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Michael Kaess : Real-time mapping for autonomous robots | CMU RI Seminar


curated by | October 11, 2014

“In this talk [Professor Kaess presents his] recent research on robust and efficient optimization techniques for real-time robotic mapping. [He focuses] on our recently developed incremental nonlinear least-squares solver, termed incremental smoothing and mapping (iSAM2). Based on our new probabilistic model called the Bayes tree, iSAM2 efficiently updates an existing solution to a nonlinear least-squares problem after new measurements are added.”

Source: www.youtube.com



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