A robot’s code needs to sense the environment, control the hardware, and communicate with other robots. Current programming languages do not provide suitable abstractions that are independent of hardware platforms. Currently, developing robot applications requires detailed knowledge of signal processing, control, path planning, network protocols, and various platform-specific details. Further, porting applications across hardware platforms remains tedious. We present Koord—a domain specific language for distributed robotics—which abstracts platform-specific functions for sensing, communication, and low-level control. Koord makes the platform-independent control and coordination code portable and modularly verifiable. Koord raises the level of abstraction in programming by providing distributed shared memory for coordination and port interfaces for sensing and control. We have developed the formal executable semantics of Koord in the K framework. With this symbolic execution engine, we can identify assumptions (proof obligations) needed for gaining high assurance from Koord applications. We illustrate the power of Koord through three applications: formation flight, distributed delivery, and distributed mapping. We also use the three applications to demonstrate how platform-independent proof obligations can be discharged using the Koord Prover while platform-specific proof obligations can be checked by verifying the obligations using physics-based models and hybrid verification tools.

No abstract

No abstract

Abstract. Automatic verification of convergence and stabilization properties of distributed algorithms has received less attention than verification of invariance properties. We present a semi-automatic strategy for verification of stabilization properties of arbitrarily large networks under structural and fairness constraints. We introduce a sufficient condition that guarantees that every fair execution of any (arbitrarily large) instance of the system stabilizes to the target set of states. In addition to specifying the protocol executed by each agent in the network and the stabilizing set, the user also has to provide a measure function or a ranking function. With this, we show that for a restricted but useful class of distributed algorithms, the sufficient condition can be automatically checked for arbitrarily large networks, by exploiting the small model properties of these conditions. We illustrate the method by automatically verifying several well-known distributed algorithms including linkreversal, shortest path computation, distributed coloring, leader election and spanning-tree construction.

Programming languages, libraries, and development tools have transformed the application development processes for mobile computing and machine learning. This paper introduces the CyPhyHouse-a toolchain that aims to provide similar programming, debugging, and deployment benefits for distributed mobile robotic applications. Users can develop hardware-agnostic, distributed applications using the high-level, event driven Koord programming language, without requiring expertise in controller design or distributed network protocols. The modular, platform-independent middleware of CyPhyHouse implements these functionalities using standard algorithms for path planning (RRT), control (MPC), mutual exclusion, etc. A high-fidelity, scalable, multi-threaded simulator for Koord applications is developed to simulate the same application code for dozens of heterogeneous agents. The same compiled code can also be deployed on heterogeneous mobile platforms. The effectiveness of CyPhyHouse in improving the design cycles is explicitly illustrated in a robotic testbed through development, simulation, and deployment of a distributed task allocation application on in-house ground and aerial vehicles.