Task Planning for Service Robots with Supervisory Control

Abstract

Without an appropriate task planning scheme for service robots (SRs) in a ubiquitous robotic companion (URC) environment, the SRs degrade the system performance and they do not achieve the desired goal and the customers’ requirements. In addition, the system resources might be wasted. In this paper, we propose a new task planning scheme for SRs to balance a desired goal and the system resources with a supervisor. In particular, we propose a high work-metric SR selection scheme using work metric (WM) information to provide the flexible trade-off with the limited communication resources. As a result, the proposed scheme not only reduces a significant communication feedback overload but also considers task planning in an URC environment. Simulation results show that the proposed scheme achieves the high customers’ requirements with the limited communication resources.