The robot programming network

The Robot Programming Network (RPN) is an initiative for creating a network of robotics education laboratories with remote programming capabilities. It consists of both online open course materials and online servers that are ready to execute and test the programs written by remote students. Online materials include introductory course modules on robot programming, mobile robotics and humanoids, aimed to learn from basic concepts in science, technology, engineering, and mathematics (STEM) to more advanced programming skills. The students have access to the online server hosts, where they submit and run their programming code on the fly. The hosts run a variety of robot simulation environments, and access to real robots can also be granted, upon successful achievement of the course modules. The learning materials provide step-by-step guidance for solving problems with increasing level of dif- ficulty. Skill tests and challenges are given for checking the success, and online competitions are scheduled for additional motivation and fun. Use of standard robotics middleware (ROS) allows the system to be extended to a large number of robot platforms, and connected to other existing tele-laboratories for building a large social network for online teaching of robotics.Support of IEEE RAS through the CEMRA program (Creation of Educational Material for Robotics and Automation) is gratefully acknowledged. This paper describes research done at the Robotic Intelligence Laboratory. Support for this laboratory is provided in part by Ministerio de Economia y Competitividad (DPI2011-27846), by Generalitat Valenciana (PROMETEOII/2014/028) and by Universitat Jaume I (P1-1B2011-54)

A Case Study: Motivational Attributes of 4-H participants engaged in Robotics

Robotics has gained a great deal of popularity across the United States as a means to engage youth in science, technology, engineering, and math. Understanding what motivates youth and adults to participate in a robotics project is critical to understanding how to engage others. By developing a robotics program built on a proper understanding of the motivational influences, the program can be built on a foundation that addresses these influences. By engaging more youth in the robotics program, they will be able to envision a future for themselves as a high-school or college graduate, in addition to a viable employee with marketable skills in tough economy. The purpose of this research was to evaluate the underlying motivational attributes or factors that influenced 4-H youth, parents, volunteers, and agents to participate in the Mississippi 4-H robotics project. Specifically, this research focuses on two unique counties in Mississippi with very diverse populations. Interviews with participants, observation, and document analysis which took place occurred over the course of a robotics year – October to July. This study sought to identify motivational attributes of participants in the robotics project. Once identified these attributes could be used when developing new program curricula or expanding into new counties in Mississippi. Data analysis revealed that there are many unique motivational factors that influence participants. Among these factors, (1) the desire to build and construct a robot, (2) competition and recognition, (3) desire for future success and security, (4) safe place to participate and build relationships, (5) teamwork, (6) positive role models, and (7) encouragement

Multi-robot behaviors with bearing-only sensors and scale-free coordinates

This thesis presents a low-cost multi-robot system for large populations of robots, a new coordinate system for the robot based on angles between robots and a series of experiments validating robot performance. The new robot platform, the r-one will serve as an educational, outreach and research platform for robotics. I consider the robot's bearing-only sensor model, where each robot is capable of measuring the bearing, but not the distance, to each of its neighbors. This work also includes behaviors demonstrating the efficiency of this approach with this bearing-only sensor model. The new local coordinate systems based on angular information is introduced as scale-free coordinate system . Each robot produces its own local scale-free coordinates to determine the relative positions of its neighbors up to an unknown scaling factor. The computation of scale-free coordinates is analyzed with hardware and simulation validation. For hardware, the scale-free algorithm is tailored to low-cost systems with limited communication bandwidth and sensor resolution. The algorithm also uses a noise sensitivity model to reduce the impact of noise on the computed scale-free coordinates. I validate the algorithm with static and dynamic motion experiments

Volume 45 - Issue 08 - Friday, November 6, 2009

The Rose Thorn, Rose-Hulman\u27s independent student newspaper.https://scholar.rose-hulman.edu/rosethorn/1109/thumbnail.jp

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Legodroid: A Type-Driven Library for Android and LEGO Mindstorms Interoperability

LEGO Mindstorms robots are widely used as educational tools to acquire skills in programming complex systems involving the interaction of sensors and actuators, and they offer a flexible and modular workbench to design and evaluate user-machine interaction prototypes in the robotic area. However, there is still a lack of support to interoperability features and the need of high-level tools to program the interaction of a robot with other devices. In this paper, we introduce Legodroid, a new Java library enabling cross-programming LEGO Mindstorms robots through Android smartphones that exploits their combined computational and sensorial capabilities in a seamless way. The library provides a number of type-driven coding patterns for interacting with sensors and motors. In this way, the robustness of the software managing robot's sensors dramatically improves

A Systematic Review of Studies on Educational Robotics

There has been a steady increase in the number of studies investigating educational robotics and its impact on academic and social skills of young learners. Educational robots are used both in and out of school environments to enhance K–12 students’ interest, engagement, and academic achievement in various fields of STEM education. Some prior studies show evidence for the general benefits of educational robotics as being effective in providing impactful learning experiences. However, there appears to be a need to determine the specific benefits which have been achieved through robotics implementation in K–12 formal and informal learning settings. In this study, we present a systematic review of the literature on K–12 educational robotics. Based on our review process with specific inclusion and exclusion criteria, and a repeatable method of systematic review, we found 147 studies published from the years 2000 to 2018. We classified these studies under five themes: (1) general effectiveness of educational robotics; (2) students’ learning and transfer skills; (3) creativity and motivation; (4) diversity and broadening participation; and (5) teachers’ professional development. The study outlines the research questions, presents the synthesis of literature, and discusses findings across themes. It also provides guidelines for educators, practitioners, and researchers in areas of educational robotics and STEM education, and presents dimensions of future research

Self-Directed Learning Development in PBL

Lifelong learning is an emphasized graduate outcome for engineering professionals at the international level by the Washington Accord and at the United States national level by ABET. When a new engineer enters the profession, she will be expected to acquire new technical knowledge in order to solve a problem or create a design. Unlike her experience in college, there will not be a professor to guide this learning. The planning, execution, monitoring, and control of this learning will now fall to the new engineer. The level of the ability to succeed in this self-directed learning modality will be a function of the extent to which the lifelong learning outcome has been met. This paper studies the importance of this graduate outcome and the development of self-directed learning as the way in which the outcome is achieved. Quantitative measures are taken using the Self-Directed Learning Readiness Scale. Quantitative results show a statistically significant difference between the developments of self-regulated abilities by students in a two-year PBL curriculum as compared to students who did not undergo the PBL treatment