  Component inspection is often the bottleneck in high-value manufacturing,
driving industries like aerospace toward automated inspection technologies.
Current systems often employ fixed arm robots, but they lack the flexibility in
adapting to new components or orientations Advanced mobile robotic platforms
with updated sensor technologies and algorithms have improved localization and
path planning capabilities, making them ideal for bringing inspection processes
directly to parts. However, mobile platforms introduce challenges in
localization and maneuverability, leading to potential errors. Their positional
uncertainty is higher than fixed systems due to the lack of a fixed calibrated
location, posing challenges for position-sensitive inspection sensors.
Therefore, it's essential to assess the positional accuracy and repeatability
of mobile manipulator platforms. The KUKA KMR iiwa was chosen for its
collaborative features, robust build, and scalability within the KUKA product
range. The accuracy and repeatability of the mobile platform were evaluated
through a series of tests to evaluate the performance of its integrated feature
mapping, the effect of various speeds on positional accuracy, and the
efficiency of the omnidirectional wheels for a range of translation
orientations. Experimental evaluation revealed that enabling feature mapping
substantially improves the KUKA KMR iiwa's performance, with accuracy gains and
error reductions exceeding 90%. Repeatability errors were under 7 mm with
mapping activated and around 2.5 mm in practical scenarios, demonstrating that
mobile manipulators, incorporating both the manipulator and platform, can
fulfil the precise requirements of industries with high precision needs.
Providing a highly diverse alternative to traditional fixed-base industrial
manipulators.
