Existing constraints on time, computational, and communication resources associated with Mars rover missions suggest on-board science evaluation of sensor data can contribute to decreasing human-directed operational planning, optimizing returned science data volumes, and recognition of unique or novel data, all of which act to increase the scientific return from a mission. Many different levels of science autonomy exist and each impacts the data collected and returned by, and activities of, rovers. Several computational algorithms, designed to recognize objects of interest to geologists and biologists, are discussed. The algorithms represent various functions producing scientific opinions and several scenarios illustrate how the opinions can be used.
Essential autonomous science inference on rovers (EASIR)
2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720) ; 2 ; 790-800 Vol.2
01.01.2004
1011517 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
2.1604 Essential Autonomous Science Inference on Rovers (EASIR)
British Library Conference Proceedings | 2004
|SAE Technical Papers | 1996
|Autonomous Rovers for Mars Exploration
British Library Conference Proceedings | 1999
|Autonomous Rovers for Mars Exploration
NTRS | 1999
|A Step Toward Autonomous Plantary Rovers
NTRS | 1999
|