StarL: Towards a Unified Framework for Programming, Simulating and Verifying Distributed Robotic Systems
Yixiao Lin, Sayan Mitra

TL;DR
StarL is a comprehensive framework that enables programming, simulating, and verifying distributed robotic systems with primitives, theory libraries, and execution environments, facilitating development and analysis of complex multi-robot applications.
Contribution
The paper introduces StarL, a unified framework combining distributed primitives, formal verification, and deployment/simulation tools for robotic systems, enhancing reliability and ease of development.
Findings
Successfully implemented primitives with invariants and progress properties.
Verified applications using PVS theorem prover.
Deployed and simulated vehicle coordination in an intersection scenario.
Abstract
We developed StarL as a framework for programming, simulating, and verifying distributed systems that interacts with physical processes. StarL framework has (a) a collection of distributed primitives for coordination, such as mutual exclusion, registration and geocast that can be used to build sophisticated applications, (b) theory libraries for verifying StarL applications in the PVS theorem prover, and (c) an execution environment that can be used to deploy the applications on hardware or to execute them in a discrete event simulator. The primitives have (i) abstract, nondeterministic specifications in terms of invariants, and assume-guarantee style progress properties, (ii) implementations in Java/Android that always satisfy the invariants and attempt progress using best effort strategies. The PVS theories specify the invariant and progress properties of the primitives, and have to…
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