A System for Continuous Underground Site Mapping and Exploration

3D mapping becomes ever more important not only in industrial mobile robotic applications for AGV and production vehicles but also for search and rescue scenarios. In this chapter we report on our work of mapping and exploring underground mines. Our contribution is two-fold: First, we present our custom-built 3D laser range platform SWAP and compare it against an architectural laser scanner. The advantages are that the mapping vehicle can scan in a continuous mode and does not have to do stop-and-go scanning. The second contribution is the mapping tool mapit which supports and automates the registration of large sets of point clouds. The idea behind mapit is to keep the raw point cloud data as a basis for any map generation and only store all operations executed on the point clouds. This way the initial data do not get lost, and improvements on low-level date (e.g. improved transforms through loop closure) will automatically improve the final maps. Finally, we also present methods for visualization and interactive exploration of such maps

Learning State-Variable Relationships in POMCP: A Framework for Mobile Robots

We address the problem of learning relationships on state variables in Partially Observable Markov Decision Processes (POMDPs) to improve planning performance. Specifically, we focus on Partially Observable Monte Carlo Planning (POMCP) and represent the acquired knowledge with a Markov Random Field (MRF). We propose, in particular, a method for learning these relationships on a robot as POMCP is used to plan future actions. Then, we present an algorithm that deals with cases in which the MRF is used on episodes having unlikely states with respect to the equality relationships represented by the MRF. Our approach acquires information from the agent’s action outcomes to adapt online the MRF if a mismatch is detected between the MRF and the true state. We test this technique on two domains, rocksample, a standard rover exploration task, and a problem of velocity regulation in industrial mobile robotic platforms, showing that the MRF adaptation algorithm improves the planning performance with respect to the standard approach, which does not adapt the MRF online. Finally, a ROS-based architecture is proposed, which allows running the MRF learning, the MRF adaptation, and MRF usage in POMCP on real robotic platforms. In this case, we successfully tested the architecture on a Gazebo simulator of rocksample. A video of the experiments is available in the Supplementary Material, and the code of the ROS-based architecture is available online

Multicore and FPGA implementations of emotional-based agent architectures

The final publication is available at Springer via http://dx.doi.org/10.1007/s11227-014-1307-6.Control architectures based on Emotions are becoming promising solutions for the implementation of future robotic agents. The basic controllers of the architecture are the emotional processes that decide which behaviors of the robot must activate to fulfill the objectives. The number of emotional processes increases (hundreds of millions/s) with the complexity level of the application, reducing the processing capacity of the main processor to solve complex problems (millions of decisions in a given instant). However, the potential parallelism of the emotional processes permits their execution in parallel on FPGAs or Multicores, thus enabling slack computing in the main processor to tackle more complex dynamic problems. In this paper, an emotional architecture for mobile robotic agents is presented. The workload of the emotional processes is evaluated. Then, the main processor is extended with FPGA co-processors through Ethernet link. The FPGAs will be in charge of the execution of the emotional processes in parallel. Different Stratix FPGAs are compared to analyze their suitability to cope with the proposed mobile robotic agent applications. The applications are set up taking into account different environmental conditions, robot dynamics and emotional states. Moreover, the applications are run also on Multicore processors to compare their performance in relation to the FPGAs. Experimental results show that Stratix IV FPGA increases the performance in about one order of magnitude over the main processor and solves all the considered problems. Quad-Core increases the performance in 3.64 times, allowing to tackle about 89 % of the considered problems. Quad-Core has a lower cost than a Stratix IV, so more adequate solution but not for the most complex application. Stratix III could be applied to solve problems with around the double of the requirements that the main processor could support. Finally, a Dual-Core provides slightly better performance than stratix III and it is relatively cheaper.This work was supported in part under Spanish Grant PAID/2012/325 of "Programa de Apoyo a la Investigacion y Desarrollo. Proyectos multidisciplinares", Universitat Politecnica de Valencia, Spain.Domínguez Montagud, CP.; Hassan Mohamed, H.; Crespo, A.; Albaladejo Meroño, J. (2015). Multicore and FPGA implementations of emotional-based agent architectures. Journal of Supercomputing. 71(2):479-507. https://doi.org/10.1007/s11227-014-1307-6S479507712Malfaz M, Salichs MA (2010) Using MUDs as an experimental platform for testing a decision making system for self-motivated autonomous agents. Artif Intell Simul Behav J 2(1):21–44Damiano L, Cañamero L (2010) Constructing emotions. Epistemological groundings and applications in robotics for a synthetic approach to emotions. In: Proceedings of international symposium on aI-inspired biology, The Society for the Study of Artificial Intelligence, pp 20–28Hawes N, Wyatt J, Sloman A (2009) Exploring design space for an integrated intelligent system. Knowl Based Syst 22(7):509–515Sloman A (2009) Some requirements for human-like robots: why the recent over-emphasis on embodiment has held up progress. Creat Brain Like Intell 2009:248–277Arkin RC, Ulam P, Wagner AR (2012) Moral decision-making in autonomous systems: enforcement, moral emotions, dignity, trust and deception. In: Proceedings of the IEEE, Mar 2012, vol 100, no 3, pp 571–589iRobot industrial robots website. http://www.irobot.com/gi/ground/ . Accessed 22 Sept 2014Moravec H (2009) Rise of the robots: the future of artificial intelligence. Scientific American, March 2009. http://www.scientificamerican.com/article/rise-of-the-robots/ . Accessed 14 Oct 2014.Thu Bui L, Abbass HA, Barlow M, Bender A (2012) Robustness against the decision-maker’s attitude to risk in problems with conflicting objectives. IEEE Trans Evolut Comput 16(1):1–19Pedrycz W, Song M (2011) Analytic hierarchy process (AHP) in group decision making and its optimization with an allocation of information granularity. IEEE Trans Fuzzy Syst 19(3):527–539Lee-Johnson CP, Carnegie DA (2010) Mobile robot navigation modulated by artificial emotions. IEEE Trans Syst Man Cybern Part B 40(2):469–480Daglarli E, Temeltas H, Yesiloglu M (2009) Behavioral task processing for cognitive robots using artificial emotions. Neurocomputing 72(13):2835–2844Ventura R, Pinto-Ferreira C (2009) Responding efficiently to relevant stimuli using an emotion-based agent architecture. Neurocomputing 72(13):2923–2930Arkin RC, Ulam P, Wagner AR (2012) Moral decision-making in autonomous systems: enforcement, moral emotions, dignity, trust and deception. Proc IEEE 100(3):571–589Salichs MA, Malfaz M (2012) A new approach to modeling emotions and their use on a decision-making system for artificial agents. Affect Comput IEEE Trans 3(1):56–68Altera Corporation (2011) Stratix III device handbook, vol 1–2, version 2.2. http://www.altera.com/literature/lit-stx3.jsp . Accessed 14 Oct 2014.Altera Corporation (2014) Stratix IV device handbook, vol 1–4, version 5.9. http://www.altera.com/literature/lit-stratix-iv.jsp . Accessed 14 Oct 2014.Naouar MW, Monmasson E, Naassani AA, Slama-Belkhodja I, Patin N (2007) FPGA-based current controllers for AC machine drives: a review. IEEE Trans Ind Electr 54(4):1907–1925Intel Corporation (2014) Desktop 4th generation Intel Core Processor Family, Desktop Intel Pentium Processor Family, and Desktop Intel Celeron Processor Family, Datasheet, vol 1, 2March JL, Sahuquillo J, Hassan H, Petit S, Duato J (2011) A new energy-aware dynamic task set partitioning algorithm for soft and hard embedded real-time systems. Comput J 54(8):1282–1294Del Campo I, Basterretxea K, Echanobe J, Bosque G, Doctor F (2012) A system-on-chip development of a neuro-fuzzy embedded agent for ambient-intelligence environments. IEEE Trans Syst Man Cybern Part B 42(2):501–512Pedraza C, Castillo J, Martínez JI, Huerta P, Bosque JL, Cano J (2011) Genetic algorithm for Boolean minimization in an FPGA cluster. J Supercomput 58(2):244–252Orlowska-Kowalska T, Kaminski M (2011) FPGA implementation of the multilayer neural network for the speed estimation of the two-mass drive system. IEEE Trans Ind Inf 7(3):436–445Cassidy AS, Merolla P, Arthur JV, Esser SK, Jackson B, Alvarez-icaza R, Datta P, Sawada J, Wong TM, Feldman V, Amir A, Ben-dayan D, Mcquinn E, Risk WP, Modha DS (2013) Cognitive computing building block: a versatile and efficient digital neuron model for neurosynaptic cores. In: Proceedings of international joint conference on neural networks, IEEE (IJCNN’2013)IBM Cognitive Computing and Neurosynaptic chips website. http://www.research.ibm.com/cognitive-computing/neurosynaptic-chips.shtml . Accessed 22 Sept 2014Seo E, Jeong J, Park S, Lee J (2008) Energy efficient scheduling of real-time tasks on multicore processors. IEEE Trans Parallel Distrib Syst 19(11):1540–1552Lehoczky J, Sha L, Ding Y (1989) The rate monotonic scheduling algorithm: exact characterization and average case behavior. In: Proceedings of real time systems symposium, IEEE 1989, pp 166–171Ng-Thow-Hing V, Lim J, Wormer J, Sarvadevabhatla RK, Rocha C, Fujimura K, Sakagami Y (2008) The memory game: creating a human-robot interactive scenario for ASIMO. In: Proceedings of intelligent robots and systems, 2008, IROS 2008, IEEE/RSJ international conference, pp 779–78

Path planning, modelling and simulation for energy optimised mobile robotics

This thesis is concerned with an investigation of a solution for mobile robotic platforms to minimize the usage of scarce energy that is available and is not wasted following traditionally planned paths for complex terrain environments. This therefore addresses the need to reduce the total energy cost during a field task or mission. A path planning algorithm is designed by creating a new approach of artificial potential field method that generates a planned path, utilising terrain map. The new approach has the capability of avoiding the local minimum problems which is one of the major problems of traditional potential field method. By solving such problems gives a reliable solution to establish a required path. Therefore the approach results in an energy efficient path of the terrain identified, instead obvious straight line of the terrain. A literature review is conducted which reviews the mainstream path planning algorithms with the applications in mobile robotic platforms was analysed. These path planning algorithms are compared for the purpose of energy optimized planning, which concludes the method of artificial potential field as the path planning algorithm which has the most potential and will be further investigated and improved in this research. The methodology of designing, modelling and simulating a mobile robotic platform is defined and presented for the purpose of energy optimized path planning requirement. The research is to clarify the needs, requirements, and specifications of the design. A complete set of models which include mechanical and electrical modelling, functional concept modelling, modelling of the system are established. Based on these models, an energy optimized path planning algorithm is designed. The modelling of force and the kinematics is established to validate and evaluate the result of the algorithm through simulations. Moreover a simulation environment is established which is constructed for multi perspective simulation. This also enables collaborative simulation using Simulink and ADAMS to for simulating a path generated by the path planning algorithm and assess the energy consumption of the driven and steering mechanism of an exemplar system called AgriRover. This simulation environment allows the capture of simulated result of the total energy consumption, therefore outlines the energy cost behaviour of the AgriRover. A total of two sets of paths was tested in the fields for validation, one being generated by the energy optimized path planning algorithm and the other following a straight path. During the field tests the total cost of energy was captured . Two sets of results are compared with each other and compared with the simulation. The comparison shows a 21.34% of the energy saving by deploying the path generated with the energy optimized path planning algorithm in the field test. This research made the following contribution to knowledge. A comparison and grading of mainstream path planning algorithms from energy optimisation perspective is undertaken using detailed evaluation criteria, including computational power required, extendibility, flexibility and more criteria that is relevant for the energy optimized planning purpose. These algorithms have not been compared from energy optimisation angle before, and the research for energy optimised planning under complex terrain environments have not been investigated. Addressing these knowledge gaps, a methodology of designing, modelling and simulating a mobile platform system is proposed to facilitate an energy optimized path planning. This , leads to a new approach of path planning algorithm that reduces unnecessary energy spend for climbing of the terrain, using the terrain data available. Such a methodology derives several novel methods: Namely, a method for avoiding local minimum problem for artificial potential field path planning using the approach of approximation; A method of achieving high expendability of the path planning algorithm, where this method is capable of generate a path through a large map in a short time; A novel method of multi perspective dynamic simulation, which is capable of simulating the behaviour of internal mechanism and the overall robotic mobile platform with the fully integrated control, The dynamic simulation enables prediction of energy consumption; Finally, a novel method of mathematically modelling and simplifying a steering mechanism for the wheel based mobile vehicle was further investigated.This thesis is concerned with an investigation of a solution for mobile robotic platforms to minimize the usage of scarce energy that is available and is not wasted following traditionally planned paths for complex terrain environments. This therefore addresses the need to reduce the total energy cost during a field task or mission. A path planning algorithm is designed by creating a new approach of artificial potential field method that generates a planned path, utilising terrain map. The new approach has the capability of avoiding the local minimum problems which is one of the major problems of traditional potential field method. By solving such problems gives a reliable solution to establish a required path. Therefore the approach results in an energy efficient path of the terrain identified, instead obvious straight line of the terrain. A literature review is conducted which reviews the mainstream path planning algorithms with the applications in mobile robotic platforms was analysed. These path planning algorithms are compared for the purpose of energy optimized planning, which concludes the method of artificial potential field as the path planning algorithm which has the most potential and will be further investigated and improved in this research. The methodology of designing, modelling and simulating a mobile robotic platform is defined and presented for the purpose of energy optimized path planning requirement. The research is to clarify the needs, requirements, and specifications of the design. A complete set of models which include mechanical and electrical modelling, functional concept modelling, modelling of the system are established. Based on these models, an energy optimized path planning algorithm is designed. The modelling of force and the kinematics is established to validate and evaluate the result of the algorithm through simulations. Moreover a simulation environment is established which is constructed for multi perspective simulation. This also enables collaborative simulation using Simulink and ADAMS to for simulating a path generated by the path planning algorithm and assess the energy consumption of the driven and steering mechanism of an exemplar system called AgriRover. This simulation environment allows the capture of simulated result of the total energy consumption, therefore outlines the energy cost behaviour of the AgriRover. A total of two sets of paths was tested in the fields for validation, one being generated by the energy optimized path planning algorithm and the other following a straight path. During the field tests the total cost of energy was captured . Two sets of results are compared with each other and compared with the simulation. The comparison shows a 21.34% of the energy saving by deploying the path generated with the energy optimized path planning algorithm in the field test. This research made the following contribution to knowledge. A comparison and grading of mainstream path planning algorithms from energy optimisation perspective is undertaken using detailed evaluation criteria, including computational power required, extendibility, flexibility and more criteria that is relevant for the energy optimized planning purpose. These algorithms have not been compared from energy optimisation angle before, and the research for energy optimised planning under complex terrain environments have not been investigated. Addressing these knowledge gaps, a methodology of designing, modelling and simulating a mobile platform system is proposed to facilitate an energy optimized path planning. This , leads to a new approach of path planning algorithm that reduces unnecessary energy spend for climbing of the terrain, using the terrain data available. Such a methodology derives several novel methods: Namely, a method for avoiding local minimum problem for artificial potential field path planning using the approach of approximation; A method of achieving high expendability of the path planning algorithm, where this method is capable of generate a path through a large map in a short time; A novel method of multi perspective dynamic simulation, which is capable of simulating the behaviour of internal mechanism and the overall robotic mobile platform with the fully integrated control, The dynamic simulation enables prediction of energy consumption; Finally, a novel method of mathematically modelling and simplifying a steering mechanism for the wheel based mobile vehicle was further investigated

Arquitectura de Agente Emocional para Aplicaciones de Control en Tiempo Real

Tesis por compendioArtificial agents are a technology suitable for solving problems. Agents can perform tasks that their users cannot and/or do not want to accomplish. Agents are systems with a significant degree of autonomy. Even being autonomous in their behavior, they assume the users' goals as their own goals, because there is an agreement between the agent and the user. It is a powerful technology, and the research on this field is very active. As agents are complex systems, it is necessary to define development frameworks that facilitate their conception, design and construction. We name these frameworks, artificial agent architectures. Each architecture is characterized by a few key ideas related to the way the agent represents its knowledge about the world, and how it organizes its behavior. We call these key ideas a paradigm. In this work, an artificial agent's architecture is proposed. In this architecture the organization of the behavior is emotionally driven. It is a bio-inspired architecture. The emotion in this case, however, is a very simplified version of the emotional process in the natural emotional agents. Although other agent architectures based on emotions have been proposed, they have been usually focused on the social skills of the agents, normally to interact with people. This situation could have been caused due to the knowledge we had about the importance of the emotion in the social relations between human beings, when people recognize the internal state of the others, or show their own internal states, and the emotional communication influences their behavior. However, the fundamental role of the emotion in a wide range of cognitive processes is being recognized because of the recent research in psychology and neuroscience. Emotions seem to make an essential contribution in processes such as perception, learning, memory, decision-making and problem solving. Deliberative rational thoughts themselves would be directed by emotions. Given this new view about the emotion, in this thesis, we have investigated the role of the emotions in the cognitive processes of an artificial agent, related them to the general decision making problem, not just the social interaction problem. As an example, in the application considered as a case study in this project, the emotional agent controls a mobile robot platform, in which there is not an important behavior layer of social interaction, and the emotional processes primarily motivate behaviors related to problems in a physical environment, with objects, parts, or areas of operation and navigation. In this thesis, we have defined a specification for the proposed emotional agent architecture, and have discussed the implementation aspects of it.Los agentes artificiales constituyen una tecnología de apoyo para la resolución de problemas. Un agente es un sistema con un grado significativo de autonomía, lo que le permite descargar a su usuario de tareas que éste no puede o no quiere realizar. Aun siendo autónomo en sus comportamientos, el agente asume los objetivos de su usuario como propios, ya que existe un contrato entre el agente y su representado. Se trata de una tecnología potente y que interesa desarrollar, con lo que el área de investigación en agentes está abierta y hay un esfuerzo continuo para construir agentes con cada vez mejores prestaciones. Siendo los agentes sistemas complejos, resulta necesario definir marcos de desarrollo que permitan concebirlos, diseñarlos y construirlos. Conocemos a estos marcos como arquitecturas de agentes artificiales. Cada una de estas arquitecturas se caracteriza por ciertas ideas clave, relacionadas con la forma en que el agente representa su conocimiento y organiza su comportamiento, en lo que se denomina un paradigma. Sin duda, queda mucho recorrido en este campo - ampliando por ejemplo las áreas de aplicación, o permitiendo funcionalidades adicionales, o aumentando la eficiencia de los procesos implicados, tanto en lo relativo al comportamiento del agente cuando éste está en explotación, como durante el propio proceso de construcción y validación del sistema. En este trabajo se propone una arquitectura de agente artificial en el que la organización del comportamiento está dirigida por un proceso emocional. Se trata de una arquitectura bio-inspirada. La emoción en este caso, sin embargo, es una versión muy simplificada del proceso emocional en los agentes emocionales naturales. Aunque se han definido otras arquitecturas de agentes artificiales basadas en emociones, han sido enfocadas, sobre todo, a construir agentes con habilidades sociales; normalmente para interactuar con las personas. Posiblemente esto ha sido debido a que ya hace mucho que se aceptaba la importancia de la emoción en las relaciones sociales entre los seres humanos; cuando éstos interpretan el estado interno de los demás o expresan su propio estado, alterando con ello sus comportamientos. Sin embargo, el papel fundamental de la emoción en un amplio espectro de procesos cognitivos está siendo reconocido a raíz de la investigación en psicología y neurología. Las emociones parecen contribuir de forma esencial en procesos como la percepción, el aprendizaje, la memoria, la toma de decisiones o la resolución de problemas. El propio pensamiento deliberativo racional estaría dirigido por las emociones. Teniendo en cuenta esta nueva visión de las emociones, en este trabajo se ha investigado el rol de la emoción en los procesos cognitivos de un agente artificial relacionados con la toma de decisiones en general, no sólo en lo relativo a los procesos de interrelación social. Así por ejemplo, en la aplicación considerada como caso de estudio de este trabajo, el agente emocional controla una plataforma de robot móvil de servicio, en la que no hay una capa de comportamiento social importante, y donde los procesos emocionales motivan fundamentalmente los comportamientos relacionados con problemas surgidos en un entorno físico, con objetos, piezas, o espacios de operación y navegación. En esta tesis se define una especificación para la arquitectura de agente emocional artificial propuesta y se discute aspectos de implementación de dicha arquitectura.Els agents artificials constitueixen una tecnologia de suport per a la resolució de problemes. Un agent és un sistema amb un grau significatiu d'autonomia, el que li permet descarregar al seu usuari de tasques que aquest no pot o no vol fer. Fins i tot sent autònom en els seus comportaments, l'agent assumeix els objectius del seu usuari com a propis, ja que hi ha un contracte entre l'agent i el seu representat. Es tracta d'una tecnologia potent i que interessa desenvolupar, de manera que l'àrea de recerca en agents està oberta i hi ha un esforç continu per construir agents amb cada vegada millors prestacions. Sent els agents sistemes complexos, resulta necessari definir marcs de desenvolupament que puguen permetre concebre'ls, dissenyar-los i construir-los. Coneixem a aquests marcs com arquitectures d'agents artificials. Cadascuna d'aquestes arquitectures es caracteritza per certes idees clau, relacionades amb la forma en què l'agent representa el seu coneixement i organitza el seu comportament, en el que s'anomena un paradigma. Sens dubte, queda molt de recorregut en aquest camp - ampliant les àrees d'aplicació, o permetent funcionalitats addicionals, o augmentant l'eficiència dels processos implicats, tant pel que fa al comportament de l'agent quan aquest està en explotació, com durant el mateix procés de construcció i validació del sistema. En aquest treball es proposa una arquitectura d'agent artificial en què l'organització del comportament està dirigida per un procés emocional. Es tracta d'una arquitectura bio-inspirada. L'emoció en aquest cas, però, és una versió molt simplificada del procés emocional en els agents emocionals naturals. Tot i que s'han definit altres arquitectures d'agents artificials basades en emocions, han estat enfocades, sobretot, a construir agents amb habilitats socials; normalment per interactuar amb les persones. Possiblement això ha segut perquè ja fa molt que s'acceptava la importància de l'emoció en les relacions socials entre els éssers humans; quan aquests interpreten l'estat intern dels altres o expressen el seu propi estat, alterant amb això els seus comportaments. No obstant això, el paper fonamental de l'emoció en un ampli espectre de processos cognitius està sent reconegut arran de la investigació en psicologia i neurologia. Les emocions semblen contribuir de forma essencial en processos com la percepció, l'aprenentatge, la memòria, la presa de decisions o la resolució de problemes. El mateix pensament deliberatiu racional estaria dirigit per les emocions. Tenint en compte aquesta nova visió de les emocions, en aquest treball s'ha investigat el paper de l'emoció en els processos cognitius d'un agent artificial relacionats amb la presa de decisions en general, no només pel que fa als processos d'interrelació social. Així per exemple, en l'aplicació considerada com a cas d'estudi d'aquest treball, l'agent emocional controla una plataforma de robot mòbil de servei, en què no hi ha una capa de comportament social important, i on els processos emocionals motiven fonamentalment els comportaments relacionats amb problemes sorgits en un entorn físic, amb objectes, peces, o espais d'operació i navegació. En aquesta tesi es defineix una especificació per a l'arquitectura d'agent emocional artificial proposta i es discuteixen aspectes d'implementació de la arquitectura.Domínguez Montagud, CP. (2017). Arquitectura de Agente Emocional para Aplicaciones de Control en Tiempo Real [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/86223TESISCompendi

Emotional robot control architecture implementation using FPGAs

[EN] Emotional control architectures are becoming promising solutions for the design of the robots of the future. The emotions motivate the robot behaviors to fulfill the objectives. The workload of the emotions increases with the complexity of the applications, which reduces the capacity of the processor to undertake more complex problems. A simple but costly solution would be the use of high performance computers to solve the complex problems. However, taking advantage of the potential parallelism of the emotions, this paper proposes a less expensive solution using low cost Cyclone FPGAs. Different FPGA devices are compared to analyze their suitability to cope with different industrial mobile robotic applications. The experiments are conducted taking into account different environmental conditions, robot dynamics and emotional states. The results of the evaluation show that Cyclone V outperforms the original RT-SW solution in 5 times and can undertake the 97% of the problems of the robot, while Cyclone IV improves the performances in about 4 times solving medium and few complex problems. Cyclone 2 and 3 double the performance of the RT-SW and are useful for simple robotic applications. (C) 2016 Elsevier B.V. All rights reserved.This work was supported in part under Grant FP7 ICT Dreams and Grant PAID/2012/325.Domínguez Montagud, CP.; Hassan Mohamed, H.; Crespo, A. (2017). Emotional robot control architecture implementation using FPGAs. Journal of Systems Architecture. 72:29-41. https://doi.org/10.1016/j.sysarc.2016.08.004S29417