CyPhyHouse: A programming, simulation, and deployment toolchain for heterogeneous distributed coordination

Ghosh, Ritwika; Jansch-Porto, Joao Paulo; Hsieh, Chiao; Gosse, Amelia; Jiang, Minghao; Taylor, Hebron; Du, Peter; Mitra, Sayan; Dullerud, Geir E.

doi:10.1109/icra40945.2020.9196513

Cited by 6 publications

(4 citation statements)

References 21 publications

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“…Robot motion planning is a large and active research area [7], [8], [9], [10], and planning from TL specifications has received significant attention [1], [11]. Abstraction-based approaches have stood out as a systematic framework of finding control policies [1], [12].…”

Section: A Related Workmentioning

confidence: 99%

Multi-Agent Motion Planning From Signal Temporal Logic Specifications

Sun

Chen

Mitra

et al. 2022

IEEE Robot. Autom. Lett.

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We tackle the challenging problem of multi-agent cooperative motion planning for complex tasks described using signal temporal logic (STL), where robots can have nonlinear and nonholonomic dynamics. Existing methods in multi-agent motion planning, especially those based on discrete abstractions and model predictive control (MPC), suffer from limited scalability with respect to the complexity of the task, the size of the workspace, and the planning horizon. We present a method based on timed waypoints to address this issue. We show that timed waypoints can help abstract nonlinear behaviors of the system as safety envelopes around the reference path defined by those waypoints. Then the search for waypoints satisfying the STL specifications can be inductively encoded as a mixedinteger linear program. The agents following the synthesized timed waypoints have their tasks automatically allocated, and are guaranteed to satisfy the STL specifications while avoiding collisions. We evaluate the algorithm on a wide variety of benchmarks. Results show that it supports multi-agent planning from complex specification over long planning horizons, and significantly outperforms state-of-the-art abstraction-based and MPC-based motion planning methods. The implementation is available at https://github.com/sundw2014/STLPlanning.

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Section: A Related Workmentioning

confidence: 99%

Multi-Agent Motion Planning From Signal Temporal Logic Specifications

Sun

Chen

Mitra

et al. 2022

IEEE Robot. Autom. Lett.

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“…There exist several projects in this space [3,11,23,29] that allow provably safe CPS code to execute on real systems. This area aims to bridge the gap between abstract, verifiable models and concrete, executable implementation-level code.…”

Section: Verifiable and Executable Cpsmentioning

confidence: 99%

“…CyPhyHouse [29], based on the Koord [28] language, is a robotics stack aimed at verifying multi-agent, possibly heterogeneous, robotics systems. The high-level Koord language allows specification of tasks and associated safety requirements.…”

Section: Verifiable and Executable Cpsmentioning

confidence: 99%

Synchronous Programming and Refinement Types in Robotics: From Verification to Implementation

Chen

Mendonça

Jalili

et al. 2022

Proceedings of the 8th ACM SIGPLAN International Workshop on Formal Techniques for Safety-Critical Systems

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Robots and other cyber-physical systems are held to high standards of safety and reliability, and thus one must be confident in the correctness of their software. Formal verification can provide such confidence, but programming languages that lend themselves well to verification often do not produce executable code, and languages that are executable do not typically have precise enough formal semantics. We present MARVeLus, a stream-based approach to combining verification and execution in a synchronous programming language that allows formal guarantees to be made about implementation-level source code. We then demonstrate the end-to-end process of developing a safe robotics application, from modeling and verification to implementation and execution.

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“…Aerostack’s swarming capabilities are enabled by the framework’s social layer interface contracts, yet the mechanics of inter-agent communication is left for the application developer to finalize. A few examples of swarming solutions embedded into frameworks can be seen in the Voltron ( Mottola et al, 2014 ), Buzz ( Pinciroli and Beltrame, 2016 ), and CyPhyHouse 10 ’s Koord ( Ghosh et al, 2020 ) programming languages. Though varying in implementation details, the development framework provided by each of these languages allows the ultimate application developer to write an application from a swarm (or a sub-group of a swarm’s agents or super-group of sub-groups…) perspective with relative ease; this is done by including an underlying mechanism that propagates coordinating information between agents.…”

Section: Introductionmentioning

confidence: 99%

AntAlate—A Multi-Agent Autonomy Framework

Dovrat

Bruckstein

2021

Front. Robot. AI

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AntAlate is a software framework for Unmanned Aerial Vehicle (UAV) autonomy, designed to streamline and facilitate the work of application developers, particularly in deployment of Multi-Agent Robotic Systems (MARS). We created AntAlate in order to bring our research in the field of multi-agent systems from theoretical results to both advanced simulations and to real-life demonstrations. Creating a framework capable of catering to MARS applications requires support for distributed, decentralized, control using local sensing, performed autonomously by groups of identical anonymous agents. Though mainly interested in the emergent behavior of the system as a whole, we focused on the single agent and created a framework suitable for a system of systems approach, while minimizing the hardware requirements of the single agent. Global observers or even a centralized control can be added on top of AntAlate, but the framework does not require a global actor to finalize an application. The same applies to a human in the loop, and fully autonomous UAV applications can be written in as straightforward a way as can semi-autonomous applications. In this paper we describe the AntAlate framework and demonstrate its utility and versatility.

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CyPhyHouse: A programming, simulation, and deployment toolchain for heterogeneous distributed coordination

Cited by 6 publications

References 21 publications

Multi-Agent Motion Planning From Signal Temporal Logic Specifications

Multi-Agent Motion Planning From Signal Temporal Logic Specifications

Synchronous Programming and Refinement Types in Robotics: From Verification to Implementation

AntAlate—A Multi-Agent Autonomy Framework

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