CHARM: A platform for algorithmic robotics education research

This paper introduces autonomous sorting of moving coins via a robot as a multi-level task that supports the principled study of robotics fundamentals including kinematics, dynamics, perception, motion planning, controls, and optimization based around a widely obtainable, standardized, low-cost object (a coin). The paper also presents a demonstrated solution to this in the form of the CHARM (Coin Handling Arm for Robotics Mastery) robot, which addresses the autonomous coin sorting problem using an economical kit made from commodity computing hardware and three Dynamixel servomotors. From a learning perspective, this problem facilitates interdisciplinary practice across subject and grade levels with an algorithmic foundation that is central to modern robotics. Evidence supporting this approach is illustrated from case studies of student projects and, in particular, the CHARM robot. Beyond practice alone, by presenting a challenging (but manageable) research problem, we found that the coin sorting task teaches robotics in a principled way. Further, algorithmic complexity tiers the problem to academic levels. While motivated by robotics education, the (optimal) coin sorting problem may also be seen as an archetype problem for manipulation/motion-planning research. Thus, this also promotes a research foundation supporting later research opportunities.