  Fast and versatile locomotion can be achieved with wheeled quadruped robots
that drive quickly on flat terrain, but are also able to overcome challenging
terrain by adapting their body pose and by making steps. In this paper, we
present a state estimation approach for four-legged robots with non-steerable
wheels that enables hybrid driving-stepping locomotion capabilities. We
formulate a Kalman Filter (KF) for state estimation that integrates driven
wheels into the filter equations and estimates the robot state (position and
velocity) as well as the contribution of driving with wheels to the above
state. Our estimation approach allows us to use the control framework of the
Mini Cheetah quadruped robot with minor modifications. We tested our approach
on this robot that we augmented with actively driven wheels in simulation and
in the real world. The experimental results are available at
https://www.ais.uni-bonn.de/%7Ehosseini/se-dsq .
