Open Source Software Architecture Research Articles

The Smart Drifter Cluster: Monitoring Sea Currents and Marine Litter Transport Using Consumer IoT Technologies.

The study of marine Lagrangian transport holds significant importance from a scientific perspective as well as for practical applications such as environmental-pollution responses and prevention (e.g., oil spills, dispersion/accumulation of plastic debris, etc.). In this regard, this concept paper introduces the Smart Drifter Cluster: an innovative approach that leverages modern "consumer" IoT technologies and notions. This approach enables the remote acquisition of information on Lagrangian transport and important ocean variables, similar to standard drifters. However, it offers potential benefits such as reduced hardware costs, minimal maintenance expenses, and significantly lower power consumption compared to systems relying on independent drifters with satellite communication. By combining low power consumption with an optimized, compact integrated marine photovoltaic system, the drifters achieve unlimited operational autonomy. With the introduction of these new characteristics, the Smart Drifter Cluster goes beyond its primary function of mesoscale monitoring of marine currents. It becomes readily applicable to numerous civil applications, including recovering individuals and materials at sea, addressing pollutant spills, and tracking the dispersion of marine litter. An additional advantage of this remote monitoring and sensing system is its open-source hardware and software architecture. This fosters a citizen-science approach, enabling citizens to replicate, utilize, and contribute to the improvement of the system. Thus, within certain constraints of procedures and protocols, citizens can actively contribute to the generation of valuable data in this critical field.

Open Source Software Architecture for Computer Based Procedure Systems

In the US and globally Advanced Reactors are being developed. These Nuclear Power Plants (NPP) will utilize modern engineering and simulation tools, as well as modern control systems. New plants are safer and more flexible than previous generations. New opportunities exist for how plants could manage and operate reactors. Specifically, future plants could utilize fleet management and reduced staffing to decrease operational expenses. Tools are needed to support the development of computer-based procedure systems for advanced reactors. Here we find inspiration from scientific open source software tools (Python, Jupyter Notebook, Jupytext, Jupyter Book, Rmarkdown, Rstudio, MarkDown, MyST, Sphinx, Git) for rapid prototyping and evaluation of computer based procedure systems to support the design and evaluation of novel concept of operations for new reactors, conducting engineering tests, validating and optimizing operations using machine learning.

Continuous-Time Vs. Discrete-Time Vision-Based SLAM: A Comparative Study

Robotic practitioners generally approach the vision-based SLAM problem through discrete-time formulations. This has the advantage of a consolidated theory and very good understanding of success and failure cases. However, discrete-time SLAM needs tailored algorithms and simplifying assumptions when high-rate and/or asynchronous measurements, coming from different sensors, are present in the estimation process. Conversely, continuous-time SLAM, often overlooked by practitioners, does not suffer from these limitations. Indeed, it allows integrating new sensor data asynchronously without adding a new optimization variable for each new measurement. In this way, the integration of asynchronous or continuous high-rate streams of sensor data does not require tailored and highly-engineered algorithms, enabling the fusion of multiple sensor modalities in an intuitive fashion. On the down side, continuous time introduces a prior that could worsen the trajectory estimates in some unfavorable situations. In this work, we aim at systematically comparing the advantages and limitations of the two formulations in vision-based SLAM. To do so, we perform an extensive experimental analysis, varying robot type, speed of motion, and sensor modalities. Our experimental analysis suggests that, independently of the trajectory type, continuous-time SLAM is superior to its discrete counterpart whenever the sensors are not time-synchronized. In the context of this work, we developed, and open source, a modular and efficient software architecture containing state-of-the-art algorithms to solve the SLAM problem in discrete and continuous time.

Modular Multi-Domain Aware Autonomous Surface Vehicle for Inspection

A growing interest in ocean exploration for scientific and commercial research has been shown, mainly due to the technological developments for maritime and offshore industries. The use of Autonomous surface vehicles (ASV) have a promising role to revolutionize the transportation, monitorization, operation and maintenance areas, allowing to perform distinct task from offshore assets inspection to harbor patrolling. This work presents SENSE, an autonomouS vEssel for multi-domaiN inSpection and maintEnance. It provides an open-source hardware and software architecture that is easy to replicate for both research institutes and industry. This is a multi-purpose vehicle capable of acquiring multi-domain data for inspecting and reconstructing maritime infrastructures. SENSE provides a research platform which can increase the situational awareness capabilities for ASVs. SENSE full configuration provides multimodal sensory data acquired from both domains using a Light Detection And Ranging (LiDAR), a stereoscopic camera, and a multibeam echosounder. In addition, it supplies navigation information obtained from a real-time kinematic satellite navigation system and inertial measurement units. Moreover, the tests performed at the harbor of Marina de Leça, at Porto, Portugal, resulted in a dataset which captures a fully operational harbor. It illustrates several conditions on maritime scenarios, such as undocking and docking examples, crossings with other vehicles and distinct types of moored vessels. The data available represents both domains of the maritime scenario, being the first public dataset acquired for multi-domain observation using a single vehicle. This paper also provides examples of applications for navigation and inspection on multi-domain scenarios, such as odometry estimation, bathymetric surveying and multi-domain mapping.

Versatile Locomotion Planning and Control for Humanoid Robots.

We propose a locomotion framework for bipedal robots consisting of a new motion planning method, dubbed trajectory optimization for walking robots plus (TOWR+), and a new whole-body control method, dubbed implicit hierarchical whole-body controller (IHWBC). For versatility, we consider the use of a composite rigid body (CRB) model to optimize the robot’s walking behavior. The proposed CRB model considers the floating base dynamics while accounting for the effects of the heavy distal mass of humanoids using a pre-trained centroidal inertia network. TOWR+ leverages the phase-based parameterization of its precursor, TOWR, and optimizes for base and end-effectors motions, feet contact wrenches, as well as contact timing and locations without the need to solve a complementary problem or integer program. The use of IHWBC enforces unilateral contact constraints (i.e., non-slip and non-penetration constraints) and a task hierarchy through the cost function, relaxing contact constraints and providing an implicit hierarchy between tasks. This controller provides additional flexibility and smooth task and contact transitions as applied to our 10 degree-of-freedom, line-feet biped robot DRACO. In addition, we introduce a new open-source and light-weight software architecture, dubbed planning and control (PnC), that implements and combines TOWR+ and IHWBC. PnC provides modularity, versatility, and scalability so that the provided modules can be interchanged with other motion planners and whole-body controllers and tested in an end-to-end manner. In the experimental section, we first analyze the performance of TOWR+ using various bipeds. We then demonstrate balancing behaviors on the DRACO hardware using the proposed IHWBC method. Finally, we integrate TOWR+ and IHWBC and demonstrate step-and-stop behaviors on the DRACO hardware.

Power to the People

How embracing open-source software architecture can provide the best of both worlds for customers.

A Densely-Deployed, High Sampling Rate, Open-Source Air Pollution Monitoring WSN

Air quality, especially particulate matter, has recently attracted a lot of attention from governments, industry, and academia, motivating the use of denser air quality monitoring networks based on low-cost sensing strategies. However, low-cost sensors are frequently sensitive to aging, environmental conditions, and pollutant cross-sensitivities. These issues have been only partially addressed, limiting their usage. In this study, we develop a low-cost particulate matter monitoring system based on special-purpose acquisition boards, deployed for monitoring air quality on both stationary and mobile sensor platforms. We explore the influence of all model variables, the quality of different calibration strategies, the accuracy across different concentration ranges, and the usefulness of redundant sensors placed in each station. The collected sensor data amounts to about 50GB of data, gathered in six months during the winter season. Tests of statically immovable stations include an analysis of accuracy and sensors’ reliability made by comparing our results with more accurate and expensive standard $\beta$ -radiation sensors. Tests on mobile stations have been designed to analyze the reactivity of our system to unexpected and abrupt events. These experiments embrace traffic analysis, pollution investigation using different means of transport and pollution analysis during peculiar events. With respect to other approaches, our methodology has been proved to be extremely easy to calibrate, to offer a very high sample rate (one sample per second), and to be based on an open-source software architecture. Database and software are available as open source in [1] .

A wearable sensor vest for social humanoid robots with GPGPU, IoT, and modular software architecture

Currently, most social robots interact with their surroundings and humans through sensors that are integral parts of the robots, which limits the usability of the sensors, human–robot interaction, and interchangeability. A wearable sensor garment that fits many robots is needed in many applications. This article presents an affordable wearable sensor vest, and an open-source software architecture with the Internet of Things (IoT) for social humanoid robots. The vest consists of touch, temperature, gesture, distance, vision sensors, and a wireless communication module. The IoT feature allows the robot to interact with humans locally and over the Internet. The designed architecture works for any social robot that has a general-purpose graphics processing unit (GPGPU), I2C/SPI buses, Internet connection, and the Robotics Operating System (ROS). The modular design of this architecture enables developers to easily add/remove/update complex behaviors. The proposed software architecture provides IoT technology, GPGPU nodes, I2C and SPI bus mangers, audio-visual interaction nodes (speech to text, text to speech, and image understanding), and isolation between behavior nodes and other nodes. The proposed IoT solution consists of related nodes in the robot, a RESTful web service, and user interfaces. We used the HTTP protocol as a means of two-way communication with the social robot over the Internet. Developers can easily edit or add nodes in C, C++, and Python programming languages. Our architecture can be used for designing more sophisticated behaviors for social humanoid robots.

Open and Flexible Li-ion Battery Tester Based on Python Language and Raspberry Pi

Technology improvements and cost reduction allow electrochemical energy storage systems based on Lithium-ion cells to massively be used in medium-power applications, where the low system cost is the major constraint. Battery pack maintenance services are expected to be required more often in the future. For this reason, a low-cost instrumentation able to characterize the cells of a battery pack is needed. Several works use low-cost programmable units as Li-ion cell tester, but they are generally based on proprietary-software running on a personal computer. This work introduces an open-source software architecture based on Python language to control common low-cost commercial laboratory instruments. The Python software application is executed on a Raspberry Pi board, which represents the control block of the hardware architecture, instead of a personal computer. The good results obtained during the validation process demonstrate that the proposed cell station tester features measurement accuracy and precision suitable for the characterization of Li-ion cells. Finally, as a simple example of application, the state of health of twenty 40 Ah LiFePO4 cells belonging to a battery pack used in an E-scooter was successfully determined.

Modelling, Validation and Quantification of Climate and Other Sensitivities of Building Energy Model on 3D City Models

New planning tools are required to depict the complete building stock in a city and investigate detailed measures on reaching local and global targets to improve energy efficiency and reduce greenhouse gas emissions. To pursue this objective, ISO (the International Organization for Standardization) 13790:2008 monthly heating and cooling energy calculation method is implemented using geometric information from 3D city models (e.g., CityGML format) in an open source software architecture. A model is developed and applied in several urban districts with different number of 3D buildings in various cities. The model is validated with the simulation software TRNSYS. We also perform a sensitivity analysis to quantify the impact of climate change and other physical and behavioral factors on modelling results. The proposed approach can help to perform city or district-wide analysis of the building energy needs and prepare different renovation plans to support decision-making, which finally will enhance the livability of a city and the quality of life of the citizens.

Software Architecture Solution Based on SDN for an Industrial IoT Scenario

The Industry 4.0 (I4.0) adoption comprises the change of traditional factories intosmartusing the ICTs. The goal is to monitor processes, objects, machinery, and workers in order to have real-time knowledge about what is going on in the factory and for achieving an efficient data collection, management, and decision-making that help improve the businesses in terms of product quality, productivity, and efficiency. Internet of Things (IoT) will have an important role in the I4.0 adoption because future smart factories are expected to rely on IoT infrastructures composed of constellations of hundreds or thousands of sensor devices spread all over the industrial facilities. However, some problems could arise in the massive IoT deployment in a medium-high factory: thousands of IoT devices to cope from different technologies and vendors could mean dozens of vendor tools and user interfaces to manage them. Moreover, the heterogeneity of IoT devices could entail different communication protocols, languages, and data formats, which can result in lack of interoperability. On the other hand, conventional IT networks and industrial machinery are expected to be managed together with the IoT infrastructure, maybe using a tool or a set of tools, fororchestratingthe whole smart factory. This work meets these challenges presenting an open-source software architecture solution based on OpenDaylight (ODL), a Software Defined Network (SDN) controller, for orchestrating an industrial IoT scenario. This work is addressed by shedding light on critical aspects from the SDN controller architectural choices, to specific IoT interfaces and the difficulties for covering the wide range of communication protocols, popular in industrial contexts. Such a global view of the process gives light to practical difficulties appearing in introducing SDN in industrial contexts, providing an open-source architecture solution that guarantees devices and networks interoperability and scalability, breaking the vendor lock-in barriers and providing a vendor-agnostic solution for orchestrating all actor of an I4.0 smart factory.

Modeling the natural UV irradiation and comparative UV measurements at Moussala BEO (BG)

Studies of and modeling the impact of natural UV irradiation on the human population are of significant importance for human activity and economics. The sharp increase of environmental problems – extraordinary temperature changes, solar irradiation abnormalities, icy rains – raises the question of developing novel means of assessing and predicting potential UV effects. In this paper, we discuss new UV irradiation modeling based on recent real-time measurements at Moussala Basic Environmental Observatory (BEO) on Moussala Peak (2925 m ASL) in Rila Mountain, Bulgaria, and highlight the development and initial validation of portable embedded devices for UV-A, UV-B monitoring using open-source software architecture, narrow bandpass UV sensors, and the popular Arduino controllers. Despite the high temporal resolution of the VIS and UV irradiation measurements, the results obtained reveal the need of new assumptions in order to minimize the discrepancy with available databases.

Abstract 2602: The ICGC data portal and its underlying open source software architecture

Abstract The goal of the International Cancer Genome Consortium (ICGC) is to analyze the cancer genomes of at least 500 tumour samples with matched controls from 50 different cancer types and subtypes, building a comprehensive catalogue of somatic abnormalities for the benefit of the research community. The amount of data ICGC members will generate is close to that of 50,000 human genome projects and, to date, has received commitments for 107 projects to study more than 27,000 tumor genomes. The ICGC Data Coordination Center (DCC) is responsible for collecting, curating, aggregating, and disseminating the data generated by the consortium’s member projects. Given the size and the complexity of the ICGC data, these tasks represent significant scientific and technological challenges that require a performant, robust software infrastructure. Key to this infrastructure is the ability to scale as data grows. Using state-of-the-art Big Data, bioinformatics and cloud computing technologies, we developed a suite of web-based applications and microservices that enable member projects to first submit their data and validate their submissions according to the rules defined in the submission specification. Following validation, the data is processed, annotated and loaded into the data portal using a modular Extract-Transform-Load (ETL) pipeline. Submission, ETL and portal systems are built using scalable and distributed technologies such as Hadoop, Spark, MongoDB and ElasticSearch. Spark is used to validate, join, index, and harmonize annotations on submitted variants while ElasticSearch powers our variant query engine, API and portal displays. Here we present the ICGC Data Portal and describe both the current features and capabilities accessible to users along with the architecture of the underlying infrastructure. The portal provides scientists with powerful and unique tools for exploring and visualizing the millions of variants and annotations available. These include sophisticated, faceted search capabilities making data exploration extremely fast and easy, a suite of interactive Javascript components for in-depth analysis and visualization of specific genomic features, embedded genome and pathway browsers, synthetic cohorts comparisons and a streaming data download service. The portal integrates a large variety of annotations such as variant consequences and frequencies, functional impact factors and druggability. The portal also offers cloud-based tools for searching a catalog of raw ICGC data files stored in worldwide repositories and compute clouds. All source code is open to the community under the GPLv3 license. Citation Format: Junjun Zhang, Bob Tiernay, Dusan Andric, Phuong-My Do, Sid Joshi, Vitalii Slobodianyk, Chang Wang, Shane Wilson, Andy Yang, Vincent Ferretti. The ICGC data portal and its underlying open source software architecture [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2602. doi:10.1158/1538-7445.AM2017-2602

Software Quality, Energy Awareness, and More

This article discusses six papers presented at events connected with the 2015 International Conference on Software Engineering. The papers cover organizational factors and software quality, microclones, big data platforms, energy-aware commits, open source software architecture, and requirements engineering.

Developing a research and practice tool to measure walkability: a demonstration project.

Growing evidence shows that higher-density, mixed-use, pedestrian-friendly neighbourhoods encourage active transport, including transport-related walking. Despite widespread recognition of the benefits of creating more walkable neighbourhoods, there remains a gap between the rhetoric of the need for walkability and the creation of walkable neighbourhoods. Moreover, there is little objective data to benchmark the walkability of neighbourhoods within and between Australian cities in order to monitor planning and design intervention progress and to assess built environment and urban policy interventions required to achieve increased walkability. This paper describes a demonstration project that aimed to develop, trial and validate a 'Walkability Index Tool' that could be used by policy makers and practitioners to assess the walkability of local areas; or by researchers to access geospatial data assessing walkability. The overall aim of the project was to develop an automated geospatial tool capable of creating walkability indices for neighbourhoods at user-specified scales. The tool is based on open-source software architecture, within the Australian Urban Research Infrastructure Network (AURIN) framework, and incorporates key sub-component spatial measures of walkability (street connectivity, density and land use mix). Using state-based data, we demonstrated it was possible to create an automated walkability index. However, due to the lack of availability of consistent of national data measuring land use mix, at this stage it has not been possible to create a national walkability measure. The next stage of the project is to increase useability of the tool within the AURIN portal and to explore options for alternative spatial data sources that will enable the development of a valid national walkability index. AURIN's open-source Walkability Index Tool is a first step in demonstrating the potential benefit of a tool that could measure walkability across Australia. It also demonstrates the value of making accurate spatial data available for research purposes. SO WHAT?: There remains a gap between urban policy and practice, in terms of creating walkable neighbourhoods. When fully implemented, AURIN's walkability tool could be used to benchmark Australian cities against which planning and urban design decisions could be assessed to monitor progress towards achieving policy goals. Making cleaned data readily available for research purposes through a common portal could also save time and financial resources.

MOOS-IvP를 이용한 무인잠수정 제어기 개발의 효용성

This paper demonstrates the benefit of using MOOS-IvP in the development of control system for Unmanned Underwater Vehicles(UUV). The demand for autonomy in UUVs has significantly increased due to the complexity in missions to be performed. Furthermore, the increased number of sensors and actuators that are interconnected through a network has introduced a need for a middleware platform for UUVs. In this context, MOOS-IvP, which is an open source software architecture, has been developed by several researchers from MIT, Oxford University, and NUWC. The MOOS software is a communication middleware based on the publish-subscribe architecture allowing each application to communicate through a MOOS database. The IvP Helm, which is one of the MOOS modules, publishes vehicle commands using multi-objective optimization in order to implement autonomous decision making. This paper explores the benefit of MOOS-IvP in the development of control software for UUVs by using a case study with an auto depth control system based on self-organizing fuzzy logic control. The simulation results show that the design and verification of UUV control software based on MOOS-IvP can be carried out quickly and efficiently thanks to the reuse of source codes, modular-based architecture, and the high level of scalability.

Public Participation GIS: a FOSS architecture enabling field-data collection

Driven by the rise of Web 2.0 and the non-stop spread of mobile device sensors, the concept of Public Participation GIS (PPGIS) is knowing a revolutionary era which perfectly fits the new vision of Digital Earth (DE). This research investigates the opportunity to build up a PPGIS prototype with completely Free and Open Source Software (FOSS) architecture, in which data directly come from field surveys carried out by users. A sample application related to urban monitoring is addressed, which concentrates on user field-collected data concerning reports of road pavement damages. Open Data Kit suite allows users to collect geotagged multimedia information using mobile devices with onboard location sensors (e.g. a Global Positioning System receiver). On field-captured data are sent to a server and stored into a PostgreSQL database with PostGIS spatial extension. GeoServer then disseminates data on the Web. On the client-side, different solutions allow data visualization on both desktop computers and mobile devices. The designed architecture provided support for FOSS usage in the process of gathering, uploading, and Web publishing information collected in situ. The implementation of the developed PPGIS could thus substantially increase public active participation in data creation and sharing, besides enlarging DE knowledge up to the local level.

Joint Effect of Team Structure and Software Architecture in Open Source Software Development

In this study, we seek to understand socio-technical interactions in a system development context via an examination of the joint effect of developer team structure and open source software (OSS) architecture on OSS development performance. Using detailed data collected from code repositories from Soure-Forge.com, we find that developer team structure and software architecture significantly moderate each other's effect on OSS development performance. Larger teams tend to produce more favorable project performance when the project being developed has a high level of structural interdependency while projects with a low level of structural interdependency require smaller teams in order to achieve better project performance. Meanwhile, centralized teams tend to have a positive impact on project performance when the OSS project has a high level of structural interdependency. However, when a project has a low level of structural interdependency, centralized teams can impair project performance. This study extends our understanding of information technology's deep engagement in organizational life and provides directions for open source practitioners to better organize their projects to achieve greater performance.

The Sharing Partnership for Innovative Research in Translation (SPIRiT) Consortium: A Model for Collaboration across CTSA Sites

In 2006, the National Institutes of Health (NIH) created the Clinical and Translational Science Award (CTSA) program to “transform the local, regional and national environment for clinical and translational science, thereby increasing the efficiency and speed of clinical and translational research.”1 Since then, 61 CTSA-funded sites have reengineered their local research enterprises to develop cadres of highly trained translational scientists and provide them with a robust array of research resources. Now under the direction of the National Center for Advancing Translational Science (NCATS), the maturing CTSA program is poised to enter its second stage of development to provide “institutions with greater flexibility and more opportunities to build on institutional strengths.”2 This approach is supported by a new CTSA Funding Opportunity Announcement (FOA) that will enable CTSA sites to develop programs to address the specific needs of their investigators and local communities. As a result, institutional CTSA programs will likely evolve from a model that provides a set of common research resources locally to unique programs with a mix of core infrastructure (e.g., training, informatics) that is supplemented by institution-specific resources (e.g., drug discovery, comparative effectiveness research, and research implementation and dissemination cores). Leveraging complementary institutional capabilities through closer collaborations between CTSA sites is the logical next step for the National CTSA Consortium. During the formative years of the CTSA program, several sites forged collaborations by creating regional consortia based on geographic proximity to enable sharing of local resources and meetings of trainees.3 For example, the Chicago Consortium for Community Engagement represents a collaboration among the three Chicago CTSAs to advance coordinated and synergistic approaches to developing community-partnered research, disseminating research results, and providing training in community engagement methods to collaborators in academic and community-based organizations. The Ohio Consortium of three CTSA sites implemented a statewide central institutional review board model. In Texas, several institutions meet to exchange best practices. However, collaborative efforts that are constrained by geographic location may limit the benefits that can be derived from linking scientists, institutions, resources, and innovative tools across an array of institutions with complementary capabilities. Accordingly, six geographically dispersed CTSA sites (Johns Hopkins University, University of Chicago, University of Pennsylvania, University of Pittsburgh, Washington University at St. Louis, Yale University) formed a “virtual CTSA consortium” based on a shared vision for data sharing and prior collaborations focused on informatics initiatives. The initial goals of the six-site Sharing Partnership for Innovative Research in Translation (SPIRiT) Consortium were 1) to develop a data sharing infrastructure for biospecimen-based research and de-identified clinical research data, and 2) to establish inter-institutional collaborations related to pilot studies, regulatory support, core laboratory facilities, and education and career development. Over the past two years, the SPIRiT Consortium embarked on several initiatives to achieve these goals, including the deployment of an informatics software and regulatory infrastructure to enable discovery and sharing of banked pathology specimens, development of an inter-institutional pilot study program to link investigators, and validation of a novel technology to improve the diagnosis of malignant melanoma. These programs are described below.

R2P: an Open Source Modular Architecture for Rapid Prototyping of Robotics Applications

Since many years, roboticists are working to bring robots in our everyday lives, but only few robotic applications have reached this market. Among the reasons for this are the high costs of design and prototyping of such innovative products. Looking at the steps needed to develop new robotic applications, we identified as a major problem the lack of tools and devices targeted to rapid robot prototyping. As a consequence, the resources, either time or money, that should be invested into the development of a new idea get drained by the building of a working prototype to eventually test the idea on. In this paper, we present R2P, an open source modular architecture for rapid prototyping of robotic applications, which aims at speeding up their development. R2P is an open source modular hardware and software architecture, where off-the-shelf basic modules (e.g., sensors, actuators, controllers) are combined together in a plug-and-play way, with tools for an easy development of control software, allowing the implementation of a complex system in a simple and standardized way. R2P allows people involved in robotics, from researchers and designers to students and hobbyists, to dramatically reduce the time and efforts required to build a robot prototype, leaving much more resources to the development of new robotic applications. In this paper, we describe R2P in its main components showing how it can really help in the development of a robot prototype.