  Despite decades of research, general purpose in-hand manipulation remains one
of the unsolved challenges of robotics. One of the contributing factors that
limit current robotic manipulation systems is the difficulty of precisely
sensing contact forces -- sensing and reasoning about contact forces are
crucial to accurately control interactions with the environment. As a step
towards enabling better robotic manipulation, we introduce DIGIT, an
inexpensive, compact, and high-resolution tactile sensor geared towards in-hand
manipulation. DIGIT improves upon past vision-based tactile sensors by
miniaturizing the form factor to be mountable on multi-fingered hands, and by
providing several design improvements that result in an easier, more repeatable
manufacturing process, and enhanced reliability. We demonstrate the
capabilities of the DIGIT sensor by training deep neural network model-based
controllers to manipulate glass marbles in-hand with a multi-finger robotic
hand. To provide the robotic community access to reliable and low-cost tactile
sensors, we open-source the DIGIT design at https://digit.ml/.
