Touch is important to the way people experience the world. We typically think of touch as a way to convey warmth and care, but it’s also a key sensing modality for perceiving the world around us. Touching provides us with information that’s not discernible through any other sense, for example, about the temperature of a matter, its texture and weight, and sometimes even its state. We want AI to be able to learn from and interact with the world through touch, like humans do. But for that to happen, we need to foster an ecosystem for tactile sensing in robotics. Today, we’re outlining our progress in developing hardware, simulators, libraries, benchmarks, and data sets — pillars of the touch-sensing ecosystem necessary for building AI systems that can understand and interact through touch.
Together, these pillars will allow us to train robots and AI to draw critical information from touch, and to integrate this information with others to accomplish tasks of greater complexity and superior functionality.
