We are releasing the code of our RSS paper: “VIMO: Simultaneous Visual
Inertial Model-based Odometry and Force Estimation”, where we estimate
external forces in addition to the robot state and IMU bias, at no extra
computational cost

Source code, paper and narrated video presentation:
http://rpg.ifi.uzh.ch/vimo/index.html

For many robotic applications, it is often essential to sense the
external force acting on the system due to, for example, interactions,
contacts, and disturbances. VIMO extends the capability of a typical
optimization-based Visual-Inertial Odometry framework to jointly
estimate external forces in addition to the robot state and IMU bias, at
no extra computational cost. The results also show up to 30% increase in
the estimator’s accuracy.

The authors:
Barza Nisar, Philipp Foehn, Davide Falanga, Davide Scaramuzza