  Accurate position sensing is important for state estimation and control in
robotics. Reliable and accurate position sensors are usually expensive and
difficult to customize. Incorporating them into systems that have very tight
volume constraints such as modular robots are particularly difficult. PaintPots
are low-cost, reliable, and highly customizable position sensors, but their
performance is highly dependent on the manufacturing and calibration process.
This paper presents a Kalman filter with a simplified observation model
developed to deal with the non-linearity issues that result in the use of
low-cost microcontrollers. In addition, a complete solution for the use of
PaintPots in a variety of sensing modalities including manufacturing,
characterization, and estimation is presented for an example modular robot,
SMORES-EP. This solution can be easily adapted to a wide range of applications.
