Signal Processing Advances in Robots and Autonomy

The capabilities of robots and autonomous systems have increased dramatically over the past years. This success story partly depends on advances in signal processing which provide appropriate and efficient analysis of sensor data and enable autonomy. A key element of the transition of signal processing output to its exploitation inside robots and autonomous systems is the way uncertainty is managed: uncertainty originating from insufficient sensor data, uncertainty about effects of future autonomous actions, and, in the case of distributed sensors and actuators (like for a team of robots), uncertainty about communication lines. The aim of this special issue is to focus on recent developments that allow passing this transition path successfully, showing either where signal processing is used in robotics and autonomy or where robotics and autonomy had special demands that had not been fulfilled by signal processing before. The articles in this special issue cover the following topics.