Processing GPS carrier-phase measurements can provide high positioning accuracy for several navigation applications. However, if not detected, cycle slips in the measured phase can strongly deteriorate the positioning accuracy. Cycle slips frequently occur in areas surrounded by trees, buildings, and other obstacles. The dynamics experienced by the GPS receiver in kinematic mode of navigation also increases the possibility of cycle slips. Detection and correction of these cycle-slips is essential for reliable navigation. One way of detecting and correcting for cycle slips is to use another system to be integrated with GPS. Inertial Navigation Systems (INS), using three-axis accelerometers and three-axis gyroscopes, is integrated with GPS to provide more reliable navigation solution. Moreover, INS was utilized in the past for GPS cycle slip detection and correction. For low cost applications, Micro-Electro-Mechanical-Systems (MEMS) accelerometers and gyroscopes are used inside INS. For land navigation, reduced inertial sensor system (RISS) utilizing two accelerometers, one gyroscope, and the vehicle odometer was suggested. MEMS-based RISS has the advantage of using less number of MEMS-based gyroscopes and accelerometers thus reducing the overall cost and avoiding the complex error characteristics associated with MEMS sensors. In this thesis, we investigate the use of MEMS – based RISS to aid GPS and detect and correct for cycle slips. The Kalman filter was employed in centralized fashion to integrate the measurements from both GPS and RISS. This thesis research also offers a new threshold selection criterion resulting in a more robust cycle slip detection and correction. The proposed method was tested in different scenarios of road tests in land vehicle. Results show accuracy iii improvement over the conventional double differenced pseudoranges-based integrated system. Moreover, the adaptive selection criterion of the detection threshold proposed in this thesis improves the detection rate, especially in the case of small-sized cycle slips. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2013-05-06 18:11:57.076

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Hand impairments have a significant impact on quality of life and career performance. This effect is specially bold in the agricultural community, since farming activities involve continuously carrying and lifting heavy objects. Assistive robotic technologies hold considerable promise in alleviating such impairment issues. However, no portable assistive device is developed for farming applications, which requires additional considerations to ensure functionality of the device and its practicality in agricultural settings. In this work, a bi-layered structure for a robotic glove is presented, which consists of a passive extension and an active flexion layers. The former is responsible for extending the fingers, using a set of elastic bands. The flexion layer, which helps with flexing the fingers and grasping of objects, is a lightweight, self-contained, portable, cable-driven, and single-actuated robotic glove. The cable configuration is inspired from the human hand flexor tendons. Due to uncertainties associated with the fabric's flexibility and potential slippage between the cable and the glove, the designed mechanisms and sensory and control systems are initially implemented on a robotic hand. The rigid structure of the robotic hand provides a suitable proving ground for the design and control ideas. The novel power transmission system design enables the active layer to perform adaptive grasp of objects with unknown shapes, sizes, and material textures. The sensory system includes a bend sensor to detect the wearer's intention to perform grasp or release actions. Additionally, a PVDF-based sensor is developed for slip-detection, which is used as feedback to prevent further slipping of the grasped objects. Overall, the active flexion layer weighs 265 gr and can provide the maximum grasping force of 122 N, which is a noticeable improvement in comparison to the literature. / Doctor of Philosophy / Hand impairments have a significant impact on quality of life and career performance. This effect is specially bold in the agricultural community, since farming activities involve continuously carrying and lifting heavy objects. Assistive robotic technologies hold considerable promise in alleviating such impairment issues. However, no portable assistive device is developed for farming applications, which requires additional considerations to ensure functionality of the device and its practicality in agricultural settings. In this work, a bi-layered structure for a robotic glove is presented, which helps with grasping objects. The first layer is responsible for extending the fingers, using a set of elastic bands. The second layer, which helps with flexing the fingers, is a lightweight, self-contained, and portable robotic glove. A novel cable-driven power transmission system is designed to perform reliable grasps using only one actuator. The power transmission system design enables the robotic glove to grasp objects with unknown shapes, sizes, and material textures. The intention of the wearer for performing a grasp or releasing an object is detected using a bend sensor. Additionally, a vibration sensor is utilized for detecting the slip of the grasped object and preventing further slipping and dropping the object. The functionality of the developed robotic gloved is evaluated through experiments, where different geometry and weight of objects are grasped.

This thesis explores the field of hand exoskeleton robotic systems with slip detection and its applications. It presents the design and control of the intelligent sensing and force- feedback exoskeleton robotic (iSAFER) glove to create a system capable of intelligent object grasping initiated by detection of the user’s intentions through motion amplification. Using a combination of sensory feedback streams from the glove, the system has the ability to identify and prevent object slippage, as well as adapting grip geometry to the object properties. The slip detection algorithm provides updated inputs to the force controller to prevent an object from being dropped, while only requiring minimal input from a user who may have varying degrees of functionality in their injured hand. This thesis proposes the use of a high dynamic range, low cost conductive elastomer sensor coupled with a negative force derivative trigger that can be leveraged in order to create a controller that can intelligently respond to slip conditions through state machine architecture, and improve the grasping robustness of the exoskeleton. The mechanical and electrical improvements to the previous design, the sensing and force- feedback exoskeleton robotic (SAFER) glove, are described while details of the controller design and the proposed assistive and rehabilitative applications are explained. Experimental results confirming the validity of the proposed system are also presented. In closing, this thesis concludes with topics for future exploration. / Master of Science / Exoskeletons are robotic systems that have rigid external covering, such as links, joints, and/or soft artificial tendons or muscles, for the desired body part to provide support and/or protection. These are typically used to enhance power and strength, provide rehabilitation and assistance, and teleoperate other robots from a distance. While the US Army developed exoskeletons for strengthening purposes, another potential purpose of exoskeletons, which is serving medical needs, such as rehabilitation, attracted a lot of attention. Among numerous illnesses and injuries that may lead to impaired hand functionality, the U.S. Department of Health and Human Services estimated that approximately 470,000 people survive strokes every year in the United States and require continuous rehabilitation to recover their motor functions. Though medical professionals believe that the intensity and duration of rehabilitation is the key for maximizing the rate of recovery, it is often limited due to many reasons, such as cost or difficulty in attending rehabilitation sessions. To augment the availability and quality of rehabilitation, the study of exoskeletons has earned popularity. Beyond the capability of providing simple movements, such as passive rehabilitation, many scientists researched to provide active rehabilitation, which involves active participation from the patients. Furthermore, detecting the patient’s intention to activate the rehabilitation glove became a topic of interest, and many types of sensors were utilized in research. This thesis explores the design and control of the intelligent sensing and force- feedback exoskeleton robotic (iSAFER) glove, which detects the user’s intentions to activate the system through motion amplification. The iSAFER glove performs soft initial grasp until the fingers touch an object. After the object is gently grabbed and lifted, the grasp is autonomously adjusted through slip detection until there is no more slip. To facilitate this idea, a low cost force sensor was created and leveraged to improve the grasping control of the exoskeleton. The mechanical and electrical improvements to the previous design, the sensing and force-feedback exoskeleton robotic (SAFER) glove, are described while details of the controller design and the proposed assistive and rehabilitative applications are explained. Experimental results confirming the validity of the proposed system are also presented. In closing, this thesis concludes with topics for future exploration.

Husqvarna AB is one of the leading producers of outdoor products such as autonomous lawn mowers. One important feature of these products is the ability toquickly respond to environmental factors such as slippy areas. A reliable slip detector is needed for this mission and many different technologies exists for detectingslip events. A common technique is to check the wheel motor current, which clearlydeviates when the lawn mower is subjected to slipping. The on-board sensors opensup for an alternative solution which utilizes the loop sensors as the main slip detector. This thesis covers the construction of a slip detection prototype which is basedon the loop sensors. In the end, Husqvarna AB was provided with a new alternativesolution, which was successfully compared to the exiting solution. It proved to bea reliable slip detector for manually induced slipping indoors, outdoor performancewere not investigated. Ultimately, the implemented prototype outperformed the existing solution in the intended environment of indoor testing.

abstract: Effective tactile sensing in prosthetic and robotic hands is crucial for improving the functionality of such hands and enhancing the user's experience. Thus, improving the range of tactile sensing capabilities is essential for developing versatile artificial hands. Multimodal tactile sensors called BioTacs, which include a hydrophone and a force electrode array, were used to understand how grip force, contact angle, object texture, and slip direction may be encoded in the sensor data. Findings show that slip induced under conditions of high contact angles and grip forces resulted in significant changes in both AC and DC pressure magnitude and rate of change in pressure. Slip induced under conditions of low contact angles and grip forces resulted in significant changes in the rate of change in electrode impedance. Slip in the distal direction of a precision grip caused significant changes in pressure magnitude and rate of change in pressure, while slip in the radial direction of the wrist caused significant changes in the rate of change in electrode impedance. A strong relationship was established between slip direction and the rate of change in ratios of electrode impedance for radial and ulnar slip relative to the wrist. Consequently, establishing multiple thresholds or establishing a multivariate model may be a useful method for detecting and characterizing slip. Detecting slip for low contact angles could be done by monitoring electrode data, while detecting slip for high contact angles could be done by monitoring pressure data. Predicting slip in the distal direction could be done by monitoring pressure data, while predicting slip in the radial and ulnar directions could be done by monitoring electrode data. / Dissertation/Thesis / M.S. Bioengineering 2012

En övergång till bilar utrustade med avancerade automatiska säkerhetssystem (ADAS) och även utvecklingen mot självkörande fordon innebär ökad trafik på den lokala databussen. Det finns således ett behov av att både minska den faktiska mängden data som överförs, samtidigt som värdet på datat ökas. Data aggregation tillämpas i dagsläget inom områden såsom trådlösasensornätverk och mindre mobila robotar (WMR’s) och skulle kunna vara en del av en lösning. Denna rapport avser undersöka aggregation av sensordata i ett tidskänsligt system. För ett användarfall gällande halka under konvojkörning testas en aggregationsstrategi genom implementation på en fysisk demonstrator. Demonstratorn består av ett autonomt fordon i mindre skala som befinner sig i en konvoj med ett annat identiskt fordon. Resultaten pekar mot att ett viktat medelvärde, som i realtid anpassar sin viktning baserat på specifika sensorers koherens, med fördel kan användas för att estimera fordonshastighet baserat på individuella hjuls sensordata. Därefter kan en slip ratio beräknas, vilket avgör om fordonet befinner sig i ett tillstånd av halka eller ej. Begränsningar för den undersökta strategin inkluderar antalet icke-halkande hjul som behövs för tillförlitliga resultat. Simulerade resultat antyder att extra hastighetsreferenser behövs för tillförlitliga resultat. Relaterat till användarfallet konvojkörning föreslås att andra fordon används som hastighetsreferens. Detta skulle innebära en ökad precision för estimeringen av fordonshastigheten samt utgöra en intressant sammanslagning av områdena samarbetande cyberfysiska system (CO-CPS) och dataaggregation. / With an impending shift to more advanced safety systems and driver assistance (ADAS) in the vehicles we drive, and also increased autonomousity, comes increased amounts of data on the internal vehicle data bus. There is a need to lessen the amount of data and at the same time increase its value. Data aggregation, often applied in the field of environmental sensing or small mobile robots (WMR’s), could be a partial solution. This thesis choses to investigate an aggregation strategy applied to a use case regarding slip detection in a vehicle convoy. The approach was implemented in a physical demonstrator in the shape of a small autonomousvehicle convoy to produce quantitative data. The results imply that a weighted adaptive average can be used for vehicle velocity estimation based on the input of four individual wheel velocities. There after a slip ratio can be calculated which is used to decide if slip exists or not. Limitations of the proposed approach is however the number of velocity references that is needed since the results currently apply to one-wheel slipon a four-wheel vehicle. A proposed future direction related to the use case of convoy driving could be to include platooning vehicles as extra velocity references for the vehicles in the convoy, thus increasing the accuracy of the slip detection and merging the areas of CO-CPS and data aggregation.