Autonomy and robust intelligence are important research areas due to the plethora of applications from space exploration, manufacturing, robotics and transportation to medicine and biology. In aerospace applications, autonomy becomes more and more important due to the need for deep space exploration. In manufacturing, the development of technologies for safe human-machine and human-robot interaction have the potential to improve the competitiveness of existing industrial processes and create economic growth. In medicine and biology, the use of intelligent systems can improve health care and minimize risk factors. In the area of disaster response, there is the need for autonomous systems to operate in remote and dangerous for the human environments. Given the importance of autonomy and robust intelligence in the aforementioned areas, this workshop aims to identify fundamental scientific questions and encourage new research directions at the confluence of aerospace, medicine, transportation, manufacturing, disaster response, space exploration, and biology.
Learning, perception and control are fundamental modalities necessary for autonomous systems to operate in dynamic, uncertain and remote environments. Autonomous systems should be able to robustly walk, navigate, efficiently explore, quickly learn new motor skills and generalize these skills to unseen conditions. This workshop brings together scientists from different areas of sciences and engineering to brainstorm on two questions related to the representation of sensory information and data, and generalization of decision and control mechanisms in robotics and autonomous systems. The aforementioned topics are investigated at the intersection of planning and control, information theory, machine learning, neuroscience and perception. The emphasis of the workshop will be on the mathematical interdependencies and interconnections of these areas based on mathematical concepts that include but they are not limited to differential geometry and topology. The goal for the workshop is to determine future research directions and identify open questions across the disciplines of control theory, machine learning, perception and cognitive sciences.
