Extensible collaborative autonomy using GAMS

Dukeman, Anton; Adams, Julie A.; Edmondson, James

doi:10.1145/2851613.2851927

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…Bio-economic modelling dates to the 1990s and includes mathematical programming models [284,294,295,349,350], multi-agent models [351][352][353], and other simulation models [291,354]. These models are sometimes combined with econometric analyses that fine-tune the results.…”

Section: Bio-economic Modellingmentioning

confidence: 99%

Role of Modelling in International Crop Research: Overview and Some Case Studies

et al. 2018

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Crop modelling has the potential to contribute to global food and nutrition security. This paper briefly examines the history of crop modelling by international crop research centres of the CGIAR (formerly Consultative Group on International Agricultural Research but now known simply as CGIAR), whose primary focus is on less developed countries. Basic principles of crop modelling building up to a Genotype × Environment × Management × Socioeconomic (G × E × M × S) paradigm, are explained. Modelling has contributed to better understanding of crop performance and yield gaps, better prediction of pest and insect outbreaks, and improving the efficiency of crop management including irrigation systems and optimization of planting dates. New developments include, for example, use of remote sensed data and mobile phone technology linked to crop management decision support models, data sharing in the new era of big data, and the use of genomic selection and crop simulation models linked to environmental data to help make crop breeding decisions. Socio-economic applications include foresight analysis of agricultural systems under global change scenarios, and the consequences of potential food system shocks are also described. These approaches are discussed in this paper which also calls for closer collaboration among disciplines in order to better serve the crop research and development communities by providing model based recommendations ranging from policy development at the level of governmental agencies to direct crop management support for resource poor farmers.

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Section: Bio-economic Modellingmentioning

confidence: 99%

Role of Modelling in International Crop Research: Overview and Some Case Studies

et al. 2018

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“…More recently, the possibility to use ROS in a multi-master architecture was introduced where multiple master nodes co-exist and exchange information being, however, still required to be aware of each other prior to their execution. The recentlydeveloped GAMS middleware supports collaborative autonomy amongst heterogeneous teams of agents using non-blocking, best-effort communications protocols, which allows operation even in communications constrained environments [15]. All nodes under a GAMS collaboration system have their own knowledge base which, using MADARA, synchronizes relevant information with peers when that information is changed [16].…”

Section: Related Workmentioning

confidence: 99%

Advancing multi-vehicle deployments in oceanographic field experiments

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Costa

et al. 2018

Auton Robot

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Our research concerns the coordination and control of robotic vehicles for upper water-column oceanographic observations. In such an environment, operating multiple vehicles to observe dynamic oceanographic phenomena, such as ocean processes and marine life, from fronts to cetaceans, has required that we design, implement and operate software, methods and processes which can support opportunistic needs in real-world settings with substantial constraints. In this work, an approach for coordinated measurements using such platforms, which relate directly to task outcomes, is presented. We show the use and operational value of a new Artificial Intelligence (AI) based mixedinitiative system for handling multiple platforms along with the networked infrastructure support needed to

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“…The first middleware is called the Multi-Agent Distributed Adaptive Resource Allocation (MADARA) project [7] and provides autonomous systems with a distributed knowledge base, network transports for updating knowledge, portable application threads, and scalable reasoning services. The second middleware is called the Group Autonomy for Mobile Systems (GAMS) project [1,5] and provides autonomous systems with interfaces for single agent and multi-agent algorithms, hardware actuators and sensors, and full integration with the MADARA project for knowledge, threading, and reasoning. The integration of these two middlewares is shown in Figure 1.…”

Section: Software Architecture Overviewmentioning

confidence: 99%

Software Solutions for Distributed Autonomous Multi-Functional Robotics in Space

et al. 2016

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Robotics systems in space must deal with a host of software challenges in addition to and amplified by the challenges of a hostile space environment and the remoteness in which they operate. Software automation has been used to good effect in managing some of these challenges to control single robotic systems, even multi-functional systems, in previous unmanned missions without the physical presence of human operators. However, these previous control software artifacts tend to be platform-specific, single-systemfocused and not really applicable to multi-agent teams of multi-functional, multi-generational robotic systems. In this paper, we discuss a software architecture based on the Multi-Agent Distributed Adaptive Resource Allocation 1 (MADARA) and Group Autonomy for Mobile Systems 2 (GAMS) open source middleware projects that is intended to be deployed in a multi-agent, multi-functional robotic system called the Keck Institute for Space Studies Multi-Planetary Smart Tile. We discuss our solution approaches to addressing scalability and quality-of-service in deployments of multi-agent systems, codifying group intelligence in hostile space environments, portability for future missions and systems, and assurance and verification of software controllers and algorithms.

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Extensible collaborative autonomy using GAMS

Cited by 5 publications

References 6 publications

Role of Modelling in International Crop Research: Overview and Some Case Studies

Role of Modelling in International Crop Research: Overview and Some Case Studies

Advancing multi-vehicle deployments in oceanographic field experiments

Software Solutions for Distributed Autonomous Multi-Functional Robotics in Space

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