Motion prediction of an uncontrolled space target

Capturing an uncontrolled space target is a tremendously challenging research topic. Target capture by a space robot can be well planned according to predicted motion of the target. In this paper, motion prediction of an uncontrolled space target is studied and a motion prediction algorithm is proposed. In the proposed algorithm, firstly a method for identifying the parameters of motion state and inertial property of the target is established; and then through substituting the identified parameters into the dynamic equations of the target, the motion of the target can be predicted as the solution of the equations. In the identification of the parameters, the unscented Kalman filter (UKF) is applied. In order to support the UKF, a method for estimating noise level of the observation data is developed, so our motion prediction algorithm is noise adaptive. A practical convergent criterion is also designed to determine the time when the estimated result of the UKF is accurate enough, such that the predicted motion is credible enough. After that, the accuracy of the prediction is further improved by an optimization method. In the end of this paper, numerical simulations are done to verify the validity of the proposed motion prediction algorithm. Simulation results indicate that the proposed algorithm is able to predict the motion of the target precisely.     

Using consecutive point clouds for pose and motion estimation of tumbling non-cooperative target

This paper proposes a consecutive point clouds-based estimation scheme to resolve the state estimation problem for tumbling non-cooperative space target during the rendezvous phase without a prior knowledge about its structure. First, a consistent pose estimation algorithm is realized by maintaining a global structure of the target that is reconstructed upon the pose graph optimization. Then an extend Kalman filter on Lie group is adopted to estimate the motion and inertia parameters of the target using the pose measurements of the point clouds. Finally, a semi-physical experimental study is carried out to evaluate the performance of the proposed estimation scheme. The result shows that the structure, motion and the inertia parameters can be estimated, and the total computation time is approximately linear with the number of point clouds.     

基于单目视觉的空间非合作目标相对运动参数估计

提出了一种估计空间非合作目标相对运动参数的单目视觉方法,该方法将相对运动参数估计问题描述为一个非线性约束优化问题．通过迭代求解特征值问题来确定基本矩阵,将基本矩阵分解可得到相对运动参数的4个可能解,给出了消除旋转矩阵多义解的简单判断准则．数值仿真结果验证了该方法的有效性．     

一种仿生附着装置柔顺关节的优化设计

为提高仿生附着装置在捕获空间非合作目标物时对目标运动参数的适应性,设计了一种3自由度串联柔顺关节,可通过关节嵌入系统后的协调运动来辅助装置被动适应运动目标物姿态,并在运动过程中基于弹簧、阻尼缓冲器组成的关节柔顺机构及其能量耗散原理来降低目标物动能。为验证、优化关节性能,通过ADAMS虚拟样机软件建立了基于柔顺关节的仿生附着装置捕获过程运动学与动力学模型,分析了柔顺关节3组弹簧刚度系数、黏滞阻尼系数对非合作目标物捕获状态的影响,并利用ADAMS-iSIGHT联合仿真平台,通过多岛遗传算法对上述弹簧、阻尼器的重要参数进行了优化,极大提高了柔顺关节的能量耗散效果,同时保证了可捕获目标物运动参数达到规定要求。      

A multi-satellite co-tracking method for a single space target based on adaptive distributed spherical simplex information-weighted consensus filter

A multi-satellite co-tracking method for a single non-cooperative target is proposed to extend the arc of observation as well as to improve the accuracy of tracking. Firstly, the motion of the target is considered to be affected by J2 perturbation, and the model of multi-satellite co-tracking a single space target is designed with only measured angles. Then, a multi-satellite co-tracking method for a single space target based on an adaptive distributed spherical simplex information-weighted consensus filter (ADSSICF) is proposed. The spherical simplex is used to reduce the computational cost of the information filter, and to improve the efficiency of tracking. The angle-only measurement equation is linearized by the statistical linear regression method, and linearization errors are compensated for by updating measurement noise. By designing an adaptive consensus algorithm, only a small number of iterations are needed to achieve network consensus, to improve the convergence speed of the consensus algorithm, and prove the stability of ADSSICF. Finally, a simulation of four low-orbit satellites tracking a single space target is established. The focus of this paper is on the real-time performance and tracking accuracy of the multi-satellite co-tracking a single space target with angle-only based on ADSSICF. The performance of ADSSICF is verified from three indicators: the consensus and convergence of algorithm, the accuracy of state estimation.     

双臂空间机器人姿态调整运动的最优控制规划

讨论了双臂空间机器人系统姿态调整运动的最优控制规划问题.以多体动力学理论为基础,导出了载体位置、姿态均不受控制情况下,双臂空间机器人系统的动量矩守恒关系,并将其转化为系统状态方程;利用近似优化方法给出了一种双臂空间机器人姿态、关节协调运动的最优控制算法.其优点在于,仅控制双臂空间机器人的关节运动,即可同时获得载体姿态及机械臂关节需要的终端位置.系统数值仿真,证实了算法的有效性.      

基于双目视觉的非合作目标自主姿态估计方法

针对在轨服务任务对于空间非合作目标的自主相对导航需求,提出了一种基于双目视觉的自主姿态估计方法。该方法以Markley变量描述目标的姿态运动,并利用双目相机对目标表面的特征点进行观测,利用特征点的运动规律与目标姿态运动的相关性,并通过容积卡尔曼滤波算法实现了对非合作目标角速度与自旋轴方向的估计。数学仿真验证了所给出的姿态估计方法,并分析了估计精度的影响因素。     

圆度误差目标函数特性的研究

建立了基于半径测量法的圆度误差最小区域评定法无约束最优化数学模型,对目标函数的特性进行了深入研究,基于现代凸函数理论严格地证明了所建立的目标函数是二维欧式空间R2中的连续、不可微的凸函数,因而它的全局极小值是唯一的。任何最优化算法,只要它收敛,均可用于求解该目标函数并得到可靠的最小区域圆度误差值。给出了实例。     

基于截断最小二乘和半正定规划的空间非合作目标相对位姿估计

面向空间在轨服务、碎片清除重大应用需求,围绕空间光场复杂、空间目标尺度变化及相对姿态与位置强耦合等难题,提出一种基于截断最小二乘与半正定规划的空间非合作目标相对位姿估计方法。基于TOF相机,首先进行体素下采样,提取快速点特征直方图（Fast Point Feature Histograms, FPFH）特征,考虑目标的局部几何结构尺寸,计算两组FPFH特征的相似度并预测特征之间的对应关系,采用截断最小二乘和半正定规划方法对姿态、位置进行解耦,实现空间非合作目标相对位姿估计。使用非合作目标的3D模型进行仿真验证,仿真结果表明：该方法在三种不同高斯噪声强度下具有较好的估计特性,为后续的工程应用及在轨任务实施提供理论与技术支撑。     

铝基微结构光栅几何参数反演

微结构光栅是一种广泛应用的电子元件。采用随机微粒群优化(SPSO)算法反演了一维铝基衬底矩形光栅的几何结构参数。首先介绍了严格耦合波分析(RCWA)法和微粒群优化算法的基本原理,并采用RCWA法求解了光栅内电磁场问题;然后根据正问题求得的光栅光谱反射率建立目标函数,并采用SPSO算法优化目标函数,反演得到单槽和双槽矩形光栅的周期、凸脊宽度和凹槽深度;最后分析了种群大小和搜索区间对反演结果的影响。结果表明,SPSO算法可以准确地反演光栅几何结构参数,并推荐种群数取30。     

基于SMO—SVR的飞机舵面损伤故障趋势预测

飞机舵面出现损伤时,为了更准确的预测状态参量变化情况,提出了一种改进的序贯最小优化支持向量回归(SMO-SVR, Sequential Minimal Optimization Support Vector Regression)预测方法.采用改进C-C平均方法对多元时间序列进行相空间重构,以确定最优嵌入维数m和延迟时间τ_d.根据所求m和τ_d建立加权SVR预测模型,并调整了SMO算法的停机准则.利用区间自适应粒子群算法(IAPSO, Interval Adaptive Particle Swarm Optimization)优化SVR参数,以提高参数优化速度.为了验证改进算法的有效性,针对飞机方向舵损伤故障趋势进行了预测和分析,并与径向基函数神经网络(RBFNN, Radial Basis Function Neural Network)方法进行了对比,仿真结果表明SMO-SVR预测模型具有很好的预测能力.     

基于指数平均动量鸽群优化的多无人机协同目标防御

针对多无人机(UAV)协同目标防御问题,提出了一种基于指数平均动量鸽群优化(EM-PIO)算法。针对三维空间中的多无人机协同目标防御系统进行建模,得到了无人机支配区域的曲面约束方程,并获得了双方无人机的最优控制输入量。采用多级罚函数法构造了优化算法的目标函数,并通过所提出的EM-PIO算法来求解最优目标点。将所提EM-PIO算法与遗传算法(GA)和粒子群优化(PSO)算法进行仿真对比实验,验证了所提EM-PIO算法更加有效解决多无人机协同目标防御问题。      

空间可展开结构区间模型修正方法

传统的模型修正未考虑工程中存在的几何尺寸、材料参数、间隙等不确定性,修正后有限元模型预测精度较低。为提高有限元模型的预测精度,准确预测结构的静动力学特性,对考虑参数不确定性的模型修正进行了研究,提出了一种基于Kriging模型和泛灰数的区间模型修正方法。首先,通过灵敏度分析确定待修正参数,并以修正参数为变量,构造基于Kriging模型的区间响应目标函数;其次,引入泛灰数将区间优化问题转换为区间上限和区间直径两个全局优化问题;然后,利用Kriging模型结合遗传算法给出修正后的参数区间形式;最后,通过该方法对含铰链间隙的某空间可展开结构进行了模型修正。结果表明,修正后参数区间与真实区间重合度较高,修正后结构响应预测区间与实际区间吻合,验证了方法的有效性,为大型空间可展开结构的模型修正提供了一个有效可行的途径。     

基于Frenet和改进人工势场的在轨规避路径自主规划

在轨道间机动的航天器规避空间目标,需兼顾沿转移轨道飞行的绝对运动和规避空间目标的相对运动,路径自主规划难度较大且目前国内外公开研究成果较少。针对上述问题,提出了一种将Frenet坐标系与改进人工势场相结合的在轨规避路径自主规划方法。首先,构建Frenet坐标系表述空间规避运动,解决了路径规划中航天器与既定转移轨道相对位置不易表述的难题,实现了空间规避运动的简便表示;其次,改进人工势场函数、调整势场作用区域,避免了传统人工势场法存在过早轨迹偏离以及局部震荡现象,实现了对空间目标的自主规避;最后,考虑规避安全、轨道保持、制动时效以及燃料消耗因素构建全局优化函数,能够满足不同任务的需求与偏好,实现了沿转移轨道飞行的最小偏移与快速恢复。算法比对与算例求解表明:所提方法应用优势明显,路径平滑、偏移量小,满足航天器规避空间目标的路径规划需求。      

Energy efficient reactionless design of multi-arm space robot for a cooperative handshake maneuver

Space robots play a significant role in on-orbit capture, space structure construction, and assembly tasks. Since the robotic arms are attached to a free-floating satellite, the motion of the manipulator in such tasks and the satellite are coupled. Multiple-arm space robots can perform complex cooperative tasks and are superior to single-arm space robots. Current work proposes a reactionless manipulation algorithm for a multi-robotic arm based on the iterative Newton–Euler method for space robots with many task and balance arms. The present work demonstrates two tasks and one balance arm to perform a reactionless handshake maneuver in space. This maneuver is presented in detail for a planar and spatial case. The planar case uses 3 DoF robotic arms, while the spatial case uses 6 DoF robotic arms. In addition, the balance arm has been designed considering the efficient usage of energy satisfying reactionless manipulation concept. The design procedure focuses on minimizing energy used during the motion of the balance arm for a known motion of task arms using a genetic algorithm. Moreover, computational experiments are conducted to validate the use of the genetic algorithm for optimization. The results of proposed reactionless manipulation algorithm have been validated with the results available in the literature for the spatial case that uses a different method. In the future, an energy-efficient balance arm will be designed to handle tumbling objects.     

多目标位姿约束下空间机器人载体姿态扰动优化

通过运行轨迹的优化设计来减小空间机械臂运动对其基座姿态产生的扰动影响是一种经济有效的方式, 然而针对笛卡儿空间内多个离散位姿约束条件下空间机械臂运动轨迹的优化设计研究相对较少. 通过改进样条函数对机械臂末端运行轨迹进行参数化设计, 将基座姿态的扰动量表达为关于样条函数控制点与相邻约束点之间运行时间的目标函数, 利用遗传算法对目标函数进行全局优化处理, 完成空间机械臂运行轨迹的优化设计. 仿真结果表明, 该方法能有效降低机械臂运动对基座姿态产生的扰动, 并且规划的关节运动轨迹二次连续可微.      

基于SABA优化的Volterra级数空战目标机动轨迹预测

目标机动轨迹预测是空战态势感知和目标威胁评估的重要前提。针对传统目标机动轨迹预测模型复杂度大、预测精度低等问题,通过分析并结合目标机动轨迹时序数据所具备的混沌特性,引入Volterra泛函级数模型进行目标机动轨迹预测。为解决Volterra泛函级数模型中存在高阶核函数难以求解的问题,利用变异机制和自适应步长控制机制改进蝙蝠算法的寻优能力,进而构建了一种基于自适应蝙蝠算法（SABA）优化的Volterra泛函级数目标机动轨迹预测模型,并利用优化后不同阶数的Volterra泛函级数模型对目标未来机动轨迹进行预测。仿真实验中,通过与其他优化算法改进的Volterra泛函级数模型的预测精度对比,验证了所提预测模型的可行性,同时也说明了二阶Volterra泛函级数模型更加适用于目标机动轨迹预测。      

Optimal trajectory planning of free-floating space manipulator using differential evolution algorithm

The existence of the path dependent dynamic singularities limits the volume of available workspace of free-floating space robot and induces enormous joint velocities when such singularities are met. In order to overcome this demerit, this paper presents an optimal joint trajectory planning method using forward kinematics equations of free-floating space robot, while joint motion laws are delineated with application of the concept of reaction null-space. Bézier curve, in conjunction with the null-space column vectors, are applied to describe the joint trajectories. Considering the forward kinematics equations of the free-floating space robot, the trajectory planning issue is consequently transferred to an optimization issue while the control points to construct the Bézier curve are the design variables. A constrained differential evolution (DE) scheme with premature handling strategy is implemented to find the optimal solution of the design variables while specific objectives and imposed constraints are satisfied. Differ from traditional methods, we synthesize null-space and specialized curve to provide a novel viewpoint for trajectory planning of free-floating space robot. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a free-floating spacecraft and demonstrate the feasibility and effectiveness of the proposed method.     

漂浮基姿态受控空间机械臂关节运动的自适应神经网络控制

讨论了载体位置无控、姿态受控情况下,空间机械臂姿态及关节协调运动的自适应神经网络控制问题.由拉格朗日第二类方法及系统动量守恒关系,建立了漂浮基空间机械臂的系统动力学方程.以此为基础,借助于RBF神经网络技术和GL矩阵及乘积算子定义,对空间机械臂系统进行了神经网络系统建模;之后针对空间机械臂所有惯性参数未知的情况,设计了空间机械臂载体姿态与机械臂各关节协调运动的自适应神经网络控制方案.提出的控制方案不要求系统动力学方程具有关于惯性参数的线性性质,且无需预知系统惯性参数的任何信息,也无需对神经网络进行离线训练和学习,因此更适于实时应用.通过对一个平面两杆自由漂浮空间机械臂系统的数值仿真,证实了方法的有效性.