Modularity in robotic systems

Most robotic systems today are designed one at a time, at a high cost of time and money. This wasteful approach has been necessary because the industry has not established a foundation for the continued evolution of intelligent machines. The next generation of robots will have to be generic, versatile machines capable of absorbing new technology rapidly and economically. This approach is demonstrated in the success of the personal computer, which can be upgraded or expanded with new software and hardware at virtually every level. Modularity is perceived as a major opportunity to reduce the 6 to 7 year design cycle time now required for new robotic manipulators, greatly increasing the breadth and speed of diffusion of robotic systems in manufacturing. Modularity and its crucial role in the next generation of intelligent machines are the focus of interest. The main advantages that modularity provides are examined; types of modules needed to create a generic robot are discussed. Structural modules designed by the robotics group at the University of Texas at Austin are examined to demonstrate the advantages of modular design

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

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Accept mobile: a mobile tool for the SINMETRO accept information system

Increasing demand of mobile applications for on-site data acquisition pushes the development of flexible and easy to use mobile tools, with great advantages over the traditional computer-based approaches. The Accept System from SINMETRO allows data gathering for quality control, in the form of Inspection sheets. Such tool allows quality assurance by monitoring some samples of a given material, for instance milk, wine, and even maintenance management. This paper presents a mobile application in the Accept System that allows a Personal Digital Assistant (PDA) device to perform data gathering based on XML Inspection templates. Using .NET Compact Framework through C#, and database the technologies SQL Server and SQL Server CE, we developed Accept Mobile. Accept Mobile uses the Remote Data Access (RDA) mechanism to send data over to the server through a synchronization service, while also providing the needed support for disconnected operation. We prove that the mobile application is very convenient and provides enough functionality for the user to dismiss the portable computer, although the main application was never developed with mobility concerns in mind

An implementation of a versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV camera and lenses

This thesis studies and implements a new versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV camera and lenses developed by Roger Tsai [1]. This technique builds up a unique relationship from the world coordinate system to the computer image coordinate system of calibration points by using a radial alignment constraint. The technique has advantage in terms of accuracy, speed, and versatility over existing techniques. The fundamental knowledge for using this technique is presented in this thesis first, followed by an overview of the existing calibration techniques, and a detailed description of the new technique. The implementation is then presented step by step and is algorithm-oriented. Finally, the experimental results using real data are reported. A precise calibration pattern, a CCD camera with zoom lens and a DADACUBE image acquisition system are used for the implementation of the calibration technique. This thesis supplies the calibrated parameters for researchers who will use the CCD camera in their research, and may pave the way for future research in camera calibration

Enhancing Infrastructure Safety: A UAV-Based Approach for Crack Detection

The imperative task of identifying and promptly detecting cracks in concrete bridges is crucial for preserving their structural health and ensuring the safety of users. Traditional bridge inspection methods heavily rely on human eyes and additional tools, demanding extensive training for inspectors and resulting in time-consuming processes. The increasing demand for Unmanned Aerial Vehicles (UAVs) has provided a transformative solution to access hard-to-reach areas efficiently. This research explores the integration of deep learning algorithms, including CNN, RCNN, Fast RCNN, Faster RCNN, and YOLO, to enhance the accuracy and efficiency of UAV-based crack detection systems. Experimental results affirm the effectiveness of these algorithms in addressing challenges such as lighting variations and small crack detection. The study aims to contribute to structural health monitoring, improving maintenance practices, and enhancing safety