Localization and motion control (navigation) are two major tasks for a successful mobile robot navigation. The motion controller determines the appropriate action for the robot’s actuator based on its current state in an operating environment. A robot recognizes its environment through some sensors and executes physical actions through actuation mechanisms. However, sensory information is noisy and hence actions generated based on this information may be non-deterministic. Therefore, a mobile robot provides actions to its actuators with a certain degree of uncertainty. Moreover, when no prior knowledge of the environment is available, the problem becomes even more difficult, as the robot has to build a map of its surroundings as it moves to determine the position. Skilled navigation of a differential drive mobile robot (DDMR) requires solving these tasks in conjunction, since they are inter-dependent. Having resolved these tasks, mobile robots can be employed in many contexts in indoor and outdoor environments such as delivering payloads in a dynamic environment, building safety, security, building measurement, research, and driving on highways. This dissertation exploits the use of the emerging Radio Frequency IDentification (RFID) technology for the design and implementation of cost-effective and modular control techniques for navigating a mobile robot in an indoor environment. A successful realization of this process has been addressed with three separate navigation modules. The first module is devoted to the development of an indoor navigation system with a customized RFID reader. This navigation system is mainly pioneered by mounting a multiple antenna RFID reader on the robot and placing the RFID tags in three dimensional workspace, where the tags’ orthogonal position on the ground define the desired positions that the robot is supposed to reach. The robot generates control actions based on the information provided by the RFID reader for it to navigate those pre-defined points. On the contrary, the second and third navigation modules employ custom-made RFID tags (instead of the RFID reader) which are attached at different locations in the navigation environment (on the ceiling of an indoor office, or on posts, for instance). The robot’s controller generates appropriate control actions for it’s actuators based on the information provided by the RFID tags in order to reach target positions or to track pre-defined trajectory in the environment. All three navigation modules were shown to have the ability to guide a mobile robot in a highly reverberant environment with variant degrees of accuracy.

Research report submitted to the School of Economic and Business Sciences, Faculty of Commerce, Law and Management, University of the Witwatersrand, 2013. / In recent years, Radio Frequency Identification (RFID) Technology has transformed from being unknown to mainstream applications that help facilitate the managing of manufactured goods and materials. Its information storage capacity as well as its ability to transfer information through contactless means without line-of-sight translates to significant advantages to deliver various benefits for retailers and their clients in the retail settings. However, up until now RFID technology has gained very little momentum and the status of adoption particularly of retail organisations in South Africa is unknown. To fill this research gap, an exploratory study that draws on the Technology-Organisation-Environment (TOE) framework was employed to provide a deeper understanding of South African retailers’ perceptions of RFID adoption. Five interviewees representing their respective organisations participated in the study. The findings suggested that the adoption level is very low and only one organisation from the sample used had done a pilot project. The results also indicated that cost, standardisation and government support influenced the adoption of the technology. Complexity and technology competence were not considered to have any influence in the adoption of the technology. Competitive pressure was not deemed influential if the technology was not embedded in the whole supply chain, a somewhat surprising result. There were no anticipated impacts on the employees if this technology was implemented. Methodological and practical implications are also discussed.

Localization and motion control (navigation) are two major tasks for a successful mobile robot navigation. The motion controller determines the appropriate action for the robot’s actuator based on its current state in an operating environment. A robot recognizes its environment through some sensors and executes physical actions through actuation mechanisms. However, sensory information is noisy and hence actions generated based on this information may be non-deterministic. Therefore, a mobile robot provides actions to its actuators with a certain degree of uncertainty. Moreover, when no prior knowledge of the environment is available, the problem becomes even more difficult, as the robot has to build a map of its surroundings as it moves to determine the position. Skilled navigation of a differential drive mobile robot (DDMR) requires solving these tasks in conjunction, since they are inter-dependent. Having resolved these tasks, mobile robots can be employed in many contexts in indoor and outdoor environments such as delivering payloads in a dynamic environment, building safety, security, building measurement, research, and driving on highways. This dissertation exploits the use of the emerging Radio Frequency IDentification (RFID) technology for the design and implementation of cost-effective and modular control techniques for navigating a mobile robot in an indoor environment. A successful realization of this process has been addressed with three separate navigation modules. The first module is devoted to the development of an indoor navigation system with a customized RFID reader. This navigation system is mainly pioneered by mounting a multiple antenna RFID reader on the robot and placing the RFID tags in three dimensional workspace, where the tags’ orthogonal position on the ground define the desired positions that the robot is supposed to reach. The robot generates control actions based on the information provided by the RFID reader for it to navigate those pre-defined points. On the contrary, the second and third navigation modules employ custom-made RFID tags (instead of the RFID reader) which are attached at different locations in the navigation environment (on the ceiling of an indoor office, or on posts, for instance). The robot’s controller generates appropriate control actions for it’s actuators based on the information provided by the RFID tags in order to reach target positions or to track pre-defined trajectory in the environment. All three navigation modules were shown to have the ability to guide a mobile robot in a highly reverberant environment with variant degrees of accuracy.

Localization and motion control (navigation) are two major tasks for a successful mobile robot navigation. The motion controller determines the appropriate action for the robot’s actuator based on its current state in an operating environment. A robot recognizes its environment through some sensors and executes physical actions through actuation mechanisms. However, sensory information is noisy and hence actions generated based on this information may be non-deterministic. Therefore, a mobile robot provides actions to its actuators with a certain degree of uncertainty. Moreover, when no prior knowledge of the environment is available, the problem becomes even more difficult, as the robot has to build a map of its surroundings as it moves to determine the position. Skilled navigation of a differential drive mobile robot (DDMR) requires solving these tasks in conjunction, since they are inter-dependent. Having resolved these tasks, mobile robots can be employed in many contexts in indoor and outdoor environments such as delivering payloads in a dynamic environment, building safety, security, building measurement, research, and driving on highways. This dissertation exploits the use of the emerging Radio Frequency IDentification (RFID) technology for the design and implementation of cost-effective and modular control techniques for navigating a mobile robot in an indoor environment. A successful realization of this process has been addressed with three separate navigation modules. The first module is devoted to the development of an indoor navigation system with a customized RFID reader. This navigation system is mainly pioneered by mounting a multiple antenna RFID reader on the robot and placing the RFID tags in three dimensional workspace, where the tags’ orthogonal position on the ground define the desired positions that the robot is supposed to reach. The robot generates control actions based on the information provided by the RFID reader for it to navigate those pre-defined points. On the contrary, the second and third navigation modules employ custom-made RFID tags (instead of the RFID reader) which are attached at different locations in the navigation environment (on the ceiling of an indoor office, or on posts, for instance). The robot’s controller generates appropriate control actions for it’s actuators based on the information provided by the RFID tags in order to reach target positions or to track pre-defined trajectory in the environment. All three navigation modules were shown to have the ability to guide a mobile robot in a highly reverberant environment with variant degrees of accuracy.

Radio frequency identification (RFID) technology allows for the scanning of RFID-tagged objects and individuals without line-of-sight requirements. Healthcare organizations use RFID to ensure the health and safety of patients and medical personnel and to uncover inefficiencies in operations. The successful implementation of a system incorporating RFID technologies requires acceptance and use of the technology. Nurses are a group of employees who must use RFID in hospitals throughout the United States. However, due to their being tracked by RFID technology, some of these nurses feel like "big brother" is watching them. This predictive study used a theoretical model that assessed the effect of five independent variables, namely, privacy concerns, attitudes, subjective norms, controllability, and self-efficacy, on a dependent variable, nurses' behavioral intention to use RFID. A total of 106 U.S. registered nurses answered a Web-based questionnaire containing previously validated and adapted questions that were answered through a five-point Likert scale. Two statistical methods, linear regression and multiple linear regression, were used to investigate the survey results. The results of the linear regression analysis showed that privacy concerns, attitudes, subjective norms, and self-efficacy were each a significant predictor of nurses' behavioral intention to use RFID. The results of the multiple linear regression analysis showed that all the constructs together accounted for 60% of the variance in nurses' intention to use RFID. Of the five predictors in the model, attitudes provided the largest unique contribution when the other predictors in the model were held constant. Subject norms also provided a unique contribution. The other predictors in the model (privacy concerns, controllability, and self-efficacy) were not statistically significant and did not provide a significant unique contribution to nurses' behavioral intention to use RFID. The outcomes of this study constitute a significant original contribution to the body of knowledge in the area of information systems by enhancing understanding of the factors affecting RFID acceptance among nurses. The results of this research also provide hospitals and medical centers that require their nurses to use RFID technology with information that they can use to address barriers to their nurses' acceptance and use of RFID technology.

M. Tech. (Department of Process Control and Computer Systems, Faculty of Engineering and Technology), Vaal University of Technology. / Radio Frequency Identification Technology (RFID) technology is increasingly being used in multiple applications due to its low cost and ability to provide a high quality of identification. The cost benefit of RFID system is seen in the reduction in labor required to perform routine tasks such as inventory. With RFID, inventory-related tasks can be done in substantially less time compared to other commonly used auto-identification systems. Recent research has illustrated the application of RFID in multiple application scenarios. RFID can be used for real-time patient identification and monitoring in hospitals, but also for product expiration-date management in retail industries. Some enterprises in South Africa uses a combination of RFID technology and Internet of Things (IoT) to detect misplaced products and to detect low stock levels. Furthermore, RFID is also used for inventory management in libraries as discussed in this dissertation. In this dissertation, a combination of RFID and ZigBee technologies was used to reduce the time spent to perform inventory in libraries. An inventory management system was designed, simulated and built in order to count and locate books inside a library hence improving inventory process time in libraries. The overall results were satisfactory which lead to the achieving of the objectives set in this study.

<p dir="ltr">Asset traceability systems support sustainable value creation. Use case scenarios include the transition from a linear to a circular economy (CE) and legislative initiatives in Europe and North America. Traceability systems are needed to consistently link physical assets with the corresponding digital life cycle data. However, there is a lack of system architectures for consistent asset life cycle traceability. Therefore, the work proposes a traceability system architecture using digital product passports (DPPs) and fingerprint (FP) technology. By providing asset related data, DPPs increase the transparency across value chain partners. The system architecture uses the Asset Administration Shell (AAS) to create interoperable and standardized DPPs. Besides, consistent product identification (ID) and unique (single occurrence) identifiers are a prerequisite for effective traceability systems. Using natural markers to identify assets can enhance consistent asset traceability in sustainable supply chains. When using FP technology, the inherent surface structure of an asset is captured by an imaging system and then compressed into a digital asset fingerprint. Since assets are not artificially marked, the work investigates the use of Bounding Symbols (BSs) to locate an asset’s fingerprint Region of Interest (ROI). Furthermore, four fingerprint creation algorithms are compared and evaluated regarding their feasibility for asset life cycle traceability. The research validates the proposed system architecture in an experimental setup by using aluminum raw castings (medallions) as the investigated asset type. Key findings include the successful identification of 80 medallions with a 100% success rate. The related fingerprint information was stored in a DPP as an AAS submodel.</p>