Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Using Scratch to Teach Undergraduate Students' Skills on Artificial Intelligence

This paper presents a educational workshop in Scratch that is proposed for the active participation of undergraduate students in contexts of Artificial Intelligence. The main objective of the activity is to demystify the complexity of Artificial Intelligence and its algorithms. For this purpose, students must realize simple exercises of clustering and two neural networks, in Scratch. The detailed methodology to get that is presented in the article.Comment: 6 pages, 7 figures, workshop presentatio

OPEB: Open Physical Environment Benchmark for Artificial Intelligence

Artificial Intelligence methods to solve continuous- control tasks have made significant progress in recent years. However, these algorithms have important limitations and still need significant improvement to be used in industry and real- world applications. This means that this area is still in an active research phase. To involve a large number of research groups, standard benchmarks are needed to evaluate and compare proposed algorithms. In this paper, we propose a physical environment benchmark framework to facilitate collaborative research in this area by enabling different research groups to integrate their designed benchmarks in a unified cloud-based repository and also share their actual implemented benchmarks via the cloud. We demonstrate the proposed framework using an actual implementation of the classical mountain-car example and present the results obtained using a Reinforcement Learning algorithm.Comment: Accepted in 3rd IEEE International Forum on Research and Technologies for Society and Industry 201

Safe, Remote-Access Swarm Robotics Research on the Robotarium

This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference

Digital Systems Teaching and Research (DSTR) Robot: A Flexible Platform for Education and Applied Research

The DSTR (pronounced “Disaster”) robot has a strong history of being adaptable to different user’s needs, and there are many opportunities ahead that indicate that the sky, quite literally, is not the limit for this robust platform. This paper provides a historical perspective on the development of the DSTR robot as a collaborative design developed by the Mobile Integrated Solutions Laboratory (MISL) at Texas A&M University and ASEP 4X4 Inc. Texas Instruments has been a major partner in the integration of the control electronics, and Texas Space Technology Applications and Research (T STAR) LLC has played a significant role in the propagation of the DSTR robot as an adaptable applied research/education/STEM outreach platform. The paper will present examples of the strong industry-academic relationships that allow the DSTR robot to be utilized in a multitude of experiential learning environments. In addition to a number of STEM outreach activities, the DSTR robots are being used in the Introduction to Engineering course at Blinn College and in the Freshman Engineering curriculum at Texas A&M University. DSTRs have also been selected by NASA scientists as a low-cost lunar sample collector. The paper will also discuss the newly developed DSTR-E (DSTR Engineering) unit which requires students to perform several engineering tasks during the build process. The paper will also include the lessons learned from initial design through its transfer to the private sector for commercialization and future plans.Cockrell School of Engineerin

Personal Food Computer: A new device for controlled-environment agriculture

Due to their interdisciplinary nature, devices for controlled-environment agriculture have the possibility to turn into ideal tools not only to conduct research on plant phenology but also to create curricula in a wide range of disciplines. Controlled-environment devices are increasing their functionalities as well as improving their accessibility. Traditionally, building one of these devices from scratch implies knowledge in fields such as mechanical engineering, digital electronics, programming, and energy management. However, the requirements of an effective controlled environment device for personal use brings new constraints and challenges. This paper presents the OpenAg Personal Food Computer (PFC); a low cost desktop size platform, which not only targets plant phenology researchers but also hobbyists, makers, and teachers from elementary to high-school levels (K-12). The PFC is completely open-source and it is intended to become a tool that can be used for collective data sharing and plant growth analysis. Thanks to its modular design, the PFC can be used in a large spectrum of activities.Comment: 9 pages, 11 figures, Accepted at the 2017 Future Technologies Conference (FTC

Exploring Planets with Directed Aerial Robot Explorers

Global Aerospace Corporation (GAC) is developing a revolutionary system architecture for exploration of planetary atmospheres and surfaces from atmospheric altitudes. The work is supported by the NASA Institute for Advanced Concepts (NIAC). The innovative system architecture relies upon the use of Directed Aerial Robot Explorers (DAREs), which essentially are long-duration-flight autonomous balloons with trajectory control capabilities that can deploy swarms of miniature probes over multiple target areas. Balloon guidance capabilities will offer unprecedented opportunities in high-resolution, targeted observations of both atmospheric and surface phenomena. Multifunctional microprobes will be deployed from the balloons once over the target areas, and perform a multitude of functions, such as atmospheric profiling or surface exploration, relaying data back to the balloons or an orbiter. This architecture will enable low-cost, low-energy, long-term global exploration of planetary atmospheres and surfaces. This paper focuses on a conceptual analysis of the DARE architecture capabilities and science applications for Venus, Titan and Jupiter. Preliminary simulations with simplified atmospheric models show that a relatively small trajectory control wing can enable global coverage of the atmospheres of Venus and Titan by a single balloon over a 100-day mission. This presents unique opportunities for global in situ sampling of the atmospheric composition and dynamics, atmospheric profiling over multiple sites with small dropsondes and targeted deployment of surface microprobes. At Jupiter, path guidance capabilities of the DARE platforms permits targeting localized regions of interest, such as "hot spots" or the Great Red Spot. A single DARE platform at Jupiter can sample major types of the atmospheric flows (zones and belts) over a 100-day mission. Observations by deployable probes would reveal if the differences exist in radiative, dynamic and compositional environments at these sites