Kalman Filter for Angle Estimation using Dual Inertial Measurement Units on Unicycle Robot

The Inverted pendulum platform is an example of classic unstable control system. Even though the system has been fairly tested and documented, it still draws attention of many researchers due to its application in unicycle robot. In the unicycle robot, there are problems that arise control strategy in the reading position of the robot tilt. This paper proposes to use the Kalman Filter Estimation angle for data processing Inertial Measurement Unit (IMU) to obtain estimates of the robot tilt position. In the previous study also found problems when using only one relatively low speed IMU sensor obstacles that the response given by the sensor. This paper uses two IMU sensor readings to speedup the response of the sensor and get accurate data during a shorter period. The proposed algorithm uses a new sensor placement strategy on a rigid body robot, with a reading sensor in interleaved mode. Kalman Filter algorithm incorporating placement constraints to achieve the estimated position of the robot tilt angle accurately. The results show synchronization time sampling of the two Inertial Measurement Unit (IMU) sensor improves the response and a twice faster in estimating the position of the robot tilt compared to the use of one sensor. Merging time sampling 2 sensors can be applied on a unicycle robot in order to have a quick response to the reading of the tilt position of the robot.