Overview of technologies for building robots in the classroom

This paper aims to give an overview of technologies that can be used to implement robotics within an educational context. We discuss complete robotics systems as well as projects that implement only certain elements of a robotics system, such as electronics, hardware, or software. We believe that Maker Movement and DIY trends offers many new opportunities for teaching and feel that they will become much more prominent in the future. Products and projects discussed in this paper are: Mindstorms, Vex, Arduino, Dwengo, Raspberry Pi, MakeBlock, OpenBeam, BitBeam, Scratch, Blockly and ArduBlock

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

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

Teaching humanoid robotics by means of human teleoperation through RGB-D sensors

This paper presents a graduate course project on humanoid robotics offered by the University of Padova. The target is to safely lift an object by teleoperating a small humanoid. Students have to map human limbs into robot joints, guarantee the robot stability during the motion, and teleoperate the robot to perform the correct movement. We introduce the following innovative aspects with respect to classical robotic classes: i) the use of humanoid robots as teaching tools; ii) the simplification of the stable locomotion problem by exploiting the potential of teleoperation; iii) the adoption of a Project-Based Learning constructivist approach as teaching methodology. The learning objectives of both course and project are introduced and compared with the students\u2019 background. Design and constraints students have to deal with are reported, together with the amount of time they and their instructors dedicated to solve tasks. A set of evaluation results are provided in order to validate the authors\u2019 purpose, including the students\u2019 personal feedback. A discussion about possible future improvements is reported, hoping to encourage further spread of educational robotics in schools at all levels

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

Low-cost, multi-agent systems for planetary surface exploration

The use of off-the-shelf consumer electronics combined with top-down design methodologies have made small and inexpensive satellites, such as CubeSats, emerge as viable, low-cost and attractive space-based platforms that enable a range of new and exciting mission scenarios. In addition, to overcome some of the resource limitation issues encountered with these platforms, distributed architectures have emerged to enable complex tasks through the use of multiple low complexity units. The low-cost characteristics of such systems coupled with the distributed architecture allows for an increase in the size of the system beyond what would have been feasible with a monolithic system, hence widening the operational capabilities without significantly increasing the control complexity of the system. These ideas are not new for Earth orbiting devices, but excluding some distributed remote sensing architectures they are yet to be applied for the purpose of planetary exploration. Experience gained through large rovers demonstrates the value of in-situ exploration, which is however limited by the associated high-cost and risk. The loss of a rover can and has happened because of a number of possible failures: besides the hazards directly linked to the launch and journey to the target-body, hard landing and malfunctioning of parts are all threats to the success of the mission. To overcome these issues this paper introduces the concept of using off-the-shelf consumer electronics to deploy a low-cost multi-rover system for future planetary surface exploration. It is shown that such a system would significantly reduce the programmatic-risk of the mission (for example catastrophic failure of a single rover), while exploiting the inherent advantages of cooperative behaviour. These advantages are analysed with a particular emphasis put upon the guidance, navigation and control of such architectures using the method of artificial potential field. Laboratory tests on multi-agent robotic systems support the analysis. Principal features of the system are identified and the underlying advantages over a monolithic single-agent system highlighted