  Autonomous navigation is essential for steel bridge inspection robot to
monitor and maintain the working condition of steel bridges. Majority of
existing robotic solutions requires human support to navigate the robot doing
the inspection. In this paper, a navigation framework is proposed for ARA robot
[1], [2] to run on mobile mode. In this mode, the robot needs to cross and
inspect all the available steel bars. The most significant contributions of
this research are four algorithms, which can process the depth data, segment it
into clusters, estimate the boundaries, construct a graph to represent the
structure, generate a shortest inspection path with any starting and ending
points, and determine available robot configuration for path planning.
Experiments on steel bridge structures setup highlight the effective
performance of the algorithms, and the potential to apply to the ARA robot to
run on real bridge structures. We released our source code in Github for the
research community to use.
