The Multimission VICAR Planner: A Fielded Planning System for Scientific Data Analysis
The Multimission VICAR Planner (MVP) system is an AI planning system which constructs.
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The Multimission VICAR Planner (MVP) system is an AI planning system which constructs.
An interactive graphical proximity operations planning system was developed, which allows on-site design of efficient, complex, multiburn maneuvers in a dynamic multispacecraft environment. Maneuvering takes place in and out of the orbital plane. The difficulty in planning such missions results from the unusual and counterintuitive character of orbital dynamics and complex time-varying operational constraints. This difficulty is greatly overcome by visualizing the relative trajectories and the relevant constraints in an easily interpretable graphical format, which provides the operator with immediate feedback on design actions. The display shows a perspective bird's-eye view of a Space Station and co-orbiting spacecraft on the background of the Station's orbital plane. The operator has control over the two modes of operation: a viewing system mode, which enables the exporation of the spatial situation about the Space Station and thus the ability to choose and zoom in on areas of interest; and a trajectory design mode, which allows the interactive editing of a series of way points and maneuvering burns to obtain a trajectory that complies with all operational constraints. A first version of this display was completed. An experimental program is planned in which operators will carry out a series of design missions which vary in complexity and constraints.
An interactive, graphical proximity operations planning system was developed which allows on-site design of efficient, complex, multiburn maneuvers in the dynamic multispacecraft environment about the space station. Maneuvering takes place in, as well as out of, the orbital plane. The difficulty in planning such missions results from the unusual and counterintuitive character of relative orbital motion trajectories and complex operational constraints, which are both time varying and highly dependent on the mission scenario. This difficulty is greatly overcome by visualizing the relative trajectories and the relative constraints in an easily interpretable, graphical format, which provides the operator with immediate feedback on design actions. The display shows a perspective bird's-eye view of the space station and co-orbiting spacecraft on the background of the station's orbital plane. The operator has control over two modes of operation: (1) a viewing system mode, which enables him or her to explore the spatial situation about the space station and thus choose and frame in on areas of interest; and (2) a trajectory design mode, which allows the interactive editing of a series of way-points and maneuvering burns to obtain a trajectory which complies with all operational constraints. Through a graphical interactive process, the operator will continue to modify the trajectory design until all operational constraints are met. The effectiveness of this display format in complex trajectory design is presently being evaluated in an ongoing experimental program.
The Payload Planning System is for experiment planning on the International Space Station. The planning process has a number of different aspects which need to be stored in a database which is then used to generate reports on the planning process in a variety of formats. This process is currently structured as a 3-tier client/server software architecture comprised of a Java applet at the front end, a Java server in the middle, and an Oracle database in the third tier. This system presently uses CGI, the Common Gateway Interface, to communicate between the user-interface and server tiers and Active Data Objects (ADO) to communicate between the server and database tiers. This project investigated other methods and tools for performing the communications between the three tiers of the current system so that both the system performance and software development time could be improved. We specifically found that for the hardware and software platforms that PPS is required to run on, the best solution is to use Java Remote Method Invocation (RMI) for communication between the client and server and SQLJ (Structured Query Language for Java) for server interaction with the database. Prototype implementations showed that RMI combined with SQLJ significantly improved performance and also greatly facilitated construction of the communication software.
This paper describes a class of knowledge-based 'assistant' systems for space system planning. Derived from technology produced for the DARPA/USAF Pilot's Associate program, these assistant systems help the human planner by doing the bookkeeping to maintain plan data and executing the procedures and heuristics currently used by the human planner to define, assess, diagnose, and revise plans. Intelligent systems for Space Station Freedom assembly sequence planning and Advanced Launch System modeling will be presented as examples. Ongoing NASA-funded work on a framework supporting the development of such tools will also be described.
This paper describes the design of a model-based autonomous planning system that will enable robots to manage a space-borne chemical laboratory. In a model-based planning system, knowledge is encapsulated in the form of models at the various layers to support the predefined system objectives. Thus the model-based approach can be considered as an extended planning paradigm which is able to base its planning, control, diagnosis, repair, and other activities on a variety of objectives-related models. A System Entity Structure/Model Base framework is employed to support autonomous system design through the ability to generate a family of planning alternatives as well as to build hierarchical event-based control structures. The model base is a multilevel, multiabstraction, and multiformalism system organized through the use of system morphisms to integrate related models.
APGEN (Activity Plan GENerator - 314), a multi-mission planning tool, must interface with external software to vest serve its users. AP-GEN's original method for incorporating external software, the User-Defined library mechanism, has been very successful in allowing APGEN users access to external software functionality.
The planning processes for the International Space Station (ISS) Program are quite complex. Detailed mission planning for ISS on-orbit operations is a distributed function. Pieces of the on-orbit plan are developed by multiple planning organizations, located around the world, based on their respective expertise and responsibilities. The "pieces" are then integrated to yield the final detailed plan that will be executed onboard the ISS. Previous space programs have not distributed the planning and scheduling functions to this extent. Major ISS planning organizations are currently located in the United States (at both the NASA Johnson Space Center (JSC) and NASA Marshall Space Flight Center (MSFC)), in Russia, in Europe, and in Japan. Software systems have been developed by each of these planning organizations to support their assigned planning and scheduling functions. Although there is some cooperative development and sharing of key software components, each planning system has been tailored to meet the unique requirements and operational environment of the facility in which it operates. However, all the systems must operate in a coordinated fashion in order to effectively and efficiently produce a single integrated plan of ISS operations, in accordance with the established planning processes. This paper addresses lessons learned during the development of these multiple distributed planning systems, from the perspective of the developer of one of the software systems. The lessons focus on the coordination required to allow the multiple systems to operate together, rather than on the problems associated with the development of any particular system. Included in the paper is a discussion of typical problems faced during the development and coordination process, such as incompatible development schedules, difficulties in defining system interfaces, technical coordination and funding for shared tools, continually evolving planning concepts/requirements, programmatic and budget issues, and external influences. Techniques that mitigated some of these problems will also be addressed, along with recommendations for any future programs involving the development of multiple planning and scheduling systems. Many of these lessons learned are not unique to the area of planning and scheduling systems, so may be applied to other distributed ground systems that must operate in concert to successfully support space mission operations.
The planning processes for the International Space Station (ISS) Program are quite complex. Detailed mission planning for ISS on-orbit operations is a distributed function. Pieces of the on-orbit plan are developed by multiple planning organizations, located around the world, based on their respective expertise and responsibilities. The pieces are then integrated to yield the final detailed plan that will be executed onboard the ISS. Previous space programs have not distributed the planning and scheduling functions to this extent. Major ISS planning organizations are currently located in the United States (at both the NASA Johnson Space Center (JSC) and NASA Marshall Space Flight Center (MSFC)), in Russia, in Europe, and in Japan. Software systems have been developed by each of these planning organizations to support their assigned planning and scheduling functions. Although there is some cooperative development and sharing of key software components, each planning system has been tailored to meet the unique requirements and operational environment of the facility in which it operates. However, all the systems must operate in a coordinated fashion in order to effectively and efficiently produce a single integrated plan of ISS operations, in accordance with the established planning processes. This paper addresses lessons learned during the development of these multiple distributed planning systems, from the perspective of the developer of one of the software systems. The lessons focus on the coordination required to allow the multiple systems to operate together, rather than on the problems associated with the development of any particular system. Included in the paper is a discussion of typical problems faced during the development and coordination process, such as incompatible development schedules, difficulties in defining system interfaces, technical coordination and funding for shared tools, continually evolving planning concepts/requirements, programmatic and budget issues, and external influences. Techniques that mitigated some of these problems will also be addressed, along with recommendations for any future programs involving the development of multiple planning and scheduling systems. Many of these lessons learned are not unique to the area of planning and scheduling systems, so may be applied to other distributed ground systems that must operate in concert to successfully support space mission operations.
This paper presents some new approaches which are required for a better adequacy of Mission Planning Systems. In particular, the performance flexibility and genericity issues are discussed based on experience acquired through various Mission Planning systems developed by Matra Marconi Space.
The Space Exploration Initiative of the United States will make great demands upon NASA and its limited resources. One aspect of great importance will be providing for autonomous (unmanned) operation of vehicles and/or subsystems in space flight and surface exploration. An additional, complicating factor is that much of the need for autonomy of operation will take place under conditions of great uncertainty or ambiguity. Issues in developing an autonomous collision avoidance subsystem within a path planning system for application in a remote, hostile environment that does not lend itself well to remote manipulation by Earth-based telecommunications is addressed. A good focus is unmanned surface exploration of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. Four major issues addressed are (1) avoidance of a fuzzy moving obstacle; (2) backoff from a deadend in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system. Examples of the need for collision avoidance by an autonomous rover vehicle on the surface of Mars with a moving obstacle would be wind-blown debris, surface flow or anomalies due to subsurface disturbances, another vehicle, etc. The other issues of backoff, sensor fusion, and adaptive learning are important in the overall path planning system.
The basic objective of the Space Station (SS) Mission Planning System (MPS) Development Study was to define a baseline Space Station mission plan and the associated hardware and software requirements for the system. A detailed definition of the Spacelab (SL) payload mission planning process and SL Mission Integration Planning System (MIPS) software was derived. A baseline concept was developed for performing SS manned base payload mission planning, and it was consistent with current Space Station design/operations concepts and philosophies. The SS MPS software requirements were defined. Also, requirements for new software include candidate programs for the application of artificial intelligence techniques to capture and make more effective use of mission planning expertise. A SS MPS Software Development Plan was developed which phases efforts for the development software to implement the SS mission planning concept.
The design and functions of ALEPS (Automated Logistics Element Planning System) is a computer system that will automate planning and decision support for Space Station Freedom Logistical Elements (LEs) resupply and return operations. ALEPS provides data management, planning, analysis, monitoring, interfacing, and flight certification for support of LE flight load planning activities. The prototype ALEPS algorithm development is described.
The complex and diverse nature of the pay load operations to be performed on the Space Station requires a robust and flexible planning approach, and the proper software tools which tools to support that approach. To date, the planning software for most manned operations in space has been utilized in a centralized planning environment. Centralized planning is characterized by the following: performed by a small team of people, performed at a single location, and performed using single-user planning systems. This approach, while valid for short duration flights, is not conducive to the long duration and highly distributed payload operations environment of the Space Station. The Payload Planning System (PPS) is being designed specifically to support the planning needs of the large number of geographically distributed users of the Space Station. This paper problem provides a general description of the distributed planning architecture that PPS must support and describes the concepts proposed for making PPS available to the Space Station payload user community.
This viewgraph representation presents an overview of the mission planning process involving distributed operations (such as the International Space Station (ISS)) and the computer hardware and software systems needed to support such an effort. Topics considered include: evolution of distributed planning systems, ISS distributed planning, the Payload Planning System (PPS), future developments in distributed planning systems, Request Oriented Scheduling Engine (ROSE) and Next Generation distributed planning systems.
A C-based artificial intelligence (AI) development effort which is based on a software tools approach is discussed with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching, and blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) Shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May of 1987 and will be used for operations scheduling of the Explorer Platform in Nov. of 1991.
The international character of future manned space missions will compel the involvement of several international space agencies in mission planning tasks. Additionally, the community of users requires a higher degree of freedom for experiment planning. Both of these problems can be solved by a decentralized mission planning concept using the so-called 'envelope method,' by which resources are allocated to users by distributing resource profiles ('envelopes') which define resource availabilities at specified times. The users are essentially free to plan their activities independently of each other, provided that they stay within their envelopes. The new developments were aimed at refining the existing vague envelope concept into a practical method for decentralized planning. Selected critical functions were exercised by planning an example, founded on experience acquired by the MSCC during the Spacelab missions D-1 and D-2. The main activity regarding future mission planning tasks was to improve the existing MSCC mission planning system, using new techniques. An electronic interface was developed to collect all formalized user inputs more effectively, along with an 'envelope generator' for generation and manipulation of the resource envelopes. The existing scheduler and its data base were successfully replaced by an artificial intelligence scheduler. This scheduler is not only capable of handling resource envelopes, but also uses a new technology based on neuronal networks. Therefore, it is very well suited to solve the future scheduling problems more efficiently. This prototype mission planning system was used to gain new practical experience with decentralized mission planning, using the envelope method. In future steps, software tools will be optimized, and all data management planning activities will be embedded into the scheduler.
Recently, many expert systems were developed in a LISP environment and then ported to the real world C environment before the final system is delivered. This situation may require that the entire system be completely rewritten in C and may actually result in a system which is put together as quickly as possible with little regard for maintainability and further evolution. With the introduction of high performance UNIX and X-windows based workstations, a great deal of the advantages of developing a first system in the LISP environment have become questionable. A C-based AI development effort is described which is based on a software tools approach with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching and a blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May 1987 and will be used for operations scheduling of the Explorer Platform in November 1991.