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ATAL
2005
Springer

Coordinating multiple rovers with interdependent science objectives

11 years 7 months ago
Coordinating multiple rovers with interdependent science objectives
This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data. The MISUS system combines techniques from planning and scheduling with machine learning to perform autonomous scientific exploration with cooperating rovers. A distributed planning and scheduling approach is used to generate efficient, multi-rover coordination plans, monitor plan execution, and perform re-planning when necessary. A machine learning clustering component is used to deduce geological relationships among collected data and select new science activities. A key concept promoted by this system is the use of goal interdependency information to perform plan optimization and increase the value of collected science data. We discuss how we represent and reason about goal dependency and utility information in our planning system and explain how this information can change dynamically during system use. We show through experimental results t...
Tara A. Estlin, Daniel M. Gaines, Forest Fisher, R
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where ATAL
Authors Tara A. Estlin, Daniel M. Gaines, Forest Fisher, Rebecca Castaño
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