An inertial navigation system for a mobile robot

Abstract

A low-cost, solid-state inertial navigation system for robotics applications is described. Error models for the inertial sensors are generated and included in an extended Kalman filter (EKF) for estimating the position and orientation of a moving robot vehicle. A solid-state gyroscope and an accelerometer have been evaluated. Without error compensation, the error in orientation is between 5-15°/min but can be improved at least by a factor of five if an adequate error model is supplied. Similar error models have been developed for each axis of a solid-state triaxial accelerometer. Linear position estimation with accelerometers and tilt sensors is more susceptible to errors due to the double integration process involved in estimating position. WIth the system described here, the position drift rate is 1-8 cm/s, depending on the frequency of acceleration changes. The results show that with careful and detailed modeling of error sources, low cost inertial sensing systems can provide valuable position information