Flexible real-time mobile robotic architecture based on behavioural models
Behaviour-based models have been widely used to represent mobile robotic systems, which operate in uncertain dynamic environments and combine information from several sensory sources. The specification of complex mobile robotic applications is performed in such models by combining deliberative goal-oriented planning with reactive sensor driven operations. Consequently, the design of mobile robotic architectures requires the combination of time-constrained activities with deliberate time-consuming components. Furthermore, the temporal requirements of the reactive activities are variable and dependent on the environment (i.e. recognition processes) and/or on application parameters (i.e. process frequencies depend on robot speed). In this paper, a real-time mobile robotic architecture to cope with the functional and variable temporal characteristics of behaviour-based mobile robotic applications is proposed. Run-time flexibility is a main feature of the architecture that supports the variability of the temporal characteristics of the workload. The system has to be adapted to the environmental conditions, by adjusting robot control parameters (i.e. speed) or the system load (i.e. computational time), and take actions depending on it. This influence is focused on the ability of the system to select the appropriate activity to be executed depending on the available time, and, to change its behaviour depending on the environmental information. The flexibility of the system is allowed thanks to the definition of a real-time task model and the design of adaptation mechanisms for the regulation of the reactive load. The improvement of the robot quality of service (QoS) is another important aspect discussed in the paper. The architecture incorporates a quality of service manager (QoSM) that allows dynamically monitor analyse and improve the robot performances. Depending on the internal state, on the environment and on the objectives, the robot performance requirements vary (i.e. when the environment is overloaded, global map processes generating high-quality maps are required). The QoSM receives the performance requirements of the robot, and by adjusting the reactive load, the system enables the necessary slack time to schedule the more suitable deliberative processes and hence fulfilling the robot QoS. Moreover, the deliberative load can be scheduled by different heuristic strategies that provide answers of varying quality.
mobile robots behavioural model quality of service autonomous guided vehicles hybrid architecture real-time system scheduling algorithms