Robotic Maintenance and ROS - Appearance Based SLAM and Navigation With a Mobile Robot Prototype

Robotic maintenance has been a topic in several master's theses and specialization projects at the Department of Engineering Cybernetics (ITK) at NTNU over many years. This thesis continues on the same topic, with special focus on camera-based mapping and navigation in conjunction with automated maintenance, and automated maintenance in general. The objective of this thesis is to implement one or more functionalities based on camera-based sensors in a mobile autonomous robot. This is accomplished by acquiring knowledge of existing solutions and future requirements within automated maintenance. A mobile robot prototype has been configured to run ROS (Robot Operating System), a middleware framework that is suited to the development of robotic systems. The system uses RTAB-Map (Real-Time Appearance Based Mapping) to survey the surroundings and a built navigation stack in ROS to navigate autonomously against easy targets in the map. The method uses a Kinect for Xbox 360 as the main sensor and a 2D laser scanner to the surveying and odometry. It is also developed functional concepts for two support functions, an Android application for remote control over Bluetooth and a remote central (OCS) developed in Qt. Remote Central is a skeletal implementation that is able to remotely control the robot via WiFi, as well as to display video from the robot's camera. Test results, obtained from both live and simulated trials, indicate that the robot is able to form 3D and 2D map of the surroundings. The method has weaknesses that are related to the ability to find visual features. Laser Based odometry can be tricked when the environment is changing, and when there are few unique features. Further testing has demonstrated that the robot can navigate autonomously, but there is still room for improvement. Better results can be achieved with a new movable platform and further tuning of the system. In conclusion, ROS works well as a development tools for robots, and the current system is suitable for further development. RTAB-Maps suitability for use on an industrial installation is still uncertain and requires further testing

Toward Image-Guided Automated Suture Grasping Under Complex Environments: A Learning-Enabled and Optimization-Based Holistic Framework

To realize a higher-level autonomy of surgical knot tying in minimally invasive surgery (MIS), automated suture grasping, which bridges the suture stitching and looping procedures, is an important yet challenging task needs to be achieved. This paper presents a holistic framework with image-guided and automation techniques to robotize this operation even under complex environments. The whole task is initialized by suture segmentation, in which we propose a novel semi-supervised learning architecture featured with a suture-aware loss to pertinently learn its slender information using both annotated and unannotated data. With successful segmentation in stereo-camera, we develop a Sampling-based Sliding Pairing (SSP) algorithm to online optimize the suture's 3D shape. By jointly studying the robotic configuration and the suture's spatial characteristics, a target function is introduced to find the optimal grasping pose of the surgical tool with Remote Center of Motion (RCM) constraints. To compensate for inherent errors and practical uncertainties, a unified grasping strategy with a novel vision-based mechanism is introduced to autonomously accomplish this grasping task. Our framework is extensively evaluated from learning-based segmentation, 3D reconstruction, and image-guided grasping on the da Vinci Research Kit (dVRK) platform, where we achieve high performances and successful rates in perceptions and robotic manipulations. These results prove the feasibility of our approach in automating the suture grasping task, and this work fills the gap between automated surgical stitching and looping, stepping towards a higher-level of task autonomy in surgical knot tying

Development of a Digital Transformation Roadmap (DTR) for the Upstream Oil and Gas Industry

Industrial Engineerin

Democratizing Manufacturing: Bridging the Gap Between Invention and Manufacturing

Entrepreneurs and small firms in the U.S. face significant challenges as they scale up their innovations to volume production. Despite innovative new technologies such as 3D printers, the transition to cost-competitive, large-scale manufacturing can be difficult for domestic firms. To assist small U.S. companies to more effectively ramp up production, MForesight assembled more than 30 experts in manufacturing at a workshop on “Democratizing Manufacturing.” The goal of the workshop was to evaluate the gaps and barriers in technology and education that prevent the competitive design and production of engineered components by small businesses in the U.S. This effort is both timely and important because a large fraction of high-value products are now manufactured outside of the U.S. Companies in Europe and Asia are winning bids to manufacture products designed in the U.S. for a host of reasons, including a willingness on the part of their own governments to consistently invest in manufacturing (both infrastructure and human capital). To successfully compete in the global manufacturing marketplace, the U.S. needs to adopt new strategies for education, technology development, and industrial policy.National Science Foundation, Grant No. 1552534https://deepblue.lib.umich.edu/bitstream/2027.42/145152/1/Democratizing-Manufacturing-Dec2016.pd

Monitoring companion for industrial robotic processes

For system integrators, optimizing complex industrial robotic applications (e.g. robotised welding) is a difficult and time-consuming task. This procedure is rendered tedious and often very hard to achieve when the operator cannot access the robotic system once in operation, perhaps because the installation is far away or because of the operational environment. In these circumstances, as an alternative to physically visiting the installation site, the system integrator may rely on additional nearby sensors to remotely acquire the necessary process information. While it is hard to completely replace this trial and error approach, it is possible to provide a way to gather process information more effectively that can be used in several robotic installations.This thesis investigates the use of a "monitoring robot" in addition to the task robot(s) that belong to the industrial process to be optimized. The monitoring robot can be equipped with several different sensors and can be moved into close proximity of any installed task robot so that it can be used to collect information from that process during and/or after the operation without interfering. The thesis reviews related work in the industry and in the field of teleoperation to identify the most important challenges in remote monitoring and teleoperation. From the background investigation it is clear that two very important issues are: i) the nature of the teleoperator’s interface and; ii) the efficiency of the shared control between the human operator and the monitoring system. In order to investigate these two issues efficiently it was necessary to create experimental scenarios that operate independently from any application scenario, so an abstract problem domain is created. This way the monitoring system's control and interface can be evaluated in a context that presents challenges that are typical of a remote monitoring task but are not application domain specific. Therefore the validity of the proposed approach can be assessed from a generic and, therefore, more powerful and widely applicable perspective. The monitoring framework developed in this thesis is described, both in the shared control design choices based on virtual fixtures (VF) and the implementation in a 3D visualization environment. The monitoring system developed is evaluated with a usability study with user participants. The usability study aims at assessing the system's performance along with its acceptance and ease of use in a static monitoring task, accompanied by user\hyp{}filled TLX questionnaires. Since future work will apply this system in real robotic welding scenarios, this thesis finally reports some preliminary work in such an application

Ohjelmistorobotiikka toimistotyössä: hyödyt, haasteet ja kyvykkyyden kehittäminen

Robotic Process Automation (RPA) is a new technology for automating business processes mainly in the office environment. It is raising much interest currently in organizations as it enables fast automation of processes expanding over several IT systems in an unprecedented way. Processes such as those usually performed in accounting are typically fit for automation with RPA. As a result, company finance functions and centralized shared services organizations are among the early adopters of this technology. This thesis examines the benefits and challenges associated with RPA adoption in organizations. Furthermore, the objective is also to explain what resources and capabilities are required to take advantage of RPA and how these capabilities develop in organizations. This thesis approaches the research questions through a qualitative cross-sectional field study. Data was gathered by way of interviews in five large corporations based in Finland. A total of 10 interviews were conducted with 13 professionals possessing expertise either from finance or robotics. Almost all of the interviewees were in a management position in their respective companies. The theoretical base of this study is drawn from the literature on business process management, as well as from the strategic management research stream on (dynamic) capabilities. The findings suggest largely similar benefits and challenges of RPA adoption as those already suggested in the few earlier studies on RPA. However, this study deepens the analysis and discussion on the benefits and challenges providing insights into their interrelations. From a capabilities perspective, a contribution to earlier research is made by discussing the constructs of the dynamic capabilities framework in an empirical field study setting, grounding the framework more solidly in business practice

Control System Development and Technological Investigation for a Climbing Robot in Offshore platforms

Denne oppgaven går gjennom forskjellige type teknologier for å utvikle en mobil offshore klatre robot

Emerging Technologies

This monograph investigates a multitude of emerging technologies including 3D printing, 5G, blockchain, and many more to assess their potential for use to further humanity’s shared goal of sustainable development. Through case studies detailing how these technologies are already being used at companies worldwide, author Sinan Küfeoğlu explores how emerging technologies can be used to enhance progress toward each of the seventeen United Nations Sustainable Development Goals and to guarantee economic growth even in the face of challenges such as climate change. To assemble this book, the author explored the business models of 650 companies in order to demonstrate how innovations can be converted into value to support sustainable development. To ensure practical application, only technologies currently on the market and in use actual companies were investigated. This volume will be of great use to academics, policymakers, innovators at the forefront of green business, and anyone else who is interested in novel and innovative business models and how they could help to achieve the Sustainable Development Goals. This is an open access book