| ||||||||||||||||||||||||||||||||||||||||
| SC Domain | Related Papers | Issues | Satellite Specification | Application Scenario | I-Psc | Links |
The Satellite Constellation Domain
|
The satellites' constellation domain consists of a group of low-Earth orbiting satellites that have cross-link communication
capability, each carrying nearly the same suite of instruments. Each satellite receives high-level goals from
ground station operators, or other satellites. Then, it will perform its own planning by decomposing a goal into a set of sub-goals to be achieved with its onboard subsystems (satellites' resources) and in cooperation with other satellites.
A wide variety of missions can be better implemented with satellites working together to meet a single objective. Reasons cited for using constellations include lower mission cost, the need for coordinated science and special coverage of survey requirements. For example storms and other phenomena observed from multiple angles can be used to generate 3-D views; or a cluster of satellites flying in formation and working together can form a virtual lens hundreds of miles across. |
Design generated via AVM Dynamics tool. |
|
However the most widely used application of satellite constellations is for reasons of extended area coverage. Low earth orbiting constellations such as Globalstar use dozens of satellites to provide continuous global or near-global coverage. The GPS system uses a constellation to provide global coverage and spatial diversity of the multiple satellites in view. Earth mapping missions can use multiple satellites to shorten the time between successive observations of the same area. NASA is planning missions of up to 100 satellites for magnetosphere research with orbits nearly as distant as the moon. A single-satellite approach would require many years of data collection to match what the constellation can survey in a short amount of time. |
|
| Zetocha, P., Self, L., Wainwright, R., Burns, R., Brito, M. and Surka, D. (2000). Commanding and Controlling Satellite Clusters. IEEE Intelligent Systems 15(1):8-13. |
| Summary: presents a proposal of satellite constellation control based on three principal technologies: ObjectAgent architecture, the Spacecraft Command Language (SCL) and CASPER (Continuous Activity Scheduling Planning Execution and Replanning). Roles of each of these components are discussed during the development of spacecraft and cluster managers. Functions of cluster managers are listed as: command and control, cluster data management, formation flying and fault management. Such functions are detailed, as for example, to determine what information the cluster manager should keep in its database. Types of ground system commands are also discussed (satellite-assigned and no-assigned commands) and related to the problem of autonomy in the last case. Finally a summary about the TechSat 21 testbed (system for operation simulations) is presented. |
|
Richards, R., Houlette, R. and Mohammed, J. (2001). Distributed Satellite Constellation Planning and Schedulling. Proceedings of 14th FLAIRS Conference, Key West, Florida, USA. |
| Summary: presents a distributed coordination architecture (D-SpaCPlanS) to constellations, which intends to minimise the reliance of the whole system on any single component. The architecture is based on HTN planning methods, also presenting a reactive component. The principal idea is to spread authority and responsibility to minimise the impact of changes into the constellation and also allow a self-reorganisation to adapt to such changes. The abstract design of satellites is discussed and the principal components listed as: social coordinator (hierarchy management), group manager (take orders and pass them, local P/S (local deliberative and reactive planning and control) and local database (repository for local information). |
|
Verfaillie, G., Garcia, F. and Peret, L. (2003). Deployment and Maintenance of a Constellation of Satellites: a Benchmark. Proceedings of 13th International Conference on Automatic Planning & Scheduling, Trento, Italy. |
| Summary: deals with the deployment and maintenance of constellations as a sequential decision problem under uncertainty , using the Markov Decision Process framework to formulate such a problem. The goal is to minimise over a given timeline the sum of unavailability costs. This formulation does not prejudge the use of any specific solving approach, so that several approaches are canalised and classified in three categories: knowledge-based (expert or case-based systems), model-based (planning or sequential decision making) and simulation-based; |
|
Barrett, A. (1999). Autonomy Architectures for a Constellation of Spacecraft. Proceedings of 5th International Symposium on AI, Robotics and Automation for Space, Noordwijk, The Netherlands. |
| Summary: analyses architectures for constellations based on four components: mission manager, planner/scheduler, executive/diagnostician and reactive controller. Among the features of these components, the paper discusses the idea of varying the constellation's level of autonomy by varying the abstractness of the mission profile (part of mission manager). The architectures are master/slave coordination, teamwork and peer-to-peer coordination. Communication is the principal feature discussed, together with knowledge boundaries. In brief architectures are characterised via the use components by the satellites, which give more or less autonomy to them; |
|
Damiani, S., Verfaillie, G. and Charmeau, M. (2005). An Earth Watching Satellite Constellation: How to Manage a Team of Watching Agents with Limited Communications. Proceedings of 4th International Joint Conference on Autonomous Agents and Multiagent Systems, Utrecht, The Netherlands. |
| Summary: presents a detailed domain related to watching missions (volcanic eruptions and forest fires). Then a proposal of anytime reasoning mechanism is discussed to deal with the problem of constellation management. Three architectures are compared in terms of coordination/communication: strong coordination (more control communication to update some activity status), weak coordination (only initial control communication to setup the activities) and no coordination (no control communication). |
|
Surka, D., Brito, M. and Harvey, C. (2001). The Real-Time ObjectAgent Software Architecture for Distributed Satellite systems. Proceedings of IEEE Aerospace Conference. |
| Summary: discusses the implementation of a software to support the development of satellite constellations control. The two principal features of this software is a messaging architecture approach to agent-to-agent communication and the idea of skills that enable agents to be dynamically added to a system to improve the system capabilities or recover from a failure. AI techniques are not built in to the software core, however they can be incorporated at. The paper also presents a technical discussion about the implementation of such a software in two different platforms: Matlab and C++. Operational system and hardware are also commented. |
|
Zetocha, P. and Brito, M. (2001). Development of a Testbed for Distributed Satellite Command and Control. Proceedings of the IEEE Aerospace Conference. |
| Summary: discusses a testbed for satellite constellations based on three major components: the ground system, the flight system and the simulation environment. The paper gives an explanation about the cluster manager, principal component of the flight system detailing the functions of command and control, constellation data management, formation flying and fault management. |
|
Mohammed, J. (2001). Mission Planning for a Formation-Flying Satellite Cluster. Proceedings of 14th International FLAIRS Conference, Key West, Florida, USA. |
| Summary: lists some advantages of constellations over single large satellites and describes some planning and schedule requirements/goals for this domain. The architecture proposed employs a dynamic hierarchical social organisation, which plans at three levels of abstraction: constellation, clusters and individual satellites. The paper details the activities of each of these levels. Details about the activity model (resources required, conditions and constraints) and an optimisation algorithm (constructive and iterative repair techniques) are also given. In brief, an initial schedule that satisfies all constraints is built up and the iterative repair technique then iteratively reduces the number of resource contention conflicts by selecting observations to be adjusted or removed. |
|
Breger, L., Ferguson, P., How, J., Thomas, S., McLoughlin, T. and Campbell, M. (2003). Distributed Control of Formation Flying Spacecraft Built on OA, MIT, Cambridge, MA |
| Summary: presents extensions of some guidance and control algorithms for satellites formation flying. |
|
Satellite's Resources
|
Satellite's Communication Schema |
|
Geostationary satellites (GEO) are spacecrafts that are positioned at an exact height above the earth (about 36000 Km). At this height they rotate around the earth at the same speed as the earth rotates around its axis, so in effect remaining stationary above a point on the earth (normally directly overhead the equator). A set of 3 GEO satellites can cover the whole Earth surface, providing a constant channel of communication to low rate communication, such as phenomenon alarms. Differently, the transmission of observation requests and data is only possible via the tracking stations and specific time windows, as discussed later. We are considering that the solar panels are able to supply the battery during 12 hours a day. The others 12 hours the satellite must "survive" with the current charge of the battery. It is important to note the dependency between memory load and battery charge. Observations consume energy and memory and because downloading produces memory, by releasing memory space, but consumes energy. |
||
is an multiagent planning application that intends to evaluate the use of the I-X architecture to the development of a command and control sytem for satellite constelations. Psc is the acronym of the Pisces Constellation, set of stars better visualised during the month of November when the motivations for this project have emerged. I-X is an issue-handling workflow style of architecture, with reasoning and functional capabilities provided as plug-ins. Also via plug-ins it allows for sophisticated management of the internal model representations. I-X agents may be recursively or fractally composed, and may interwork with other processing cells or architectures. The following concepts are going to be tested in this project: |
|