Harmful algae blooms in lakes are a major environmental problem, producing extremely dangerous toxins that can taint water supplies or harm other organic life—including people. Biologists can test water safety by collecting samples off the side of a boat, but getting relevant data is no small task, especially in lakes that cover hundreds of miles.
And while algae blooms can spring up anywhere, finding optimal sites to sample is like looking for a needle in a haystack.
As a result, biologists currently find algae concentrations through trial and error and struggle to anticipate new growth, prolonging the discovery of potentially harmful algae and wasting time and labor in the field.
Now, USC computer scientists and biologists have developed a way for autonomous robots to find prime sample spot locations for toxic algae, before a scientist even steps foot onsite. The team recently presented the paper, titled” Informative Path Planning to Estimate Quantiles for Environmental Analysis,” at the International Conference on Intelligent Robots and Systems (IROS.) The paper is also available on the arXiv preprint server.
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