Experiences applying formal approaches in the development of swarm-based space exploration systems

NASA is researching advanced technologies for future exploration missions using intelligent swarms of robotic vehicles. One of these missions is the Autonomous Nano-Technology Swarm (ANTS) mission that will explore the asteroid belt using 1,000 cooperative autonomous spacecraft. The emergent properties of intelligent swarms make it a potentially powerful concept, but at the same time more difficult to design and ensure that the proper behaviors will emerge. NASA is investigating formal methods and techniques for verification of such missions. The advantage of using formal methods is the ability to mathematically verify the behavior of a swarm, emergent or otherwise. Using the ANTS mission as a case study, we have evaluated multiple formal methods to determine their effectiveness in modeling and ensuring desired swarm behavior. This paper discusses the results of this evaluation and proposes an integrated formal method for ensuring correct behavior of future NASA intelligent swarms.     

Object-oriented modelling for spacecraft dynamics: Tools and applications

The development process for spacecraft control systems relies heavily on modelling and simulation tools for spacecraft dynamics. For this reason, there is an increasing need for adequate design tools in order to cope efficiently with tightening budgets for space missions. The paper discusses the main issues related to the modelling and simulation of satellite dynamics for control purposes, and then presents an object-oriented modelling framework, implemented as a Modelica library. The proposed approach allows a unified approach to a range of problems spanning from initial mission design and actuator sizing phases, down to detailed closed-loop simulation of the control system, including realistic models of sensors and actuators. It also promotes the reuse of modelling knowledge among similar missions, thus minimizing the design effort for any new project. The proposed framework and the Modelica library are demonstrated by several illustrative case studies.     

基于DAMPSO算法的USVs集群攻击任务规划研究

现代防御技术的迅速发展使得水面舰艇的攻击效果大大下降,水面无人舰艇自主编队集群攻击技术已经成为未来海战的关键技术之一,多水面无人舰艇之间的任务规划是保证无人舰艇顺利、高效完成任务的关键。将水面无人舰艇集群攻击任务规划问题看成是多约束的任务分配过程,建立任务规划模型,提出了基于分布式拍卖机制的粒子群优化算法,该算法结合分布式拍卖机制对粒子群优化算法的粒子初始化和寻优过程进行改进,使得粒子既符合任务的约束条件,又保持了多样性,避免粒子在寻优过程中陷入局部最优。仿真结果表明应用分布式拍卖机制粒子群优化算法得到的方案不仅完全满足水面无人舰艇集群攻击任务的要求,而且比传统粒子群优化算法和其他群体智能算法具有更好的收敛性。     

ATOS — An AI-based space mission operations system

Artificial Intelligence is generally recognised as one of the key technologies for future spaceflight, and a number of ambitious applications for on-board use have been proposed already. Such applications still require a good deal of basic research and development, but on-ground applications could make an impact already in the medium term, and will for some time represent the major part of AI use for space missions.

ESA has started the development of a future integrated and mission-independent spacecraft control data processing system called the Advanced Technology Operations System (ATOS) at the European Space Operations Centre, which will employ artificial intelligence techniques in supporting the operations staff during all mission preparation and implementation phases, in order to cope reliably with complex mission operations and to achieve optimal efficiency in the use of human resources.

ATOS will consist of a number of knowledge based software modules, such as

• Automated mission planning

• Automated operations preparation

• Computer assisted operations

• Advanced operator training,

centred around a Mission Information Base configured for the particular satellite mission, the common data repository for all information required to conduct the mission and operate the spacecraft.

The Mission Information Base will, in addition to numerical data presently found in conventional spacecraft control systems, contain a large amount of ‘knowledge’ about the spacecraft and its mission, which is currently available only in paper documents or embedded in software. It will be implemented as a physically and logically distributed set of databases each representing a particular field of mission information, such that the knowledge can be dynamically shared between different intelligent spacecraft control applications.     

Extension of a ground control interface for swarms of Small Drones

Although the technology for fully autonomous swarms of robots is rapidly progressing, the human operator will continue to play an important role during any swarming mission due to safety, monitoring and control constraints. In this paper, we present the set of features that a Ground Control Interface (GCI) must incorporate to allow monitoring, control and safety of outdoor missions with a swarm of Small Drones (drones of less than 1 kg). We propose a new extension to a widely used GCI by incorporating those features and we demonstrate its usage on a swarm of 10 Small Drones flying outdoor.     

Low-cost flights in the Jovian system using Tisserand coordinates

Real ephemeris have been used to develop an algorithm for overcoming the “paradox of solo perturbations” for mass calculations in the simulation of gravity assist maneuvers in the Jovian system to approach to one of its satellites. The zone of excessive total ionizing dose is bypassed on the upper corridor of the Tisserand—Poincaré graph. Simultaneously, we perform a low-cost reduction of the asymptotic speed of the spacecraft required for approaching. These scenarios can be synthesized when the model of a restricted three-body problem is replaced by a pair of restricted three-body problems and the problem of four or more bodies. To derive a criterion that launches a given model, new Tisserand coordinates are introduced. Their usage shows that gravity cross-maneuvers are required at an early stage of the reduction of the spacecraft’s orbital period. As a result, a reasonable increase in the mission’s duration can be replaced by a sharp decline in the resulting ionizing dose and scenarios (comfortable with respect to this parameter and efficient in terms of the characteristic velocity consumption) for tours in the Jovian system (less than 70 krad for a standard protection of the Galileo spacecraft of 8 mm Al). This provides a considerable gain in the spacecraft payload for missions to Jupiter and makes it possible to enhance the reliability of the scientific equipment.

     

Progressive autonomy: a method for gradually introducing autonomy into space missions

This paper presents a method under development for introducing autonomy and agent-based software into future space- and ground-based missions while both reducing the risk of mission failures and gaining the confidence and support of mission management and principal investigators (PIs). This is being done using a mechanism to support dynamic agent-community evolution (e.g., agents adapting to community changes, agents joining a community, or agents leaving a community). This dynamic capability of agents is necessary to achieve what we call ‘‘progressive autonomy,’’ which will allow dynamic modification of satellite systems using agent migration to update and modify spacecraft capabilities on an as-needed basis, as well as allow the introduction of mission management and autonomy into existing missions. This paper will also address an application of progressive autonomy through spectral analysis automation (SAA). The long-term fully realized SAA system will be a multiagent system designed to provide automated support for two major functions: (1) the automatic remote filtering (onboard a spacecraft or robotic device) of spectral image data based on PI guidance, goals, and science agenda and (2) the packing and transmission of the selected spectral data to the PI for further processing. Additionally, the innovative multiagent-based infrastructure for the SAA can be generalized in such a way as to enable it to support the type of progressive autonomy that will be needed to support an adaptive and growing autonomous behavior for other spacecraft or robotic subsystems.     

航天器任务调度模型、算法与通用求解技术综述

针对航天器任务调度大规模、复杂化的新常态和灵活组网、快速响应的新要求, 综述了航天器任务调度模型、算法与通用求解技术的发展现状. 首先, 基于遥感卫星、中继通信卫星、导航卫星和航天测控等航天器任务, 从任务排序模型和时间窗口分配模型两个角度出发, 揭示了不同航天器任务调度模型的决策形式和共性特征, 阐明提升模型兼容性、适用性的必要性. 其次, 基于启发式算法、精确求解算法和元启发式算法, 探讨了航天器任务调度算法的适用模型与编码特色, 指明“算法?模型”解耦、算法深度融合的重要性. 在此基础上, 介绍了CPLEX、STK/Scheduler、Europa2和“高景一号”任务调度分系统等航天器任务调度通用求解技术的模型、算法与主要功能, 说明我国自主研发通用求解技术的必要性和新的应用思路. 最后, 指出了开发航天器任务调度统一化建模语言、打造算法库与测试集等未来航天器任务调度研究的新方向.     

基于当代学习离散粒子群算法的多机器人任务分配*

针对多机器人协同控制中的任务分配问题,首先综合考虑机器人完成任务的效率、机器人自身能力以及任务本身性质各因素,建立了多机器人任务分配的数学模型。而后提出一种基于当代学习机制的离散粒子群算法进行高效求解,该算法设计了准确的粒子运动方程,并加入扰动算子保持粒子多样性,使其迅速跳出局部最优,增加了算法空间探索能力。实验结果表明：在小规模任务数情况下,算法能精确寻到最优,稳定性表现极佳且优于现有算法。在中大规模任务数情况下算法也表现出强寻优能力,实验验证了模型的合理性和算法的优越性。     

Hybrid multi-objective optimisation for concurrent activities consolidating two docked spacecraft

Rendezvous and docking (RVD) is a key technology for performing complicated space missions. After an RVD process, several activities are executed to consolidate two docked spacecraft into a spacecraft complex, and this task phase is referred to as a spacecraft consolidation mission. It can save the mission time to execute these activities in parallel, but a high degree of parallelism could result in a disordered execution profile and many violations of precedence constraints. To solve this contradiction, a hybrid multi-objective optimisation approach is proposed. The precedence requirements within each activity are satisfied using an encoding and scheduling process, while the precedence requirements between different activities are treated by adding release time variables. A compact-execution index is designed to express the preference of an orderly and compact execution profile. Furthermore, a multi-objective hybrid-encoding genetic algorithm is employed to find optimal solutions. Finally, the proposed approach is demonstrated for a numerical example. The results show that optimal solutions satisfying precedence requirements both within each activity and between different activities are successfully obtained, and the trade-off between saving mission time and obtaining an orderly and compact execution profile can be effectively made. The performance of the proposed method is validated by comparison with two other multi-objective genetic algorithms.     

A Framework for Simulation and Testing of UAVs in Cooperative Scenarios

Today, Unmanned Aerial Vehicles (UAVs) have deeply modified the concepts of surveillance, Search&Rescue, aerial photogrammetry, mapping, etc. The kinds of missions grow continuously; missions are in most cases performed by a fleet of cooperating autonomous and heterogeneous vehicles. These systems are really complex and it becomes fundamental to simulate any mission stage to exploit benefits of simulations like repeatability, modularity and low cost. In this paper a framework for simulation and testing of UAVs in cooperative scenarios is presented. The framework, based on modularity and stratification in different specialized layers, allows an easy switching from simulated to real environments, thus reducing testing and debugging times, especially in a training context. Results obtained using the proposed framework on some test cases are also reported.     

Mexar2: AI Solves Mission Planner Problems

Deep-space missions carry an ever larger set of different and complementary onboard payloads. Each payload generates data, and synthesizing it for optimized downlinking is one way to reduce the ratio of mission costs to science return. This is the main role of the Mars-Express scheduling architecture (Mexar2), an Al-based tool in daily use on the Mars-Express mission since February 2005. Mexar2 supports space mission planners continuously as they plan data downlinks from the spacecraft to Earth. The tool lets planners work at a higher abstraction level while it performs low-level, often-repetitive tasks. It also helps them produce a plan rapidly, explore alternative solutions, and choose the most robust plan for execution. Additionally, planners can analyze any problems over multiple days and identify payload overcommitments that cause resource bottlenecks and increase the risk of data losses. Mexar2 has significantly increased the data return over the whole Mars-Express mission duration. It's effectively become a work companion for mission planners at the European Space Agency's European Space Operations Center (ESOC) in Darmstadt, Germany.     

On-board autonomy, EURECA experience and requirements for future space missions

The paper describes, after a basic definition of on-board autonomy, the on-board autonomous mission control capabilities used during the EURECA mission for nominal operations and fault management and related experiences. It also covers autonomy enhancements required for future highly productive missions. These are functionalities in relation to on-board mission planning, use of intelligent sub-system elements, “off-line” test capabilities and adaptive fault management.

EURECA, an unmanned retrievable multi-disciplinary science laboratory has successfully flown an 11-month mission in a 500 km, 28 deg. inclination orbit in the period August 1992 to June 1993. It was launched and brought back to earth by Space Shuttle flights STS46 and STS57 respectively. The complex spacecraft was operated by ESOC, in continuous productive mode, with less than 6% ground on-line contact, in a highly on-board autonomous mode. Its mission products encompassed all types of continuously produced scientific data, processed materials and biological samples, and a significant number of technological demonstrations.     

An overview of small satellites in remote sensing*

This article gives a global overview of some aspects of small satellite developments since the launch of Sputnik‐1 50 years ago. These developments are offering new opportunities for remote sensing.

The earliest satellites were small but, as time went on, the satellites that were flown were developed to serve several different projects and they became larger and more expensive and took a long time to design, build and be launched. One of the extreme examples was Envisat. For these large satellites compromises often had to be made between different objectives and different instruments. A failure of the whole system meant the death of many different projects.

The future is likely to see more small satellites, each of which is dedicated to a particular mission objective and carries a single instrument. Through this approach more and more countries around the world are becoming involved in Earth observation from space, not just in using the data from the major established systems but also in constructing their own systems.

There were some small, low‐cost satellites in the early days, but they were overlooked or considered toys by the space community. The first microsatellites were built by enthusiasts of the amateur radio community and launched in the early 1960s. The invention/introduction of the microprocessor in the 1970s represented a quantum jump for the onboard capabilities of a spacecraft. This technology introduction represented a prime catalyst in the development of microsatellites since it enabled small physical structures in support of sophisticated data handling applications. The engineering of microsatellites, which emerged in the early 1980s, took a radical change of approach from the custom design of traditional spacecraft, namely a design‐to‐capability scheme to achieve cost reductions by focusing on available, and existing technologies using a general purpose bus and ‘off‐the‐shelf’ components and instruments.

The new approach of small satellite design was pioneered by Surrey Satellite Technology Ltd (SSTL) of Surrey University, UK. SSTL's lead has now been followed by various companies and space agencies throughout the world. A key feature of this work is the development of microsatellite technology transfer programmes, providing partnerships and on‐the‐job training of engineers and scientists of foreign national organizations in cooperative programmes – in particular to those who were not in a position to start or afford their own space projects – to participate in the development of their own microsatellites.

In addition to discussing these developments, this article also covers small satellite classification, small satellite initiatives in the USA, small satellite development in the rest of the world, some aspects of the technology and applications of small satellites, and small satellites developed by universities, particularly the CubeSats programme.

Today, small satellites are changing the economics of space. These spacecraft embrace cutting edge Commercial Off‐The‐Shelf (COTS) technology, permitting novel and less‐expensive ways to perform meaningful observation missions, although there are various technical challenges. There are several synthetic aperture radar (SAR) and hyperspectral imaging missions on small satellites in operation and in planning.     

Full-state prescribed performance pose tracking of space proximity operations with input saturation

This paper investigates the relative position tracking and attitude synchronization control for spacecraft close-range proximity missions with input saturation and model uncertainties. A robust saturated relative motion controller is proposed for this purpose. Prescribed performance functions are designed to guarantee the transient and steady-state response of the system and the full-state constraints. Then, a nonlinear disturbance observer is developed to estimate the lumped disturbance that comprises the effects of parametric uncertainties and kinematic couplings. At the same time, a linear compensator system is incorporated into the controller design to deal with the control input saturation. Finally, it can be proved via the Lyapunov theory that the closed-loop system is uniformly ultimately bounded stable. Simulation results on the spacecraft close-range rendezvous and docking mission validate the effectiveness of the proposed control approach.     

Monitoring active volcanism with the Autonomous Sciencecraft Experiment on EO-1

The ability to monitor and rapidly react to remote detection of volcanic activity has been greatly improved through use of the Autonomous Sciencecraft Experiment (ASE), an advanced software application installed on a spacecraft in Earth orbit. ASE is a NASA New Millennium Program experiment demonstrating science-driven autonomous command and control of a spacecraft. Flying on the Earth Observing-1 (EO-1) spacecraft, ASE successfully detected thermal emission from the Mt. Erebus lava lake on 7 May 2004, having analyzed a Hyperion hyperspectral data product on board the spacecraft. EO-1 was re-tasked by ASE to obtain a follow-up observation 7 h later and sent a notification of detection of volcanic activity to the ground. The entire process was carried out autonomously. Initial acquisition to receipt on the ground of the positive detection took less than 3 h, a process that without ASE would have taken weeks. The ASE Thermal Classifier has detected several styles of effusive volcanic activity: active lava lakes, pahoehoe flow fields, open channel flows and lava domes. ASE successfully demonstrated that science-driven spacecraft operation greatly enhances science return per returned byte through the identification of the most valuable data, allowing prioritization of downlink products and the discarding of null data sets. This technology has applications on missions elsewhere in the solar system. Modified thermal classifiers can be used for detecting and monitoring active volcanism on the jovian satellite Io, the neptunian moon Triton, and searching for active volcanism on Mars and icy satellites. The success of ASE is an incentive for future instrument and mission designers to consider on-board data-processing requirements (especially data storage capacity, number of processors and processor speed, and RAM) in order to take advantage of this flight-proven technology.     

Distributed Service-Based Cooperation in Aerial/Ground Robot Teams Applied to Fire Detection and Extinguishing Missions

This paper presents a system for the coordination of aerial and ground robots for applications such as surveillance and intervention in emergency management. The overall system architecture is described. An important part for the coordination between robots is the task allocation strategy. A distributed market-based algorithm, called S + T, has been developed to solve the multi-robot task allocation problem in applications that require cooperation among the robots to accomplish all the tasks. Using this algorithm, robots can provide transport and communication relay services dynamically to other robots during the missions. Moreover, the paper presents a demonstration with a team of heterogeneous robots (aerial and ground) cooperating in a mission of fire detection and extinguishing.     

基于可重构技术的航天器数据管理系统研究

研究了一种改进的可跨平台使用的航天器数据管理系统,采用这种系统设计的航天器能够在出现故障或飞行任务发生改变时通过硬件重构完成飞行任务.在此基础上利用FPGA芯片结合SOPC(system on the programmable chip,可编程片上系统)技术,设计了一种新型航天器数据管理系统.