自由翻滚故障卫星外包络抓捕及抓捕路径优化

自由翻滚故障卫星抓捕是航天器在轨服务及空间碎片清理的基础。由于难以确定固定抓捕点及目标运动参数不确定,传统机械臂抓捕方法无法适用类似自由翻滚故障卫星的空间非合作目标。提出一种具有鲁棒性的外包络抓捕方法及抓捕路径优化方案。外包络抓捕方式能够适用于自由翻滚故障卫星抓捕问题,其特点在于,第一,由抓捕末端执行器构成的抓捕包络可以包络空间目标,约束其运动并最终实现抓捕,因此不需要固定抓捕点;第二,末端执行器构成的抓捕包络,能够约束故障卫星运动,而两者之间的摩擦可以有效消除两者之间的相对运动最终成功抓捕翻滚目标。进一步,针对外包络抓捕方法,提出了一种最小燃料消耗及最小抓捕扰动的机械臂抓捕路径。为验证外包络抓捕方法的有效性,构建旋转立方星抓捕地面实验,并利用数值仿真验证外包络抓捕机械臂最优路径规划,仿真结果验证了所提出方法的有效性。     

Capture and detumbling control for active debris removal by a dual-arm space robot

Active debris removal (ADR) technology is an effective approach to remediate the proliferation of space debris, which seriously threatens the operational safety of orbital spacecraft. This study aims to design a controller for a dual-arm space robot to capture tumbling debris, including capture control and detumbling control. Typical space debris is considered as a non-cooperative target, which has no specific capture points and unknown dynamic parameters. Compliant clamping control and the adaptive backstepping-based prescribed trajectory tracking control (PTTC) method are proposed in this paper. First, the differential geometry theory is utilized to establish the constraint equations, the dynamic model of the chaser-target system is obtained by applying the Hamilton variational principle, and the compliance clamping controller is further designed to capture the non-cooperative target without contact force feedback. Next, in the post-capture phase, an adaptive backstepping-based PTTC is proposed to detumble the combined spacecraft in the presence of model uncertainties. Finally, numerical simulations are carried out to validate the feasibility of the proposed capture and detumbling control method. Simulation results indicate that the target detumbling achieved by the PTTC method can reduce propellant consumption by up to 24.11%.     

基于机器学习的空间翻滚目标实时运动预测

借助监督式机器学习（ML）方法,对空间翻滚目标的运动状态预测问题进行研究,为空间机器人抓捕空间翻滚目标提供可靠的数据依据。基于物理模型的运动预测方法依赖理想的建模假设,需要连续的视觉反馈信息,解决目标预测问题的能力有限。因此,本文采用机器学习中纯数据驱动方式的稀疏伪输入高斯过程（SPGP）回归方法进行空间翻滚目标的运动预测。给定空间翻滚目标运动状态的历史观测数据,通过连续优化真实观测数据,得到稀疏的伪训练数据集,进而在线快速预测目标的运动状态,预测的计算效率达到毫秒级。此外,利用马尔科夫链蒙特卡洛（MCMC）法处理连续优化过程,克服由于随机初始值造成的优化过程陷入局部极小值问题。利用Snelson数据验证了所提稀疏伪输入高斯过程回归方法的正确性,并通过4组仿真算例验证了所提方法对于空间翻滚目标运动预测的有效性和鲁棒性。     

Detumbling strategy based on friction control of dual-arm space robot for capturing tumbling target

The rotational motion of a tumbling target brings great challenges to space robot on successfully capturing the tumbling target. Therefore, it is necessary to reduce the target’s rotation to a rate at which capture can be accomplished by the space robot. In this paper, a detumbling strategy based on friction control of dual-arm space robot for capturing tumbling target is proposed. This strategy can reduce the target’s rotational velocity while maintaining base attitude stability through the establishment of the rotation attenuation controller and base attitude adjustment controller. The rotation attenuation controller adopts the multi-space hybrid impedance control method to control the friction precisely. The base attitude adjustment controller applies the dual-arm extended Jacobian matrix to stabilize the base attitude. The main contributions of this paper are as follows: (1) The compliant control method is adopted to achieve a precise friction control, which can reduce the target angular velocity steadily; (2) The dual-arm extended Jacobian matrix is applied to stabilize the base attitude without affecting the target capture task; (3) The detumbling strategy of dual-arm space robot is designed considering base attitude stabilization, realizing coordinated planning of the base attitude and the arms. The strategy is verified by a dual-arm space robot with two 7-DOF (degrees of freedom) arms. Simulation results show that, target with a rotation velocity of 20 (°)/s can be effectively controlled to stop within 30 s, and the final deflection of the base attitude is less than 0.15° without affecting the target capture task, verifying the correctness and effectiveness of the strategy. Except to the tumbling target capture task, the control strategy can also be applied to other typical on-orbit operation tasks such as space debris removal and spacecraft maintenance.     

Multi-view space object recognition and pose estimation based on kernel regression

The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions.     

Three-line structured light vision system for non-cooperative satellites in proximity operations

Adapter ring is a commonly used component in non-cooperative satellites, which has high strength and is suitable to be recognized and grasped by the space manipulator. During proximity operations, this circle feature may be occluded by the robot arm or limited field of view. Moreover, the captured images may be underexposed when there is not enough illumination. To address these problems, this paper presents a structured light vision system with three line lasers and a monocular camera. The lasers project lines onto the surface of the satellite, and six break points are formed along both sides of the adapter ring. A closed-form solution for real-time pose estimation is given using these break points. Then, a virtual structured light platform is constructed to simulate synthetic images of the target satellite. Compared with the predefined camera parameters and relative positions, the proposed method is demonstrated to be more effective, especially at a close distance. Besides, a physical space verification system is set up to prove the effectiveness and robustness of our method under different light conditions. Experimental results indicate that it is a practical and effective method for the pose measurement of on-orbit tasks.     

Pre-impact trajectory planning for minimizing base attitude disturbance in space manipulator systems for a capture task

Aimed at capture task for a free-floating space manipulator, a scheme of pre-impact trajectory planning for minimizing base attitude disturbance caused by impact is proposed in this paper.Firstly, base attitude disturbance is established as a function of joint angles, collision direction and relative velocity between robotic hand and the target.Secondly, on the premise of keeping correct capture pose, a novel optimization factor in null space is designed to minimize base attitude disturbance and ensure that the joint angles do not exceed their limits simultaneously.After reaching the balance state, a desired configuration is achieved at the contact point.Thereafter, particle swarm optimization(PSO) algorithm is employed to solve the pre-impact trajectory planning from its initial configuration to the desired configuration to achieve the minimized base attitude disturbance caused by impact and the correct capture pose simultaneously.Finally, the proposed method is applied to a 7-dof free-floating space manipulator and the simulation results verify the effectiveness.     

空间翻滚非合作目标消旋技术发展综述

大量残存太空的空间垃圾对在轨运行航天器的安全构成严重威胁,对其进行主动移除已迫在眉睫。火箭末级、失效卫星等非合作目标已失去姿态调整能力,且长期在失控状态下运行,受太阳光压、重力梯度等摄动力矩及失效前自身残余角动量等因素的影响往往会出现翻滚运动。对翻滚非合作目标直接捕获存在碰撞风险,为降低风险系数采取消旋后再捕获是较为合适的方式。在对火箭末级、失效卫星等典型非合作目标运动形式及消旋过程进行分析的基础上,综述了目前国内外所提出的接触式及非接触式消旋方法,并对非合作目标翻滚运动测量及动力学参数辨识和消旋控制这两项消旋共性关键技术进行了归纳总结。本综述将为中国空间碎片主动清除技术的发展提供有益参考。     

Online condition diagnosis for a two-stage gearbox machinery of an aerospace utilization system using an ensemble multi-fault features indexing approach

China manned space station is designed to operate for over ten years. Long-term and sustainable research on space science and technology will be conducted during its operation. The application payloads must meet the ‘‘long life and high reliability" mission requirement. Gearbox machinery is one of the essential devices in an aerospace utilization system, failure of which may lead to downtime loss even during some disastrous catastrophes. A fault diagnosis of gearbox has attracted attentions for its significance in preventing catastrophic accidents and guaranteeing sufficient maintenance. A novel fault diagnosis method based on the Ensemble Multi-Fault Features Indexing(EMFFI) approach is proposed for the condition monitoring of gearboxes. Different from traditional methods of signal analysis in the one-dimensional space, this study employs a supervised learning method to determine the faults of a gearbox in a two-dimensional space using the classification model established by training the features extracted automatically from diagnostic vibration signals captured. The proposed method mainly includes the following steps. First, the vibration signals are transformed into a bi-spectrum contour map utilizing bi-spectrum technology,which provides a basis for the following image-based feature extraction. Then, Speeded-Up Robustness Feature(SURF) is applied to automatically extract the image feature points of the bi-spectrum contour map using a multi-fault features indexing theory, and the feature dimension is reduced by Linear Discriminant Analysis(LDA). Finally, Random Forest(RF) is introduced to identify the fault types of the gearbox. The test results verify that the proposed method based on the multi-fault features indexing approach achieves the target of high diagnostic accuracy and can serve as a highly effective technique to discover faults in a gearbox machinery such as a two-stage one.     

空间失效慢旋卫星视觉特征跟踪与位姿测量

空间碎片或者失效卫星往往绕其惯性主轴做自旋运动,虽然处于一种稳定状态,但是对其运动状态测量的难度相比三轴稳定目标而言又增加了许多,主要体现在复杂光场环境下和目标观测面周期性进出视场引起的特征点丢失、尺度变化和旋转变化,以及长时间连续观测引起的累积误差增大、位姿解算不收敛等难题。通过构建优化目标特征数据库,将传统测量方式中前后帧的匹配转变为当前帧与特征数据库的匹配和特征点的优化,即使中间过程帧出现了偏差仍然可以较好地跟踪后续图像帧的正确位置。在李代数空间下建立位姿向量微分扰动方程,获得测量值与估计值的残差目标函数,基于贝叶斯法则最大后验概率和李群与李代数的对指变换法则,求取位姿向量最优解。解决了李群空间下由于位姿变换矩阵不可加性而无法优化的问题,提高了连续测量过程中系统的测量精度。实验结果表明,无优化测量方法无法保证整个旋转周期的有效测量;通过增加位姿优化过程,连续稳定测量时间明显延长,针对以12（°）/s自旋运动的目标,测量稳定段误差在2°以内,旋转角速度测量误差为0.12（°）/s。     

基于多智能体强化学习的空间机械臂轨迹规划

针对某型六自由度（DOF）空间漂浮机械臂对运动目标捕捉场景,开展了基于深度强化学习的在线轨迹规划方法研究。首先给出了机械臂DH （Denavit-Hartenberg）模型,考虑组合体力学耦合特性建立了多刚体运动学和动力学模型。然后提出了一种改进深度确定性策略梯度算法,以各关节为决策智能体建立了多智能体自学习系统。而后建立了"线下集中学习,线上分布执行"的空间机械臂对匀速直线运动目标捕捉训练系统,构建以目标相对距离和总操作时间为参数的奖励函数。最后通过数学仿真验证,实现了机械臂对各向匀速运动目标的快速捕捉,平均完成耗时5.4 s。与传统基于随机采样的规划算法对比,本文提出的自主决策运动规划方法求解速度和鲁棒性更优。     

无先验信息的低轨空间目标航迹起始方法

针对光学观测中缺乏预报信息的低轨道空间目标自动识别捕获问题,提出一种基于修正Hough变换的空间目标航迹起始方法,从而实现空间目标的自动识别。首先利用背景恒星运动规律对观测数据进行预处理,剔除大部分背景恒星。再利用观测数据的时序信息、定向参数进行Hough变换。本方法并没有采用传统的Hough变换对所有参数空间中的数据点进行投票,而是仅对参数空间中部分点投票,可以大幅减少运算量和存储量。试验表明:该方法能够有效地抑制背景恒星产生的虚假航迹,并快速准确地完成无先验信息的低轨道空间目标的航迹起始;可以在光学观测中实现空间目标的自动识别捕获,以及实时发现新目标,这为低轨道空间目标光学观测的无人值守和联网观测奠定了技术基础。     

空间非合作目标多指包络抓捕路径设计

针对现有空间非合作目标抓捕中存在无固定抓捕点以及待抓捕目标存在动态性等问题,提出了一种"主-从"式多指包络抓捕路径设计算法。首先,为了降低多指包络构型设计中的自由度,将多指机构分为一根主手指和其余从手指两类。然后,为了实现对具有动态性的空间非合作目标的抓捕,采用误差跟踪控制方法使主手指的基关节与包络点之间的运动保持同步。接着,引入单向距离的概念衡量主手指构型和包络边相似度,并利用快速搜索随机树算法寻找使得单向距离最小的主手指关节角取值。进一步,根据多指机构的结构模型,确定其余从手指的构型。最后,根据包络条件选择能够约束住空间非合作目标运动的有效包络构型。通过对可以简化为扁平型的空间非合作目标和一般性三维空间非合作目标这两类目标的包络抓捕仿真可以得出,所设计的算法可适用于一般性空间非合作目标的包络抓捕,同时计算复杂度也大大降低。     

Use of land＇s cooperative object to estimate UAV＇s pose for autonomous landing

The research of unmanned aerial vehicles＇（UAVs＇）autonomy navigation and landing guidance with computer vision has important signifcance.However,because of the image blurring,the position of the cooperative points cannot be obtained accurately,and the pose estimation algorithms based on the feature points have low precision.In this research,the pose estimation algorithm of UAV is proposed based on feature lines of the cooperative object for autonomous landing.This method uses the actual shape of the cooperative-target on ground and the principle of vanishing line.Roll angle is calculated from the vanishing line.Yaw angle is calculated from the location of the target in the image.Finally,the remaining extrinsic parameters are calculated by the coordinates transformation.Experimental results show that the pose estimation algorithm based on line feature has a higher precision and is more reliable than the pose estimation algorithm based on points feature.Moreover,the error of the algorithm we proposed is small enough when the UAV is near to the landing strip,and it can meet the basic requirements of UAV＇s autonomous landing.     

基于图像质量度量准则的空间目标平动补偿

为了获得空间目标的微动信息,需要对雷达回波中的高速平动分量进行精确补偿。针对空间目标高速运动对微动信息提取的影响问题,首先分析了空间目标平动对微多普勒频率的调制影响,得到目标高速平动,特别是平动加速度、平动加加速度对微多普勒频率趋势性调制现象将干扰微多普勒频率提取的结论。在此基础上,利用目标平动直接导致目标多普勒频谱展宽的特点,提出了一种基于图像质量度量准则的空间目标平动参数估计方法,并根据估计出的平动参数实现运动补偿。最后,采用空间目标多散射中心模型,进行平动补偿分析,仿真结果验证了该方法的有效性。     

空间目标控制与信息处理技术的研究内容和应用现状

星际空间目标识别、探测以及开发利用，将是21世纪人类关注的热点领域，也是进一步推动科学技术不断发展的动力之一。本文讨论了空间目标控制与信息处理技术研究的主要内容以及涉及的基础理论；重点介绍了与空间目标控制与制导以及信息处理密切相关的估计方法的发展现状以及存在的问题；最后，简单分析了未来空间活动将面临的课题和有关方法的发展方向。     

单目相机物体位姿估计方法研究

现有的机器视觉通常以边缘轮廓和角点作为特征,因此要求背景单一,对环境结构化依赖程度高。为了拓展机器人的应用范围,使其脱离结构化的环境,提出了一种基于SIFT特征点和PNP技术的单目相机估计目标物体位姿的方法。以BumbleBee双目相机为硬件基础,以C++为开发平台,结合了Eigen计算库、OpenCV图像处理库和Triclops库,开发了单目视觉位姿估计算法,实现在复杂背景下对表面纹理较为丰富的物体的位姿估计。利用试验对所提方法进行了验证,试验结果表明,该算法具有较高的估计精度,可以作为机器抓取的依据。     

Exploring 2D projection and 3D spatial information for aircraft 6D pose

The 6D pose estimation is important for the safe take-off and landing of the aircraft using a single RGB image. Due to the large scene and large depth, the exiting pose estimation methods have unstratified performance on the accuracy. To achieve precise 6D pose estimation of the aircraft, an end-to-end method using an RGB image is proposed. In the proposed method, the 2D and 3D information of the keypoints of the aircraft is used as the intermediate supervision, and 6D pose information of the aircraft in this intermediate information will be explored. Specifically, an off-the-shelf object detector is utilized to detect the Region of the Interest (RoI) of the aircraft to eliminate background distractions. The 2D projection and 3D spatial information of the pre-designed keypoints of the aircraft is predicted by the keypoint coordinate estimator (KpNet). The proposed method is trained in an end-to-end fashion. In addition, to deal with the lack of the related datasets, this paper builds the Aircraft 6D Pose dataset to train and test, which captures the take-off and landing process of three types of aircraft from 11 views. Compared with the latest Wide-Depth-Range method on this dataset, our proposed method improves the average 3D distance of model points metric (ADD) and 5° and 5 m metric by 86.8% and 30.1%, respectively. Furthermore, the proposed method gets 9.30 ms, 61.0% faster than YOLO6D with 23.86 ms.     

飞行器失稳平面振荡运动的物理机制

基于全局亚迭代耦合求解非定常流体动力学方程和刚体动力学方程(CFD/RBD),研究动不稳定飞行器在自由俯仰与自由沉浮二自由度下自激发平面失稳运动的非定常特征。数值研究表明:超声速锥-柱-裙飞行器的平面失稳运动发展为极限环形式,并伴随着波系结构非定常变化;平面运动保持了自由俯仰基本运动特征,但同步自由沉浮使得极限环周期运动的振幅更小、频率更快;平面自由运动中飞行器绕靠近头部的"不动点"转动。基于第二拉格朗日方程和虚功原理,导出能够描述迟滞现象的参数化非线性动力学模型。多尺度近似分析(MTS)获得参数化运动特征:自激振动过程是拟简谐运动;平衡点阻尼是决定运动稳定特性的分叉参数;振幅特性与阻尼非线性相关,频率特性与刚度非线性相关;模型分析证实了平面自由运动的"不动点"现象并自洽地解释了沉浮自由度存在使得极限环振幅变小的动力学机制。非线性模型的理论分析、重构都与数值结果高度一致,从而有效地佐证了自激振荡建模研究的合理性。     

Trajectory Planning Algorithm Based on Quaternion for 6-DOF Aircraft Wing Automatic Position and Pose Adjustment Method

 A 6-degree of freedom (6-DOF) aircraft wing position and pose automatic adjustment method is presented to improve ARJ21 wing-fuselage connection precision and efficiency. Wing position and pose are adjusted by three pillars which are driven by six high-precision servo motors. During the adjustment process, wing is tracked and positioned by laser tracker. Wing initial posi-tion and pose are calibrated by using the measurement coordinates of assembly reference points. Wing target position and pose are calculated according to wing initial, fuselage position and pose, and relative position and pose requirements between wing and fuselage for the connection. Combining Newton-Euler method with quaternion position and pose analyzing method, the inverse kinematics of servo motors, together with the adjustment system dynamics is obtained. Wing quintic polynomial trajec-tory planning algorithm based on quaternion is proposed; the initial, target position and pose need to be solved and the inter-mediate moving path is uncertain. Simulation results show that the adjustment method has good dynamic characteristics and satisfies engineering requirements. Preliminary engineering application indicates that ARJ21 wing adjustment efficiency and precision are improved by using the proposed method.