Optimizing Information Value: Improving Rover Sensor Data Collection

Robotic exploration is an excellent method for obtaining information about sites too dangerous for people to explore. The operator's understanding of the environment depends on the rover returning useful information. Robotic mission bandwidth is frequently constrained, limiting the amount of information the rover can return. This paper explores the tradeoff between information and bandwidth based on two years of observations during a robotic astrobiology field study. The developed theory begins by analyzing the search task conducted by robot operators. This analysis leads to an information optimization model. Important parameters in the model include the value associated with detecting a target, the probability of locating a target, and the bandwidth required to collect the information from the environment. Optimizing the information return between regions creates an image and provides the necessary information while reducing bandwidth. Application of the model to the analyzed field study results in an optimized image that requires 48.3% less bandwidth to collect. The model also predicts several data collection patterns that could serve as the basis of data collection templates for improving mission effectiveness. The developed optimization model reduces the bandwidth necessary to collect information, thus aiding missions in collecting more information from the environment.