The Use of the Blackboard Archiecture for a Decision making System for the Control of Craft with various Actuator and Movement Capabilities

This paper provides an overview of an approach to the control of multiple craft with heterogeneous movement and actuation characteristics that is based on the Blackboard software architecture. An overview of the Blackboard architecture is provided. Then, the operational and mission requirements that dictate the need for autonomous control are characterized and the utility of the Blackboard architecture is for meeting these requirements is discussed. The performance of a best-path solver and naïve solver are compared. The results demonstrate that the best-path solver outperforms the naïve solver in the amount of time taken to generate a solution, however, the number of solver-runs to be executed against the Blackboard must be sufficient to allow the lower individual-run times to offset the time required to propagate the data utilized by the best-path solver for solution generation through the database. The existence of other justifications for this approach (even if the number of runs for each data propagation cycle is not sufficient) is also discussed

A Blackboard-style decision-making system for multi-tier craft control and its evaluation

This article presents an approach for decision-making in support of the control of an autonomous system of multiple tiers of robots (e.g., satellite, aerial and ground) based on the Blackboard architectural style. Under the proposed approach, the system evaluates prospective approaches for goal satisfaction (identified by user selected final rules), identifies the lowest-cost solution and determines the best path to achieving the goal, via the analysis of the Blackboard rule and action set. Two different approaches to this rule and action path generation are discussed. This article presents the proposed Blackboard-style architecture for autonomous multi-tier control and describes its implementation. The benefits and drawbacks of the Blackboard-style approach are analysed, its extrapolation to the control of multiple heterogeneous craft is presented and the tradeoffs between the two approaches to rule-path generation are assessed