רונן ברפמן

Model-based planning and execution systems offer a principled approach to building flexible autonomous robots that can perform diverse tasks by automatically combining a host of basic skills. This idea is almost as old as modern robotics. Yet, while diverse general-purpose reasoning architectures have been proposed since, general-purpose software platforms that support the construction of planner-based controllers and their integration with modern robotic platforms have emerged only recently, starting with the influential ROSPlan system. Since then, a growing number of domain-independent model-based platforms for robot task-level control have emerged. In this paper, we consider the diverse design choices and issues existing platforms attempt to address, the different solutions proposed so far, and suggest avenues for future development. We also briefly discuss the elephant in the room: foundation models.