Machine learning applied to an intelligent and adaptive robotic inspection station

Industry 4.0 promotes the use of emergent technologies, such as Internet of Things (IoT), Big Data, Artificial Intelligence (AI) and cloud computing, sustained by cyber-physical systems to reach smart factories. The idea is to decentralize the production systems and allow to reach monitoring, adaptation and optimization to be made in real time, based on the large amount of data available at shop floor that feed the use of machine learning techniques. This technological revolution will bring significant productivity gains, resources savings and reduced maintenance costs, as machines will have information to operate more efficiently, adaptable and following demand fluctuations. This thesis discusses the application of supervised Machine Learning (ML) techniques allied with artificial vision, to implement an intelligent, collaborative and adaptive robotic inspection station, which carries out the Quality Control (QC) of Human Machine Interface (HMI) consoles, equipped with pressure buttons and Liquid Crystal Display (LCD) displays. Machine learning techniques were applied for the recognition of the operator’s face, to classify the type of HMI console to be inspected, to classify the state condition of the pressure buttons and detect anomalies in the LCD displays. The developed solution reaches promising results, with almost 100% accuracy in the correct classification of the consoles and anomalies in the pressure buttons, and also high values in the detection of defects in the LCD displays.Indústria 4.0 promove o uso de tecnologias emergentes, como Internet of Things (IoT), Big Data, artificial intelligence (AI) e cloud computing, sustentadas por sistemas ciberfísicos, como o designio de alcançar o que chamam de fábricas inteligentes. A ideia é descentralizar os sistemas de produção e permitir que a monotorização, a adaptação e a otimização sejam feitos em tempo real, com base na grande quantidade de dados disponíveis no ambiente fabril que alimentam o uso de técnicas de machine learning (ML). Esta revolução tecnológica trará ganhos significativos de produtividade, economia de recursos e custos de manutenção mais reduzidos, pois as máquinas terão informações para operar com mais eficiência, adaptáveis e acompanhar as flutuações de procura. Esta tese discute a aplicação de técnicas supervisionadas de ML, aliadas à visão artificial, para a implementação de uma estação de inspeção robótica inteligente, colaborativa e adaptativa, que realiza o controlo de qualidade de consolas HMI, equipados com botões de pressão e displays LCD. Técnicas de ML foram aplicadas para o reconhecimento facial do operador, para classificação do tipo de console HMI a ser inspecionado, para classificar a condição do estado dos botões de pressão e deteção de anomalias nos displays LCD. A solução desenvolvida alcança resultados promissores, com quase 100 % de precisão na correta classificação das consolas e anomalias nos botões de pressão, e também valores elevados de acerto na deteção de defeitos nos displays LCD

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

Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense

NASA Center for Intelligent Robotic Systems for Space Exploration

NASA's program for the civilian exploration of space is a challenge to scientists and engineers to help maintain and further develop the United States' position of leadership in a focused sphere of space activity. Such an ambitious plan requires the contribution and further development of many scientific and technological fields. One research area essential for the success of these space exploration programs is Intelligent Robotic Systems. These systems represent a class of autonomous and semi-autonomous machines that can perform human-like functions with or without human interaction. They are fundamental for activities too hazardous for humans or too distant or complex for remote telemanipulation. To meet this challenge, Rensselaer Polytechnic Institute (RPI) has established an Engineering Research Center for Intelligent Robotic Systems for Space Exploration (CIRSSE). The Center was created with a five year $5.5 million grant from NASA submitted by a team of the Robotics and Automation Laboratories. The Robotics and Automation Laboratories of RPI are the result of the merger of the Robotics and Automation Laboratory of the Department of Electrical, Computer, and Systems Engineering (ECSE) and the Research Laboratory for Kinematics and Robotic Mechanisms of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics (ME,AE,&M), in 1987. This report is an examination of the activities that are centered at CIRSSE

Rail Robot for Rail Track Inspection

Railway transportation requires constant inspections and immediate maintenance to ensure public safety. Traditional manual inspections are not only time consuming, but also expensive. In addition, the accuracy of defect detection is also subjected to human expertise and efficiency at the time of inspection. Computing and Robotics offer automated IoT based solutions where robots could be deployed on rail-tracks and hard to reach areas, and controlled from control rooms to provide faster and low-cost inspection. In this thesis, a novel automated system based on robotics and visual inspection is proposed. The system provides local image processing while inspecting and cloud storage of information that consist of images of the defected railway tracks only. The proposed system utilizes state of the art Machine Learning system and applies it on the images obtained from the tracks in order to classify them as normal or suspicious. Such locations are then marked and more careful inspection can be performed by a dedicated operator with very few locations to inspect (as opposed to the full track)

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based 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

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS