Mission modeling, planning, and execution module for teams of unmanned vehicles

Croix, Jean-Pierre de la; Lim, Grace; Hook, Joshua Vander; Rahmani, Amir; Droge, Greg; Xydes, Alexander; Scrapper, Chris

doi:10.1117/12.2266881

Cited by 7 publications

(7 citation statements)

References 7 publications

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“…They used depth limits as a trade-off between performance and the ability to verify properties. 59 de la Croix et al 65 Cicchetti et al 68 proposed the CHESS framework to design, validate and verify and generate code from complex component-based embedded software system models. For modeling, they use CHESSML which adopts elements from the UML, SysML, and MARTE languages.…”

Section: Verifying Systems With Hidden Formal Methodsmentioning

confidence: 99%

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Pragmatic verification and validation of industrial executable SysML models

Horváth

Molnár

Graics

et al. 2023

Systems Engineering

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In recent years, Model‐Based Systems Engineering (MBSE) practices have been applied in various industries to design, simulate and verify complex systems. The verification and validation (V&V) of such systems engineering models are crucial to develop high‐quality systems. However, this is a challenging problem due to the complexity of the models and semantic differences in how different tools interpret the models, which can undermine the validity of the obtained results if they go undiscovered. To address these issues, we propose (i) a subset of the SysML language for which the practical semantic integrity of tools can be achieved and (ii) a cloud‐based V&V framework for this subset, lifting verification to an industrial scale. We demonstrate the feasibility of our approach on an industrial‐scale model from the aerospace domain and summarize the lessons learned during transitioning formal verification tools to an industrial context.

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Section: Verifying Systems With Hidden Formal Methodsmentioning

confidence: 99%

“…de la Croix et al 65 . proposed a role‐based framework for the design, execution, and verification of robotic applications.…”

Section: Related Workmentioning

confidence: 99%

Pragmatic verification and validation of industrial executable SysML models

Horváth

Molnár

Graics

et al. 2023

Systems Engineering

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“…Mission specification: A mission file is used to describe a mission and combines several highlevel robot autonomy behaviors to create the flow for more complex scenarios. For this, we use the Traceable Robotic Activity Composer and Executive (TRACE) proposed in (de la Croix et al, 2017) and the Business Process Modelling Notation (BPMN). Figure 38 When robots are too close, this behavior performs a prioritized motion planning to resolve the situation.…”

Section: Autonomymentioning

confidence: 99%

NeBula: TEAM CoSTAR’s Robotic Autonomy Solution that Won Phase II of DARPA Subterranean Challenge

Agha–mohammadi¹,

Otsu²,

Morrell³

et al. 2022

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This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved second and first place, respectively. We also discuss CoSTAR’s demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including (i) geometric and semantic environment mapping, (ii) a multi-modal positioning system, (iii) traversability analysis and local planning, (iv) global motion planning and exploration behavior, (v) risk-aware mission planning, (vi) networking and decentralized reasoning, and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g., wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.

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“…Mission Specification: A Mission File is used to describe a mission and combines several high-level Robot Autonomy Behaviors to create the flow for more complex scenarios. For this, we use the Traceable Robotic Activity Composer and Executive (TRACE) proposed in (de la Croix et al, 2017) and the Business Modelling Process Notation (BPMN). Figure 37 shows one example "Exploration" Mission File that was used in one of our Cave exploration scenarios.…”

Section: Autonomymentioning

confidence: 99%

NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge

Agha–mohammadi¹,

Otsu²,

Morrell³

et al. 2021

Preprint

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This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved 2nd and 1st place, respectively. We also discuss CoSTAR's demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including: (i) geometric and semantic environment mapping; (ii) a multi-modal positioning system; (iii) traversability analysis and local planning; (iv) global motion planning and exploration behavior; (i) risk-aware mission planning; (vi) networking and decentralized reasoning; and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g. wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.

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Mission modeling, planning, and execution module for teams of unmanned vehicles

Cited by 7 publications

References 7 publications

Pragmatic verification and validation of industrial executable SysML models

Pragmatic verification and validation of industrial executable SysML models

NeBula: TEAM CoSTAR’s Robotic Autonomy Solution that Won Phase II of DARPA Subterranean Challenge

NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge

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