MULTIPLE-TARGET SINGLE CYCLE INSTRUMENT PLACEMENT

Approaching targets and placing instruments on them is fundamental to planetary exploration. Because of communications, power and operational limitations, it currently takes 3 full sol command cycles to accomplish this on Mars with the MER rovers. To accomplish single cycle instrument placement (SCIP) on multiple targets, we developed and integrated precision visual tracking, off-board contingency planning, robust execution, autonomous instrument placement, round trip data tracking, and a photorealistic virtual reality system to visualize the robot’s environment and returned data products, and request further measurements. Our system has demonstrated a tenfold improvement in robotic capability, as measured by number of samples measured in a single command uplink, by getting 3um/pixel microscopic images from 3 targets designated with 1cm accuracy and up to 10m distant from the rover start position in a single command cycle, executed in under 3 hours.

[1]  Jeremy Frank,et al.  Constraint-Based Attribute and Interval Planning , 2003, Constraints.

[2]  Carol R. Stoker,et al.  Analyzing Pathfinder data using virtual reality and superresolved imaging , 1999 .

[3]  Peter Norvig,et al.  Robustness via Run-Time Adaptation of Contingent Plans , 2000 .

[4]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[5]  David E. Smith,et al.  Integrated Demonstration of Instrument Placement , Robust Execution and Contingent Planning , 2003 .

[6]  Tara Estlin,et al.  The CLARAty architecture for robotic autonomy , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[7]  John L. Bresina,et al.  Just-In-Case Scheduling , 1994, AAAI.

[8]  David E. Smith,et al.  Planning Under Continuous Time and Resource Uncertainty: A Challenge for AI , 2002, AIPS Workshop on Planning for Temporal Domains.

[9]  Linda Kobayashi,et al.  Extensible Hardware Architecture for Mobile Robots , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[10]  David E. Smith,et al.  Incremental Contingency Planning , 2003 .

[11]  David E. Smith,et al.  Optimal Limited Contingency Planning , 2002, UAI.

[12]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[13]  Randy Sargent,et al.  Terrain model registration for single cycle instrument placement , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[14]  C. Keller.  Algorithms to solve the orienteering problem: A comparison , 1989 .

[15]  David E. Smith.  Choosing Objectives in OverSubscription Planning , 2004 .