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Visually recognising a traversed route - regardless of whether seen duringthe day or night, in clear or inclement conditions, or in summer or winter - isan important capability for navigating robots. Since SeqSLAM was introduced in2012, a large body of work has followed exploring how robotic systems can usethe algorithm to meet the challenges posed by navigation in changingenvironmental conditions. The following paper describes OpenSeqSLAM2.0, a fullyopen source toolbox for visual place recognition under changing conditions.Beyond the benefits of open access to the source code, OpenSeqSLAM2.0 providesa number of tools to facilitate exploration of the visual place recognitionproblem and interactive parameter tuning. Using the new open source platform,it is shown for the first time how comprehensive parameter characterisationsprovide new insights into many of the system components previously presented inad hoc ways and provide users with a guide to what system component optionsshould be used under what circumstances and why.

OpenSeqSLAM2.0: An Open Source Toolbox for Visual Place Recognition Under Changing Conditions