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Decision-theoretic control of planetary rovers
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Zilberstein, Shlomo Washington, Richard Morris, Robert Technical Monitor Mouaddib, Abdel-Illah Bernstein, Daniel S. |
| Copyright Year | 2003 |
| Description | Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We describe two decision-theoretic approaches to maximize the productivity of planetary rovers: one based on adaptive planning and the other on hierarchical reinforcement learning. Both approaches map the problem into a Markov decision problem and attempt to solve a large part of the problem off-line, exploiting the structure of the plan and independence between plan components. We examine the advantages and limitations of these techniques and their scalability. |
| File Size | 1137318 |
| Page Count | 19 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_20030034662 |
| Archival Resource Key | ark:/13960/t9r25ws55 |
| Language | English |
| Publisher Date | 2003-01-01 |
| Access Restriction | Open |
| Subject Keyword | Ground Support Systems And Facilities (space) Decision Theory Stochastic Processes Unmanned Ground Vehicles Markov Processes Cameras Mathematical Models Control Theory Sensors Planning Roving Vehicles Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
