Abstract
Currently, there is a lack of developer-friendly software tools to formally address multi-robot coordination problems and obtain robust, efficient, and predictable strategies. This paper introduces a software toolbox that encapsulates, in one single package, modeling, planning, and execution algorithms. It implements a state-of-the-art approach to representing multi-robot systems: generalized Petri nets with rewards (GSPNRs). GSPNRs enable capturing multiple robots, decision states, action execution states and respective outcomes, action duration uncertainty, and team-level objectives. We introduce a novel algorithm that simplifies the model design process as it generates a GSPNR from a topological map. We also introduce a novel execution algorithm that coordinates the multi-robot system according to a given policy. This is achieved without compromising the model compactness introduced by representing robots as indistinguishable tokens. We characterize the computational performance of the toolbox with a series of stress tests. These tests reveal a lightweight implementation that requires low CPU and memory usage. We showcase the toolbox functionalities by solving a multi-robot inspection application, where we extend GSPNRs to enable the representation of heterogeneous systems and system resources such as battery levels and counters.
Highlights
The use of multi-robot systems has proven successful in a wide range of real life applications, coordinating these systems at mission-level is still challenging in a number of scenarios
We introduce a software toolbox that allows: modeling multi-robot systems taking into account time uncertainty; obtaining coordination strategies that guarantee optimality; and executing these strategies in the Robot Operating System (ROS) environment
We address a solar farm inspection problem where the capabilities of the toolbox are showcased. When solving this problem we introduce an extension to the work in [20] to enable modeling heterogeneous multi-robot systems and system resources such as battery levels and counters
Summary
The use of multi-robot systems has proven successful in a wide range of real life applications, coordinating these systems at mission-level is still challenging in a number of scenarios. PRISM [13] and STORM [14] are open source probabilistic model checkers, that support discrete and continuous time Markov chains, Markov decision processes (MDPs) and generalized stochastic petri nets (GSPNRs) Both these tools allow model analysis, providing reachability properties, conditional probabilities and cost queries, long-run average values, cost-bounded properties and multi-objective queries. It does not provide methods to capture probabilistic behavior, or supports policy synthesis and, requires the input of a task plan Our work addresses these gaps and proposes a unified toolbox to implement multirobot coordination problems. This toolbox allows us to capture multi-robot systems as a generalized stochastic Petri net with rewards (GSPNR) [20], to synthesize optimal control policies that optimize team-level objectives, and provides methods to execute the obtained task plans in real robots. When solving this problem we introduce an extension to the work in [20] to enable modeling heterogeneous multi-robot systems and system resources such as battery levels and counters
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