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An Autonomous Spacecraft Agent Prototype

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Abstract

This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. The architecture supports challenging requirements of the autonomous spacecraft domain not usually addressed in mobile robot architectures, including highly reliable autonomous operations over extended time periods in the presence of tight resource constraints, hard deadlines, limited observability, and concurrent activity. A hybrid architecture, NMRA integrates traditional real-time monitoring and control with heterogeneous components for constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration. Novel features of this integrated architecture include support for robust closed-loop generation and execution of concurrent temporal plans and a hybrid procedural/deductive executive.

We implemented a prototype autonomous spacecraft agent within the architecture and successfully demonstrated the prototype in the context of a challenging autonomous mission scenario on a simulated spacecraft. As a result of this success, the integrated architecture has been selected to fly as an autonomy experiment on Deep Space One (DS-1), the first flight of NASA';s New Millennium Program (NMP), which will launch in 1998. It will be the first AI system to autonomously control an actual spacecraft.

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References

  • Ahmed, A., Aljabri, A.S., and Eldred, D. 1994. Demonstration of on-board maneuver planning using autonomous s/w architecture. In 8th Annual AIAA/USU Conference on Small Satellites.

  • Bonasso, R.P., Kortenkamp, D., Miller, D., and Slack, M. 1997. Experiences with an architecture for intelligent, reactive agents. JETAI, 9(1).

  • Bresina, J., Edgington, W., Swanson, K., and Drummond, M. 1996. Operational closed-loop obesrvation scheduling and execution. In Proc. of the AAAI Fall Symposium on Plan Execution, L. Pryor (Ed.), AAAI Press.

  • Brooks, R.A. 1986. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, 2(1):14-23.

    Google Scholar 

  • Brown, G.M., Bernard, D.E., and Rasmussen, R.D. 1995. Attitude and articulation control for the cassini spacecraft: A fault tolerance overview. In 14th AIAA/IEEE Digital Avionics Systems Conference, Cambridge, MA.

  • Cohen, P.R., Greenberg, M.L., Hart, D.M., and Howe, A.E. 1989. Trial by fire: Understanding the design requirements for agents in complex environments. AI Magazine, 10(3):32-48.

    Google Scholar 

  • Currie, K. and Tate, A. 1991. O-plan: The open planning architecture. Art. Int., 52(1):49-86.

    Article  Google Scholar 

  • de Kleer, J. and Williams, B.C. 1987. Diagnosing multiple faults. Artificial Intelligence, 32(1):97-130. Reprinted in Readings in Model-Based Diagnosis, Morgan Kaufmann: San Mateo, CA.

    Article  Google Scholar 

  • de Kleer, J. and Williams, B.C. 1989. Diagnosis with behavioral modes. In Proc. of IJCAI-89, pp. 1324-1330. Reprinted in Readings in Model-Based Diagnosis, Morgan Kaufmann: San Mateo, CA.

  • de Kleer, J. and Williams, B.C. (Eds.) 1991. Artificial Intelligence, Elsevier, Vol. 51.

  • Dean, T. and Boddy, M. 1986. An analysis of time-dependent planning. In Proceedings Conference of the American Association for Artificial Intelligence, pp. 49-54.

  • Drabble, B. 1993. Excalibur: A program for planning and reasoning with processes. Artificial Intelligence, 62(1):1-40.

    Article  Google Scholar 

  • Drabble, B., Tate, A., and Dalton, J. 1996. O-plan project evaluation experiments and results. Oplan Technical Report ARPA-RL/ O-Plan/TR/23 Version 1, AIAI.

  • Drummond, M., Bresina, J., and Swanson, K. 1994. Just-in-case scheduling. In Proc. of AAAI-94, AAAI Press: Cambridge, MA, pp. 1098-1104.

    Google Scholar 

  • Firby, R.J. 1978. Adaptive execution in complex dynamic worlds. Ph.D. thesis, Yale University.

  • Gat, E. 1992. Integrating planning and reacting in a heterogeneous asynchronous architecture for controlling real-world mobile robots. In Proc. of AAAI-92, AAAI Press: Cambridge, MA.

    Google Scholar 

  • Gat, E. 1996. ESL: A language for supporting robust plan execution in embedded autonomous agents. In Proc. of the AAAI Fall Symposium on Plan Execution, L. Pryor (Ed.), AAAI Press.

  • Georgeff, M.P. and Lansky, A.L. 1987. Procedural knowledge. Technical Report 411, Artificial Intelligence Center, SRI International.

  • Hackney, J., Bernard, D.E., and Rasmussen, R.D. 1993. The cassini spacecraft: Object oriented flight control software. In 1993 Guidance and Control Conference, Keystone, CO.

  • Hamscher, W., Console, L., and de Kleer, J. 1992. Readings in Model-Based Diagnosis, Morgan Kaufmann: San Mateo, CA.

    Google Scholar 

  • Hart, D.M., Anderson, S.D., and Cohen, P.R. 1990. Envelopes as a vehicle for improving the efficiency of plan execution. COINS Technical Report 90-21, Department of Computer Science, University of Massachusetts at Amherst.

  • Hayes-Roth, B. 1995. An architecture for adaptive intelligent systems. Artificial Intelligence, 72.

  • IJCAI, 1997. Proc. of the Fifteenth Int. Joint Conf. on Artificial Intelligence, Morgan Kaufmann Publishers: Los Altos, CA.

    Google Scholar 

  • Laird, J.E., Newell, A., and Rosenbloom, P.S. 1987. Soar: An architecture for general intelligence. Artificial Intelligence, 33(1).

  • Langley, P. 1992. Systematic and nonsystematic search strategies. In Proc. of the 1st Int. Conf. on Artificial Intelligence Planning Systems, Morgan Kaufmann, pp. 145-152.

  • Levinson, R. 1995. A general programming language for unified planning and control. Artificial Intelligence, 76.

  • Muscettola, N. 1994. HSTS: Integrating planning and scheduling. In Intelligent Scheduling, M. Fox and M. Zweben (Eds.), Morgan Kaufmann.

  • Muscettola, N., Pell, B., Hansson, O., and Mohan, S. 1995. Automating mission scheduling for space-based observatories. In Robotic Telescopes: Current Capabilities, Present Developments, and Future Prospects for Automated Astronomy, G.W. Henry and J.A. Eaton (Eds.), No. 79 in ASP Conf. Series. Astronomical Society of the Pacific, Provo, UT.

    Google Scholar 

  • Muscettola, N., Smith, B., Chien, C., Fry, C., Rabideau, G., Rajan, K., and Yan, D. 1997. On-board planning for autonomous spacecraft. In Proc. of the Fourth Int. Symp. on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS), D. Atkinson (Ed.), Tokyo, Japan. Jet Propulsion Laboratory.

    Google Scholar 

  • Musliner, D., Durfee, E., and Shin, K. 1993. Circa: A cooperative, intelligent, real-time control architecture. IEEE Transactions on Systems, Man, and Cybernetics, 23(6).

  • Nayak, P.P. and Williams, B.C. 1997. Fast context switching in realtime propositional reasoning. In Proc. of AAAI-97, AAAI Press: Cambridge, MA.

    Google Scholar 

  • Nilsson, N.J. 1994. Teleo-reactive programs for agent control. JAIR, 1:139-158.

    Google Scholar 

  • Noreils, F. and Chatila, R. 1995. Plan execution monitoring and control architecture for mobile robots. IEEE Transactions on Robotics and Automation.

  • Pell, B., Bernard, D.E., Chien, S.A., Gat, E., Muscettola, N., Nayak, P.P., Wagner, M.D., and Williams, B.C. 1996. A remote agent prototype for spacecraft autonomy. In Proc. of the SPIE Conf. on Optical Science, Engineering, and Instrumentation.

  • Pell, B., Gamble, E., Gat, E., Keesing, R., Kurien, J., Millar, B., Nayak, P.P., Plaunt, C., and Williams, B. 1997. A hybrid procedural/deductive executive for autonomous spacecraft. In Procs. of the AAAI Fall Symposium on Model-Directed Autonomous Systems, P.P. Nayak and B.C. Williams (Eds.), AAAI Press.

  • Pell, B., Gat, E., Keesing, R., Muscettola, N., and Smith, B. 1997. Robust periodic planning and execution for autonomous spacecraft. In Proc. of IJCAI-97, Morgan Kaufmann Publishers: Los Altos, CA.

    Google Scholar 

  • Pryor, L. (Ed.) 1996. Procs. of the AAAI Fall Symposium on Plan Execution, AAAI Press.

  • Reece, G. and Tate, A. 1994. Synthesizing protection monitors from causal structure. In Procs. AIPS-94, AAAI Press.

  • Schoppers, M.J. 1987. Universal plans for reactive robots in unpredictable environments. In Procs. Int. Joint Conf. on Artificial Intelligence, pp. 1039-1046.

  • Simmons, R. 1990. An architecture for coordinating planning, sensing, and action. In Proc. DARPA Workshop on Innovative Approaches to Planning, Scheduling and Control, DARPA, Morgan Kaufmann: San Mateo, CA, pp. 292-297.

    Google Scholar 

  • Tambe, M., Johnson, W.L., Jones, R.M., Koss, F., Laird, J.E., Rosenbloom, P.S., and Schwamb, K. 1995. Intelligent agents for interactive simulation environments. AI Magazine, 16(1):15-39.

    Google Scholar 

  • Weld, D.S. 1994. An introduction to least commitment planning. AI Magazine.

  • Weld, D.S. and de Kleer, J. (Eds.) 1990. Readings in Qualitative Reasoning About Physical Systems. Morgan Kaufmann Publishers, Inc.: San Mateo, California.

    Google Scholar 

  • Wilkins, D.E. 1988. Practical Planning, Morgan Kaufman: San Mateo, CA.

    Google Scholar 

  • Wilkins, D.E. and Myers, K.L. 1995. A common knowledge representation for plan generation and reactive execution. Journal of Logic and Computation.

  • Wilkins, D.E., Myers, K.L., Lowrance, J.D., and Wesley, L.P. 1995. Planning and reacting in uncertain and dynamic environments. JETAI, 7(1):197-227.

    Google Scholar 

  • Williams, B.C. and Nayak, P.P. 1996a. Immobile robots: AI in the new millennium. AI Magazine, 17(3):16-35.

    Google Scholar 

  • Williams, B.C. and Nayak, P.P. 1996b. A model-based approach to reactive self-configuring systems. In Proc. of AAAI-96, AAAI Press: Cambridge, MA, pp. 971-978.

    Google Scholar 

  • Williams, B.C. and Nayak, P.P. 1997. A reactive planner for a model-based executive. In Proc. of IJCAI-97, Morgan Kaufman Publishers: Los Altos, CA.

    Google Scholar 

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Authors and Affiliations

  1. Caelum Research Corporation, NASA Ames Research Center, MS 269/2, Moffett Field, CA, 94035

    Barney Pell

  2. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA, 91109

    Douglas E. Bernard, Steve A. Chien & Erann Gat

  3. NASA Ames Research Center, Recom Technologies, MS 269/2, Moffett Field, CA, 94035

    Nicola Muscettola & P. Pandurang Nayak

  4. Fourth Planet Inc., 220 Main Street, Suite 204, Los Altos, CA, 94022. E-mail

    Michael D. Wagner

  5. NASA Ames Research Center, MS 269/2, Moffett Field, CA, 94035. E-mail

    Brian C. Williams

Authors
  1. Barney Pell
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  2. Douglas E. Bernard
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  3. Steve A. Chien
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  4. Erann Gat
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  5. Nicola Muscettola
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  6. P. Pandurang Nayak
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  7. Michael D. Wagner
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  8. Brian C. Williams
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Pell, B., Bernard, D.E., Chien, S.A. et al. An Autonomous Spacecraft Agent Prototype. Autonomous Robots 5, 29–52 (1998). https://doi.org/10.1023/A:1008860925034

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