Name
Abstract | ||
|---|---|---|
This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules. Commanding the rover to achieve mission goals requires significant knowledge of the rover design, access to the low-level rover command set, and an understanding of the performance metrics rating the desirability of alternative sequences. It also requires coordination with external events such as orbiter passes and day/night cycles. An automated planning and scheduling system encodes this knowledge and uses search and reasoning techniques to automatically generate low-level command sequences while respecting rover operability constraints, science and engineering preferences,and also adhering to hard temporal constraints. Enabling goal-driven commanding of planetary rovers by engineering and science personnel greatly reduccs the requirements for highly skilled rover engineering personnel and Rover Science Team time. This in turn greatly reduces mission operations costs. In addition, goal-driven commanding permits a faster response to changes in rover state (e.g., faults) or science discoveries by removing the time consuming manual sequence validation process, allowing rapid "what-iV' analyses, and thus reducing overall cycle times. |
Year | Venue | Keywords |
|---|---|---|
2001 | FLAIRS Conference | autonomous ground-based rover planning,scheduling,artificial intelligent,planning,artificial intelligence,autonomy,sequencing,prototypes,cycle time,satisfiability,proof of concept |
Field | DocType | ISBN |
Systems engineering,Computer science,Scheduling (computing),Simulation,Operability,Scheduling system,Artificial intelligence,Mission operations,Automated planning and scheduling,Machine learning,Orbiter | Conference | 1-57735-133-9 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rob Sherwood | 1 | 1462 | 128.08 |
| Andrew Mishkin | 2 | 20 | 9.80 |
| Tara A. Estlin | 3 | 146 | 15.11 |
| Steve Chien | 4 | 286 | 43.51 |
| Barbara Engelhardt | 5 | 151 | 19.77 |
| Brian Cooper | 6 | 162 | 65.34 |
| Gregg Rabideau | 7 | 244 | 29.61 |