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A Bayesian nonparametric approach to modeling battery health
2012
2012 IEEE International Conference on Robotics and Automation
The batteries of many consumer products, including robots, are often both a substantial portion of the product's cost and commonly a first point of failure. Accurately predicting remaining battery life can lower costs by reducing unnecessary battery replacements. Unfortunately, battery dynamics are extremely complex, and we often lack the domain knowledge required to construct a model by hand. In this work, we take a data-driven approach and aim to learn a model of battery time-to-death from
doi:10.1109/icra.2012.6225178
dblp:conf/icra/JosephDR12
fatcat:6hc7pos6q5eu5grxfaq3suqshu