As robots evolve, society’s collective imagination forever ponders what else robots can do, with recent fascinations coming to life as self-driving cars or robots that can walk and interact with objects as humans do. These sophisticated systems are powered by advances in deep learning that triggered breakthroughs in robotic perception, so that robots today have greater potential for better decision-making and improved functioning in real-world environments. But tomorrow’s roboticists need to understand how to combine deep learning with dynamics, controls, and long-term planning. To keep this momentum in robotic manipulation…
