A Task-based Approach to Generate Optimal Software-Architecture for Intelligent Service Robots

In order to provide services more reliably, intelligent service robots need to consider various factors, such as their surrounding environments, user´s changing requirements, and constrained resources. Most of the intelligent service robots are controlled based on a task-based control system, which generates a task plan that consists of a sequence of actions, and executes the actions by invoking the corresponding functions. However, this task-based control system did not seriously consider resource factors even though intelligent service robots have limited resources (limited computational power, memory space, and network bandwidth). If we consider these factors during the task generation time, the complexity of the plan may become unmanageable. Therefore, in this paper, we propose a mechanism for robots to efficiently use their resources on-demand. We define reusable software-architectures corresponding to each action of a task plan, and provide a way of using the limited resources by minimizing redundant software components. We conducted an experiment of this mechanism for an infotainment robot. The experiment shows the effectiveness of our mechanism.