Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

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)

An analysis on controlling humanoid robot arm using Robot Operating System (ROS)

Humanoid robots are extensively discussed in modern days. The movement task and manipulation of Humanoid Robots is examined based on mobility of platforms and control of the arm. This project describes a robotic arm that is analogous to an arm of a human being. Some important parameters to be considered are reachability, stability and manipulability. This thesis aims at adapting a humanoid robot arm for performing movement operation that can be used for various purposes. The proposed robot arm has 3 motors on the left arm and 3 motors on the right arm thereby constituting a total of 6 motors. This operation can be achieved by the use of sensor like ultrasonic sensor. Here Beaglebone Black, an open source linux based controller board is used. The Beaglebone Black acts as the main controller for the entire system. A research is also being made to implement the robotic arm using Robot Operating System (ROS) platform. ROS is preferred since it is modular, simple and easy to use tools for development, it provides good hardware support, lots of algorithms are implemented together as package, etc

Application of LEGO Mindstorms Kits for Teaching Mechatronics Engineering

One of the major educators’ challenges is to teach the theoretical lessons with practical examples that can be taught in the classroom or teaching laboratories. The application of these examples will face a major problem for students in engineering: the difficulty of understanding and seeing how a mechatronic device works in everyday life. This requires the use of tools that enable the construction of different low cost prototypes to assist in student learning. Another challenge to educators is the need to motivate students during the lessons and to present models that students can make and develop on their own. Within this context this paper presents a pedagogic proposition based on the use of LEGO Mindstorms kits to teach practical lab activities in a mechatronics engineering course. The objective is to develop teaching methodologies with the use of these LEGO kits in order to motivate the students and also to promote a higher interdisciplinarity, by proposing projects that unify different disciplines. Thus, the paper is divided into three parts according to the educational experiences implemented in the course of mechatronics engineering at the Federal University of Uberlândia, Brazil. The first part presents the use of the kits in robotics discipline. The second part presents the use of the virtual kits in the Computer Aided Design discipline with zero-cost. The third part presents a multi-disciplinary project EDROM in mechatronics using LEGO kits

Mechatronics versus Robotics

In Bolton, mechatronics is defined as the integration of electronics, control engineering, and mechanical engineering, thus recognizing the fundamental role of control in joining electronics and mechanics. A robot is commonly considered as a typical mechatronic system, which integrates software, control, electronics, and mechanical designs in a synergistic manner. Robotics can be considered as a part of mechatronics; i.e., all robots are mechatronic systems, but not all mechatronic systems are robots. Advanced robots usually plan their actions by combining an assigned functional task with the knowledge about the environment in which they operate. By using a simplified approach, advanced robots could be defined as mechatronic devices governed by a smart brain, placed at a higher hierarchical level. Actuators are building blocks of any mechatronic system. Such systems, however, have a huge application span, ranging from low-cost consumer applications to high-end, high-precision industrial manufacturing equipment

Deep learning systems for estimating visual attention in robot-assisted therapy of children with autism and intellectual disability

Recent studies suggest that some children with autism prefer robots as tutors for improving their social interaction and communication abilities which are impaired due to their disorder. Indeed, research has focused on developing a very promising form of intervention named Robot-Assisted Therapy. This area of intervention poses many challenges, including the necessary flexibility and adaptability to real unconstrained therapeutic settings, which are different from the constrained lab settings where most of the technology is typically tested. Among the most common impairments of children with autism and intellectual disability is social attention, which includes difficulties in establishing the correct visual focus of attention. This article presents an investigation on the use of novel deep learning neural network architectures for automatically estimating if the child is focusing their visual attention on the robot during a therapy session, which is an indicator of their engagement. To study the application, the authors gathered data from a clinical experiment in an unconstrained setting, which provided low-resolution videos recorded by the robot camera during the child–robot interaction. Two deep learning approaches are implemented in several variants and compared with a standard algorithm for face detection to verify the feasibility of estimating the status of the child directly from the robot sensors without relying on bulky external settings, which can distress the child with autism. One of the proposed approaches demonstrated a very high accuracy and it can be used for off-line continuous assessment during the therapy or for autonomously adapting the intervention in future robots with better computational capabilities