A Dual-Loop Control Model and Software Framework for Autonomous Robot Software

Autonomous robot software is an extremely complex system that drives robots to operate in an open and dynamic environment to accomplish tasks. This requires such software to be designed with effective control models to support continuous and flexible feedback. To this end, this paper presents a dual loop control model called D-SMPA and corresponding software framework that adopts several design principles to support the development and running of autonomous robot. Our proposed model explicitly abstracts the robot behaviors into observation oriented and task-oriented types, and provides a dual-loop control to coordinate these behaviors. Control mechanisms in D-SMPA are proposed to support a tight integration and accompanying cooperation between observation and task behaviors so that the task accomplishment can get required feedback of sensors. Our approach aims to enrich the capabilities of autonomous robot software by obtaining on-demand feedback from multiple sources, and at the same time to simplify software development by separating complex behaviors of robots. We present a multi-agent software framework called AutoRobot to implement the proposed control model and provide tools to support the development of autonomous robot software. Our case study validates the effectiveness and applicability of our proposed approach and framework.