Non Linear State Estimation of a Multi Axis Surgical Robot

Non Linear State Estimation of a Multi Axis Surgical Robot Srikrishnan Ramadurai Chair of the Supervisory Committee: Professor Blake Hannaford Electrical Engineering Minimally invasive surgical robots often have cable driven power transmission mechanisms. An example is the RAVEN surgical robot developed at the Biorobotics Laboratory, University of Washington for research on robotic surgery. The use of flexible cable based power transmission often causes a difference between the motor angle and joint angles during operation due to the elasticity of the cable. To achieve good control, controllers typically need to account for the dynamics and the elastic power transmission element. Recent control methodologies that can be used to improve performance often use a state space representation. To study the state estimation on the RAVEN, state estimates of a simulation of the RAVEN are obtained with the Unscented Kalman Filter (UKF) and compared with the known states available from the simulation. These state estimates are also utilized by two different controllers interacting with the simulation to test the UKF performance under closed loop control. We tested the UKF performance with perturbations in the UKF model cable stiffness parameter. The simulation is developed based on device file based I/O using the Filesystem in Userspace(FUSE)/Character device in Userspace(CUSE) library. We attempted to develop the simulation with real-time performance considerations combined with userspace development and ability to seamlessly switch the control software from simulation to real system.