  Visually recognising a traversed route - regardless of whether seen during
the day or night, in clear or inclement conditions, or in summer or winter - is
an important capability for navigating robots. Since SeqSLAM was introduced in
2012, a large body of work has followed exploring how robotic systems can use
the algorithm to meet the challenges posed by navigation in changing
environmental conditions. The following paper describes OpenSeqSLAM2.0, a fully
open source toolbox for visual place recognition under changing conditions.
Beyond the benefits of open access to the source code, OpenSeqSLAM2.0 provides
a number of tools to facilitate exploration of the visual place recognition
problem and interactive parameter tuning. Using the new open source platform,
it is shown for the first time how comprehensive parameter characterisations
provide new insights into many of the system components previously presented in
ad hoc ways and provide users with a guide to what system component options
should be used under what circumstances and why.
