基于经验学习的空间机器人精细抓捕方法

机器人在空间环境下完成对复杂形状物体的精细操作,要求其具有较强的自主操作规划能力.从学习人类经验出发,模仿人类经验生成来建立经验数据库,提出有效的物体分类方法,在物体类别基础上,识别同类物体的可抓取区域,并提出“单拇指”姿态规划方法,将对物体的操作经验泛化到同类物体的操作规划中.试验证明了算法的有效性.     

Design and fabrication of robotic gripper for grasping in minimizing contact force

This paper presents a new method to improve the kinematics of robot gripper for grasping in unstructured environments, such as space operations. The robot gripper is inspired from the human hand and kept the hand design close to the structure of human fingers to provide successful grasping capabilities. The main goal is to improve kinematic structure of gripper to increase the grasping capability of large objects, decrease the contact forces and makes a successful grasp of various objects in unstructured environments. This research will describe the development of a self-adaptive and reconfigurable robotic hand for space operations through mechanical compliance which is versatile, robust and easy to control. Our model contains two fingers, two-link and three-link, with combining a kinematic model of thumb index. Moreover, some experimental tests are performed to examine the effectiveness of the hand-made in real, unstructured tasks. The results represent that the successful grasp range is improved about 30% and the contact forces is reduced approximately 10% for a wide range of target object size. According to the obtained results, the proposed approach provides an accommodative kinematic model which makes the better grasping capability by fingers geometries for a robot gripper.     

雷达波束驻留模式下空间碎片数量的置信区间估计

碎片数量估计是空间碎片环境统计特征描述的重要内容之一,对于空间碎片环境模型验证、航天器碰撞风险分析以及碎片数量增长趋势预测有重要意义.针对波束指向正东、正南任意仰角的雷达波束驻留(Beam-park)模式(天顶指向是波束指向仰角为90°时的特例),给出了一种估计碎片数量置信区间的方法.对于给定轨道高度范围内一个具有穿越雷达波束可能性(即雷达散射截面足够大,且轨道倾角相对测站纬度足够大)的碎片,将其是否真正穿越波束这一随机事件用(0-1)分布来建模,根据所采集的轨道高度和倾角数据,计算出该轨道高度范围内碎片穿越波束的平均概率,进而采用中心极限定理来估计碎片数量的置信区间.仿真结果表明了方法的有效性.      

A Partially Orthogonal EnKF approach to atmospheric density estimation using orbital debris

A key requirement for accurate trajectory prediction and space situational awareness is knowledge of how non-conservative forces affect space object motion. These forces vary temporally and spatially, and are driven by the underlying behavior of space weather particularly in Low Earth Orbit (LEO). Existing trajectory prediction algorithms adjust space weather models based on calibration satellite observations. However, lack of sufficient data and mismodeling of non-conservative forces cause inaccuracies in space object motion prediction, especially for uncontrolled debris objects. The uncontrolled nature of debris objects makes them particularly sensitive to the variations in space weather. Our research takes advantage of this behavior by utilizing observations of debris objects to infer the space environment parameters influencing their motion.The hypothesis of this research is that it is possible to utilize debris objects as passive, indirect sensors of the space environment. We focus on estimating atmospheric density and its spatial variability to allow for more precise prediction of LEO object motion. The estimated density is parameterized as a grid of values, distributed by latitude and local sidereal time over a spherical shell encompassing Earth at a fixed altitude of 400 km. The position and velocity of each debris object are also estimated. A Partially Orthogonal Ensemble Kalman Filter (POEnKF) is used for assimilation of space object measurements to estimate density.For performance comparison, the scenario characteristics (number of objects, measurement cadence, etc.) are based on a sensor tasking campaign executed for the High Accuracy Satellite Drag Model project. The POEnKF analysis details spatial comparisons between the true and estimated density fields, and quantifies the improved accuracy in debris object motion predictions due to more accurate drag force models from density estimates. It is shown that there is an advantage to utilizing multiple debris objects instead of just one object. Although the work presented here explores the POEnKF performance when using information from only 16 debris objects, the research vision is to utilize information from all routinely observed debris objects. Overall, the filter demonstrates the ability to estimate density to within a threshold of accuracy dependent on measurement/sensor error. In the case of a geomagnetic storm, the filter is able to track the storm and provide more accurate density estimates than would be achieved using a simple exponential atmospheric density model or MSIS Atmospheric Model (when calm conditions are assumed).     

空间目标在天基光学探测中的特性分析与仿真

分析了空间目标的分布及几何特性,研究了空间目标光学特性与天基探测系统、太阳以及目标自身参数的关系,提出了空间目标光学特性仿真的思路,建立的天基空间目标光学特性分析系统可以计算并绘制相对距离、太阳相位角及目标星等变化曲线.由于很难获取准确的空间目标实际光度数据,文中提出了对仿真结果的验证方法.通过对仿真结果的分析,得出了天基空间目标光学探测的特点,为天基光学探测和识别的研究提供了参考.      

Procedure and methodologies for managing the risk of space object reentry

This paper proposes a procedure for managing the risk of reentering space objects and risk assessment methodologies used for the process. The proposed procedure comprises three phases encompassing the whole reentry stages of space objects. Mathematical models for assessing the impact risk of the reentering space objects by utilizing the information available during different risk management phases and the recommended risk analysis results for public communication are presented. The concept of the conditional casualty expectation is proposed as the metric representing the reentry risk and the method to compute its profile is introduced. A case study on the risk management procedure with the dataset on an actual reentry event is conducted to demonstrate the efficacy of the proposed procedure.     

Apparent rotation properties of space debris extracted from photometric measurements

Knowledge about the rotation properties of space debris objects is essential for the active debris removal missions, accurate re-entry predictions and to investigate the long-term effects of the space environment on the attitude motion change. Different orbital regions and object’s physical properties lead to different attitude states and their change over time.Since 2007 the Astronomical Institute of the University of Bern (AIUB) performs photometric measurements of space debris objects. To June 2016 almost 2000 light curves of more than 400 individual objects have been acquired and processed. These objects are situated in all orbital regions, from low Earth orbit (LEO), via global navigation systems orbits and high eccentricity orbit (HEO), to geosynchronous Earth orbit (GEO). All types of objects were observed including the non-functional spacecraft, rocket bodies, fragmentation debris and uncorrelated objects discovered during dedicated surveys. For data acquisition, we used the 1-meter Zimmerwald Laser and Astrometry Telescope (ZIMLAT) at the Swiss Optical Ground Station and Geodynamics Observatory Zimmerwald, Switzerland. We applied our own method of phase-diagram reconstruction to extract the apparent rotation period from the light curve. Presented is the AIUB’s light curve database and the obtained rotation properties of space debris as a function of object type and orbit.     

Probabilistic resident space object detection using archival THEMIS fluxgate magnetometer data

Recent progress in the detection of small space objects, at geosynchronous altitudes, through ground-based optical and radar measurements is demonstrated as a viable method. However, in general, these methods are limited to detection of objects greater than 10?cm. This paper examines the use of magnetometers to detect plausible flyby encounters with charged space objects using a matched filter signal existence binary hypothesis test approach. Relevant data-set processing and reduction of archival fluxgate magnetometer data from the NASA THEMIS mission is discussed in detail. Using the proposed methodology and a false alarm rate of 10%, 285 plausible detections with probability of detection greater than 80% are claimed and several are reviewed in detail.     

MCMC-Particle-based group tracking of space objects within Bayesian framework

With the intense increase in space objects, especially space debris, it is necessary to efficiently track and catalog the extensive dense clusters of space objects. As the main instrument for low earth orbit (LEO) space surveillance, ground-based radar system is usually limited by its resolution while tracking small space debris with high density. Thus, the obtained measurement information could have been seriously missed, which makes the traditional tracking method inefficient. To address this issue, we conceived the concept of group tracking. For group tracking, the overall tendency of the group objects is expected to be revealed, and the trajectories of individual objects are simultaneously reconstructed explicitly. According to model the interaction between the group center and individual trajectories using the Markov random field (MRF) within Bayesian framework, the objects’ number and individual trajectory can be estimated more accurately in the condition of high miss alarm probability. The Markov chain Monte Carlo (MCMC)-Particle algorithm was utilized for solving the Bayesian integral problem. Furthermore, we introduced the mechanism for describing the behaviors of groups merging and splitting, which can expand the single group tracking algorithm to track variable multiple groups. Finally, simulation of the group tracking of space objects was carried out to validate the efficiency of the proposed method.     

Dynamical evolution of high area-to-mass ratio objects in Molniya orbits

For special demands, some notable orbit types have been developed by human, including the Molniya orbits, which have a relatively high eccentricity up to about 0.7, and a period of 12 h. Considering that space debris with high area-to-mass ratio (A/M) has been discovered, such objects may also exist in Molniya orbits due to spacecraft and upper stages fragmentation events. However, there are not sufficient studies of the complex dynamical phenomena of such orbits. These studies can enrich the knowledge about the long-term evolution of these orbits, be helpful to propose uncatalogued objects observation and identification, and also set the protected region as well as active debris removal. In this paper, the characteristics of 2:1 resonance of Molniya satellite orbits are studied. A large set of numerical simulations, including all the relevant perturbations, is carried out to further investigate the main characteristics, and special attention is payed to the dynamical evolution of objects with high A/M, particularly affected by the direct solar radiation pressure. The long-term dynamical evolution of orbital elements, as well as the dependency of lifetime on the A/M value, is discussed.     

Fuzzy multi-criteria decision-making approach to prioritization of space debris for removal

As private companies and government space agencies begin to seriously consider the task of active space debris removal, it is becoming increasingly more important to determine the highest priority objects to deorbit. This work sets forth an approach for prioritization of space debris through the utilization of Multi-Criteria Decision-Making methodologies and fuzzy logic, as well as both quantitative and qualitative criteria. The proposed debris prioritization approach considers various criteria including the orbit, size, mass, pairwise and total collision probabilities, and decay timeframe of each debris object. The means of assigning attributes to each assessment criterion is discussed in detail. To determine the weighting scheme for the criteria, a questionnaire was prepared and shared with experts in the field of space situational awareness. The work examines over two thousand critical debris objects selected from the existing debris catalog with respect to these criteria. The quantified attributes for each debris object are then aggregated through the fuzzy versions of the Analytic Hierarchy Process and the Technique for Order Preference by Similarity to Ideal Solution. The results of the analysis identify high-priority debris objects for removal from Earth-bound orbits.     

基于概念空间学习认知的机器人目标识别方法

针对复杂环境中机器人多类目标识别通常所依托的原始特征空间中数据区分度低、难以直接表达高层次特征知识的挑战性问题,采用概念空间知识表达方法,通过多传感器数据融合与特征提取建立基本特征空间,并运用高斯混合模型表示目标的各种属性,形成具有高层知识特性的概念空间,在此基础上进行高层知识的概念学习,增强多类目标在概念空间中的可区分性.利用支持向量机作为机器人的分类器,实现针对室内环境的多类目标物体的准确识别.实验结果表明:该方法不但有效地获取和表达待识别目标的高层特征知识,而且能有效提高机器人的目标识别与环境感知能力,展现出优越的分类识别性能.     

Space Debris Mitigation in France,Germany, Italy and United Kingdom

The Space systems today provide growing benefits to enhance the quality of humankind. However, as a by-product, the orbiting objects inevitably leaves some debris which after 50 years of space activities represent a concern for all space agencies and manufacturers and operators. Since last year no international agreement was in place to mitigate the growing population of space debris objects. The successful result obtained at UN-COPUOS in 2007 and available in the OOSA web site, now gives to the public, a set of voluntary international guidelines that could, if adopted by each space fairing Country, help in maintaining the present space environment. More further steps are necessary in the future to define a legal and normative framework. The paper will present the seven established UN Space Debris guidelines as well as examples of the minimum steps to be carried out at national level to enable the UN-COPUOS to start the discussion of the legal aspect associated with the space debris issue.     

自由虚拟实景空间的构造

使用基于图像的绘制技术构造虚拟实景空间是目前虚拟现实领域研究的热点. 如何扩大自由度是虚拟实景空间需要解决的关键问题.自由虚拟实景空间是能够自由操纵的 虚拟实景空间. 提出同心球拼图的方法构造自由虚拟实景空间,能满足用户在自由漫游时俯 视和仰视的需要.另外在自由虚拟实景空间中引入超链的思想,通过对虚拟空间中虚拟对象 进行有效的组织,为用户提供丰富的空间操纵能力.试验结果表明,用户在自由虚拟实景空 间中能够自由地操纵虚拟空间.      

Uncertainty-aware Cube algorithm for medium-term collision risk assessment

The number of Earth orbiting objects is constantly growing, and some orbital regions are becoming risky environments for space assets of interest, which are increasingly threatened by accidental collisions with other objects, especially in Low-Earth Orbit (LEO). Collision risk assessment is performed by various methods, both covariance and non-covariance based. The Cube algorithm is a non-covariance-based method used to estimate the collision rates between space objects, whose concept consists in dividing the space in cubes of fixed dimension and, at each time instant, checking if two or more objects share the same cube. Up to now its application has been limited to the long-term scenarios of orbital debris evolutionary models, where considering the uncertainties is not necessary and impractical. Within operative contexts, instead, medium-term collision risk analysis may be an important task, in which the propagation-related uncertainties play a prominent role, but the timescale poses challenges for the application of standard covariance-based conjunction analysis techniques. In this framework, this paper presents an approach for the evaluation of the medium-term collision frequency for objects in LEO, called Uncertainty-aware Cube method. It is a modified version of the Cube, able to take the possible errors in the space objects’ position into account for the detection of the conjunctions. As an object’s orbit is propagated, the along-track position error grows more and more, and each object could potentially be in a different position with respect to the one determined by numerical propagation and, thus, in a different cube. Considering the uncertainties, at each time instant the algorithm associates more than one cube to each object and checks if they share at least one cube. If so, a conjunction is detected and a degree of confidence is evaluated. The performance of the method is assessed in different LEO scenarios and compared to the original Cube method.     

Feasibility analysis of LEO and GEO large space debris de/re-orbiting taking into account launch mass of spacecraft-collector and its configuration layout

Analysis of the efficiency of two basic strategies for de/re-orbiting large space debris objects to disposal orbits (DO) is given. Large objects in LEO are classified into groups with similar orbital inclinations and comprise primarily last stages of launch vehicles, in GEO vicinity the paper studies upper stages. Under the first de/re-orbiting variant, it is assumed a spacecraft-collector is equipped with several thruster de/re-orbiting kits (TDKs); one of them can be fixed on an object and is capable of de/re-orbiting an object to a DO independently of the collector. In the second variant, a collector operates as a space tug: transfers objects to a DO and then returns to the next objects in line. The authors study possible configuration layouts of collectors in LEO and near GEO. The available analogous projects are analyzed. The efficiency of both de/re-orbiting variants can be properly compared using the estimations of collector's dry mass and having at one's disposal the parameters of the maneuvers required for transfers between all objects in the group. As reasonable criteria of effectiveness, one can consider (separately or jointly) the launch mass of an equipped collector, its ΔV budget, and the required number of such active spacecraft. Two de/re-orbiting variants are compared in terms of these criteria via mass-energy diagrams constructed for each group of objects in both altitude regions. Analysis of these diagrams shows that low Earth orbits can be more efficiently cleaned under the first de-orbiting variant by using a two-stage space system consisting of an active spacecraft carrying TDKs. For GEO, it is expedient to choose the second re-orbiting variant using a single-stage spacecraft. Our analysis shows that LEO cleaning is an order of magnitude more expensive than that for GEO, hence the problem of LEO population should be given increased attention.     

空间碎片环境与碰撞预警仿真系统设计

在轨编目航天器数目已超过了9000,为了保证航天任务的顺利完成,必须对可能威胁到任务轨道的空间目标进行分析,文章首先对两行轨道根数和SGP4／SDP4轨道预报模型进行了分析,在此基础上建立了空间目标数据库及空间碎片环境与碰撞预警仿真和数据可视化系统。     

基于相控阵雷达波束篱笆的空间碎片数量与分布估计方法

随着载人航天与空间站等航天活动的增多,不能有效防护、也无法定期跟踪和编目的小尺寸(尤其是1～10 cm)碎片的危害越来越受到关注,这些碎片信息的获取依赖于统计采样技术.针对简化的相控阵雷达波束篱笆空间碎片探测模式,提出了一种采用统计技术估计空间碎片总数量以及高度和倾角分布的方法.将碎片穿越波束篱笆的过程用Poisson分布来建模,根据观测时段内穿越波束篱笆目标的平均到达率及测量的轨道高度和倾角数据来估计给定轨道高度范围或倾角范围内碎片的数量,进而得到碎片的总数量以及碎片数量随轨道高度或倾角的分布.在获取雷达散射截面信息时,该方法还可用于估计碎片数量随尺寸的分布.通过仿真实验验证了该方法的有效性.      

An adaptive threshold method for improving astrometry of space debris CCD images

Optical survey is a main technique for observing space debris, and precisely measuring the positions of space debris is of great importance. Due to several factors, e.g. the angle object normal to the observer, the shape as well as the attitude of the object, the variations of observed characteristics for low earth orbital space debris are distinct. When we look at optical CCD images of observed objects, the size and brightness are varying, hence it’s difficult to decide the threshold during centroid measurement and precise astrometry. Traditionally the threshold is given empirically and constantly in data reduction, and obviously it’s not suitable for data reduction of space debris. Here we offer a solution to provide the threshold. Our method assumes that the PSF (point spread function) is Gaussian and estimates the signal flux by a directly two-dimensional Gaussian fit, then a cubic spline interpolation is performed to divide each initial pixel into several sub-pixels, at last the threshold is determined by the estimation of signal flux and the sub-pixels above threshold are separated to estimate the centroid. A trail observation of the fast spinning satellite Ajisai is made and the CCD frames are obtained to test our algorithm. The calibration precision of various threshold is obtained through the comparison between the observed equatorial position and the reference one, the latter are obtained from the precise ephemeris of the satellite. The results indicate that our method reduces the total errors of measurements, it works effectively in improving the centering precision of space debris images.