Just adopt a Kalman filter based on constant static contact assumption to reduce the noise from direct prediction of tip position by characterized polynomial model.

To build dynamic contact estimate and also calculate the transform between world-fixed frame and whisker base, it is necessary to install an encoder to obtain the linear velocity measurement.

To make it easy on test, we build a simulated flexible whisker sensor model based on mujoco and elasticity cable element, and leave an interface for furture control test.

Try to locat the contact with a prerequisite that the contact happened only on the tip of whisker shaft. We were trying to build a fully detailed description on whisker’s deflection profile here.

Build process model based on static contect hypothesis and inverse uniquly mapping measurement according to the previous studies, moreover, make a test on offline data from whisker sensor.

This is to thoroughly exam the details to calculate the kalmann gain and others of state estimation problem and data fusion, mathematically.