Robot’s Velocity and Tilt Estimation Through Computationally Efficient Fusion of Proprioceptive Sensors Readouts

Abstract—In this paper a method is introduced that combines Inertial Measurement Unit (IMU) readouts with low accuracy and temporarily unavailable velocity measurements (e.g., based on kinematics or GPS) to produce high accuracy estimates of velocity and orientation with respect to gravity. The method is computationally cheap enough to be readily implementable in sensors. The main area of application of the introduced method is mobile robotics. Keywords—velocity estimation, Kalman filter, mobile robotics. I