Using an Accelerometer for State Estimation on an Icosahedral Tensegrity Structure

This paper presents a methodology for implementing a Kalman filter on an icosahedral tensegrity system capable of performing state estimation on an icosahedral structure. A motion model based on the geometry of the system and a measurement model based on the Inertial Measurement Unit (IMU) data are derived for this purpose. Due to the nature of icosahedral tensegrity robots, accurately predicting the state of the robot through conventional models is difficult, primarily because the entire structure is rotated in 3D space during movement. As such, adding bearing or distance sensors to this robot is very difficult, since the location of those sensors with respect to the base frame changes with every rotation. This paper instead uses a simple kinematic model based on the predicted geometry of the structure to act as the motion model and uses the data from an accelerometer to create a measurement model. These models are then used in a Kalman filter to estimate the state of the system.