Sensor uncertainty management for an encapsulated logical device architecture. Part II: a control policy for sensor uncertainty

For Part I see ACC, Arlington, VA. USA (2001). A procedure to perform data fusion inside a low-level control loop was developed and implemented on a 1-DOF manipulator. This procedure uses sensory data provided by low-level and non-dedicated high-level sensors, at different rates. Fusion of the multiple feedback signals generates a signal with a smaller uncertainty level. The performance of the control scheme is directly related to the quality and relevance of the feedback signal. In this control policy, data fusion is performed with the data coming from the different sensors, once they have been time-correlated using Kalman filters. Also, In order to stabilize the fused feedback signal when there is no data available from the slower sensors, a Kalman filter is used to observe and generate a prediction of the fused measurement signal, which can then be used by the data fusion process. The slow sensor processing delay compensation and fused measurement stabilization are independent of the fusion process. Therefore, any data fusion process can be used with this procedure, as long as the process respects the real-time constraint of the low-level control loop