Improving sensory perception through predictive correction of monitoring errors

We present an approach to managing the quality and cost of perception in a multi-sensor robotic system. The approach involves prediction of monitoring errors of low-performance process monitors using a weighted least squares algorithm, and detection of instances when high-performance process monitoring is necessary. Two significant characteristics of the approach are (1) dynamic, real-time management of process monitors, and (2) the ability to deliver high quality information while keeping the cost of perception low.