generalize the behaviors of two humans to different situations such as different speeds and turning speeds in a realistic way in real time.     

A Sequential Bi-criteria Search Algorithm for Robot Path Planning in the Box Pushing Problem

The collision-free trajectory planning method subject to control constraints for mobile manipulators is presented. The robot task is to move from the current configuration to a given final position in the workspace. The motions are planned in order to maximise an instantaneous manipulability measure to avoid manipulator singularities. Inequality constraints on state variables i.e. collision avoidance conditions and mechanical constraints are taken into consideration. The collision avoidance is accomplished by local perturbation of the mobile manipulator motion in the obstacles neighbourhood. The fulfilment of mechanical constraints is ensured by using a penalty function approach. The proposed method guarantees satisfying control limitations resulting from capabilities of robot actuators by applying the trajectory scaling approach. Nonholonomic constraints in a Pfaffian form are explicitly incorporated into the control algorithm. A computer example involving a mobile manipulator consisting of nonholonomic platform (2,0) class and 3DOF RPR type holonomic manipulator operating in a three-dimensional task space is also presented.     

序优化理论在大规模机组组合求解中的应用

序优化理论以满足工程实际需要为目的,能够简化优化问题复杂程度,节省大量计算时间,保证以足够高的概率求得足够好的解.文中将煤耗费用、机组启动成本、购电费用、SO_2排放费用作为目标函数,考虑了带时间耦合关系的系统运行约束、机组特性约束、一次能源约束,建立了考虑火电、水电、核电、生物质、燃气多种类型电源的96时段机组组合动态优化模型,并引入序优化理论予以求解.最后,分别对10~100机24时段标准火电测试系统和128机96时段某省级实际电力系统进行算例仿真,并与其他优化算法的求解结果进行了详细的对比分析,进一步验证了采用序优化理论解决电力系统大规模机组组合问题的可行性和实用性.     

Motion planning for mobile manipulators with a non-holonomic constraint using the FSP (full space parameterization) method

The efficient utilization of the motion capabilities of mobile manipulators, i.e., manipulators mounted on mobile platforms, requires the resolution of the kinematically redundant system formed by the addition of the degrees of freedom (DOF) of the platform to those of the manipulator. At the velocity level, the linearized Jacobian equation for such a redundant system represents an underspecified system of algebraic equations, which can be subject to a varying set of contraints such as a non-holonomic constraint on the platform motion, obstacles in the workspace, and various limits on the joint motions. A method, which we named the Full Space Parameterization (FSP), has recently been developed to resolve such underspecified systems with constraints that may vary in time and in number during a single trajectory. In this article, we first review the principles of the FSP and give analytical solutions for constrained motion cases with a general optimization criterion for resolving the redundancy. We then focus on the solutions to (1) the problem introduced by the combined use of prismatic and revolute joints (a common occurrence in practical mobile manipulators), which makes the dimensions of the joint displacement vector components non-homogeneous, and (2) the treatment of a non-holonomic constraint on the platform motion. Sample implementations on several large-payload mobile manipulators with up to 11 DOF are discussed. Comparative trajectories involving combined motions of the platform and manipulator for problems with obstacle and joint limit constraints, and with non-holonomic contraints on the platform motions, are presented to illustrate the use and efficiency of the FSP approach in complex motion planning problems. © 1996 John Wiley & Sons, Inc.     

Simulation and optimization of automated masonry construction using cable robots

A cable-driven parallel robot for automated masonry construction is currently under development. Besides the mechatronic design and component engineering, a simulation framework has been realized to optimize the cable robot motions with respect to technical and economic requirements, which supports both the prediction of the potential and limitations of this approach as well as the reduction of the risk for further development activities.The framework generates suitable trajectories for every masonry unit to be placed, considering several requirements and optimization criteria. These include motion time, collision avoidance, stiffness, cable forces and energy requirements. The framework uses a hybrid particle swarm algorithm for global optimization.The paper presents the trajectory modeling and the definition of the cost functions derived from physical models of the cable robot. It includes the analysis of simulation results that illustrate the generated trajectories.     

Control of snake robots with switching constraints: trajectory tracking with moving obstacle

We propose control of a snake robot that can switch lifting parts dynamically according to kinematics. Snakes lift parts of their body and dynamically switch lifting parts during locomotion: e.g. sinus-lifting and sidewinding motions. These characteristic types of snake locomotion are used for rapid and efficient movement across a sandy surface. However, optimal motion of a robot would not necessarily be the same as that of a real snake as the features of a robot’s body are different from those of a real snake. We derived a mathematical model and designed a controller for the three-dimensional motion of a snake robot on a two-dimensional plane. Our aim was to accomplish effective locomotion by selecting parts of the body to be lifted and parts to remain in contact with the ground. We derived the kinematic model with switching constraints by introducing a discrete mode number. Next, we proposed a control strategy for trajectory tracking with switching constraints to decrease cost function, and to satisfy the conditions of static stability. In this paper, we introduced a cost function related to avoidance of the singularity and the moving obstacle. Simulations and experiments demonstrated the effectiveness of the proposed controller and switching constraints.     

Dynamics-based analysis and synthesis of human locomotion

One of the best ways to synthesize realistic human motions is to animate characters from captured motion data that inherently respect motion laws. Retargeting and interpolation methods are often used to adapt these motions to different representations of the character and to various environmental constraints but they may introduce physical inaccuracies, although the synthesized motions are natural looking. This paper presents a method for evaluating the physical correctness of retargeted and interpolated locomotions using an inverse dynamics analysis. Furthermore, we propose to improve an initial database with analysed motions that are synthesized again by using a forward dynamics approach. The analysis algorithm consists in determining the resulting forces and torques at joints. With this intention, we develop an automatic creation process of the mass/inertia model of the character. Then using support phase recognition, we compute resulting forces and torques by an inverse dynamics method. The retargeting and the interpolation methods change the physics of the motions. This change is evaluated by using the results of our analysis on artificial and real motions and by using literature results and experimental data from force plates. The evaluation relies on the study of several retargeting and interpolation parameters such as the global size of the character or the structure of the model. The output of this evaluation, the resulting forces and torques at joints, are used to produce physically valid motions by using forward dynamics simulation. With this purpose, we introduce forces and torques normalizations, and finally the synthesized motions may improve the initial database.     

Forward dynamics based realistic animation of rigid bodies

This paper presents a new methodology for model and control of the motion of an (articulated) rigid body for the purposes of animation. The technique uses a parameter optimization method for forward dynamic simulation to obtain a good set of values for the control variables of the system. We model articulated rigid bodies using a moderate number of control nodes, and we linearly interpolate control values between adjacent pairs of these nodes. The interpolated control values are used to determine the forces/torques for the body actuators. We can control total motion duration time, and the control is more flexible than in any other dynamics based animation techniques. We employ a parameter optimization, (or nonlinear programming) method to find a good set of values for the control nodes. We extend this method by using a musculotendon skeletal model for the human body instead of the more commonly used robot model to provide more accurate human motion simulations. Skeletal and musculotendon dynamics enable us to do the human body animation more accurately than ever because the muscle force depends on the geometry of a human as well as on differential kinematic parameters. We show various levels of motion control for forward dynamics animation: ranging from piecewise linear forces/torques control for joints to muscle activation signal control for muscles to generate highly nonlinear forces/torques. This spectrum of control levels provides various nonlinear resulting motions to animators to allow them to achieve effective motion control and physically realistic motion simultaneously. Because our algorithms are heavily dependent on parameter optimization, and since the optimization technique may have difficulty finding a global optimum, we provide a modified optimization method along with various techniques to reduce the search space size. Our parameter optimization based forward dynamic animation and musculotendon dynamics based animation present the first use of such techniques in animation research to date.     

Simulation and Optimization of Regular Motions of a Tube-Crawling Robot

The paper is devoted to issues associated with thetube-crawling robot designed at the Munich Technical University. Wefocus on the simulation of the robot dynamics and the optimization ofstructural parameters of the machine and characteristics of its gait.The mathematical model of the eight-legged tube-crawling robotperforming regular motions at a constant speed along a cylindrical tubeis described. On the basis of this model we investigate the influence ofthe machine design and gait parameters on the robot velocity and findtheir optimal values providing the maximal velocity under givenparametric and drive constraints. Numerical examples are presented anddiscussed.     

考虑侧倾的无人车NMPC轨迹跟踪控制

针对高速行驶工况下,无人车转弯时的侧倾易导致车辆模型非线性程度增加,引起轨迹跟踪精度下降和状态失稳的问题,设计一种考虑车辆侧倾因素,基于非线性模型预测控制(NMPC)的无人车轨迹跟踪控制器.根据拉格朗日分析力学和车辆运动学,考虑车辆侧倾几何学和载荷转移效应,建立考虑侧倾因素的非线性车辆模型,包括车体动力学模型和修正的“Magic Formula”轮胎模型;基于此车辆模型,构建非线性模型预测控制器(NMPC)的预测模型,并设定控制器的线性、非线性约束,以保证车辆的运动状态处于稳定区域内.在Carsim和Simulink联合仿真平台上,验证车辆高速蛇形工况和双移线工况下的轨迹跟踪控制效果,仿真结果显示,所设计的控制器可有效改善高速弯道工况下的跟踪精度和车辆状态稳定性.     

Optimum motion planning in joint space for robots using genetic algorithms

The optimum motion planning in joint space (OMPJS) for robots, which generally consists of two subproblems, optimum path planning and optimum trajectory planning, was considered as a whole in the paper. A new method for optimum motion planning problem based on an improved genetic algorithm is proposed, which is more general, flexible and effective. This approach incorporates kinematics constraints, dynamics constraints, and control constraints of robotic manipulator. The simulation results for a two and a three degrees of freedom robots are presented and discussed. The simulations are based on genetic algorithm class library WGAClass 1.0 developed by us with Borland C++ 3.1.     

Motion planning for humanoid robots based on virtual constraints extracted from recorded human movements

In the field of robotics there is a great interest in developing strategies and algorithms to reproduce human-like behavior. In this paper, we consider motion planning for humanoid robots based on the concept of virtual holonomic constraints. At first, recorded kinematic data of particular human motions are analyzed in order to extract consistent geometric relations among various joint angles defining the instantaneous postures. Second, a simplified human body representation leads to dynamics of an underactuated mechanical system with parameters based on anthropometric data. Motion planning for humanoid robots of similar structure can be carried out by considering solutions of reduced dynamics obtained by imposing the virtual holonomic constraints that are found in human movements. The relevance of such a reduced mathematical model in accordance with the real human motions under study is shown. Since the virtual constraints must be imposed on the robot dynamics by feedback control, the design procedure for a suitable controller is briefly discussed.