Balancing deliberation and reaction, planning and execution for space robotic applications

Intelligent behavior for robotic agents requires a careful balance of fast reactions and deliberate consideration of long-term ramifications. The need for this balance is particularly acute in space applications, where hostile environments demand fast reactions, and remote locations dictate careful management of consumables that cannot be replenished. However, fast reactions typically require procedural representations with limited scope and handling long-term considerations in a general fashion is often computationally expensive. We describe three major areas for autonomous systems for space exploration: free-flying spacecraft, planetary rovers, and ground communications stations. In each of these broad applications areas, we identify operational considerations requiring rapid response and considerations of long-term ramifications. We describe these issues in the context of ongoing efforts to deploy autonomous systems using planning and task execution systems.

[1]  Karen L. Myers.  Towards a Framework for Continuous Planning and Execution , 2000 .

[2]  Forest Fisher,et al.  A planning approach to monitor and control for deep space communications , 2000, 2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).

[3]  T.T. Nguyen,et al.  Experiences with operations and autonomy of the Mars Pathfinder Microrover , 1998, 1998 IEEE Aerospace Conference Proceedings (Cat. No.98TH8339).

[4]  Katia Sycara,et al.  The RETSINA Multiagnet System: Towards Integrating Planning, Execution and Information Gathering. , 1998 .

[5]  Sam Steel,et al.  Integrating Planning, Execution and Monitoring , 1988, AAAI.

[6]  Randall W. Hill,et al.  A hierarchical architecture for resource allocation, plan execution, and revision for operation of a network of communications antennas , 1997, Proceedings of International Conference on Robotics and Automation.

[7]  Karen Zita Haigh,et al.  Interleaving Planning and Robot Execution for Asynchronous User Requests , 1998, Auton. Robots.

[8]  Erann Gat,et al.  Integrating Planning and Reacting in a Heterogeneous Asynchronous Architecture for Controlling Real-World Mobile Robots , 1992, AAAI.

[9]  Erann Gat,et al.  Experiences with an architecture for intelligent, reactive agents , 1997, J. Exp. Theor. Artif. Intell..

[10]  Michael Beetz,et al.  Improving Robot Plans During Their Execution , 1994, AIPS.

[11]  Daniel S. Weld,et al.  UCPOP: A Sound, Complete, Partial Order Planner for ADL , 1992, KR.

[12]  Ronald C. Arkin,et al.  Motor Schema — Based Mobile Robot Navigation , 1989, Int. J. Robotics Res..

[13]  Erann Gat,et al.  Robust Periodic Planning and Execution for Autonomous Spacecraft , 1997, IJCAI.

[14]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[15]  Tara A. Estlin,et al.  Automated planning for a Deep Space Communications Station , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[16]  Daniel S. Weld,et al.  Probabilistic Planning with Information Gathering and Contingent Execution , 1994, AIPS.

[17]  Tucker R. Balch,et al.  AuRA: principles and practice in review , 1997, J. Exp. Theor. Artif. Intell..

[18]  Edmund H. Durfee,et al.  Integrated Premission Planning and Execution for Unmanned Ground Vehicles , 1997, AGENTS '97.

[19]  David J. Musliner,et al.  CIRCA: a cooperative intelligent real-time control architecture , 1993, IEEE Trans. Syst. Man Cybern..

[20]  Barbara Hayes-Roth,et al.  An Architecture for Adaptive Intelligent Systems , 1995, Artif. Intell..

[21]  Illah Nourbakhsh.  Interleaving Planning and Execution for Autonomous Robots , 1997 .

[22]  Rob Sherwood,et al.  Using Iterative Repair to Improve the Responsiveness of Planning and Scheduling , 2000, AIPS.

[23]  Reid G. Simmons,et al.  A task description language for robot control , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[24]  Craig Boutilier,et al.  Integrating Planning and Execution in Stochastic Domains , 1994, UAI.

[25]  Peter Haddawy,et al.  An Abstraction-Based Approach to Interleaving Planning and Execution in Partially-Observable Domains , 1996 .

[26]  Reid G. Simmons,et al.  Structured control for autonomous robots , 1994, IEEE Trans. Robotics Autom..

[27]  Onn Shehory,et al.  Interleaving Planning and Execution in a Multiagent Team Planning Environment , 2000, Electron. Trans. Artif. Intell..

[28]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[29]  Edmund H. Durfee,et al.  Integrated premission planning and execution for unmanned ground vehicles , 1997, AGENTS '97.

[30]  Robert James Firby,et al.  Adaptive execution in complex dynamic worlds , 1989 .

[31]  Rachid Alami,et al.  A Scheme for Coordinating Multi-robots Planning Activities and Plans Execution , 1998, ECAI.

[32]  E. Gat.  On Three-Layer Architectures , 1997 .

[33]  Oren Etzioni,et al.  Planning with Execution and Incomplete Information , 1996 .