EKF-based visual self-calibration tool for robots with rotating directional cameras

Autonomous mobile robots perception systems are complex multi-sensors systems. Information from different sensors, placed in different parts of the platforms, need to be related and fused into some representation of the world or robot state. For that, the knowledge of the relative pose (position and rotation) between sensors frames and the platform frame plays a critical role. The process to determine those is called extrinsic calibration. This paper addresses the development of automatic robot calibration tool for Middle Size League Robots with rotating directional cameras, such as the ISePorto team robots. The proposed solution consists on a robot navigating in a path, while acquiring visual information provided by a known target positioned in a global reference frame. This information is then combined with wheel odometry sensors, robot rotative axis encoders and gyro information within an Extend Kalman filter framework, that estimates all parameters required for the sensors angles and position determination related to the robot body frame. We evaluated our solution, by performing several trials and obtaining similar results to the previous used manual calibration procedure, but with a much less time consuming performance and also without being susceptible to human error.