  In this paper, we consider the problem of multirotor flying robots physically
interacting with the environment under wind influence. The result are the first
algorithms for simultaneous online estimation of contact and aerodynamic
wrenches acting on the robot based on real-world data, without the need for
dedicated sensors. For this purpose, we investigate two model-based techniques
for discriminating between aerodynamic and interaction forces. The first
technique is based on aerodynamic and contact torque models, and uses the
external force to estimate wind speed. Contacts are then detected based on the
residual between estimated external torque and expected (modeled) aerodynamic
torque. Upon detecting contact, wind speed is assumed to change very slowly.
From the estimated interaction wrench, we are also able to determine the
contact location. This is embedded into a particle filter framework to further
improve contact location estimation. The second algorithm uses the propeller
aerodynamic power and angular speed as measured by the speed controllers to
obtain an estimate of the airspeed. An aerodynamics model is then used to
determine the aerodynamic wrench. Both methods rely on accurate aerodynamics
models. Therefore, we evaluate data-driven and physics based models as well as
offline system identification for flying robots. For obtaining ground truth
data we performed autonomous flights in a 3D wind tunnel. Using this data,
aerodynamic model selection, parameter identification, and discrimination
between aerodynamic and contact forces could be done. Finally, the developed
methods could serve as useful estimators for interaction control schemes with
simultaneous compensation of wind disturbances.
