Development and Validation of Control Moment Gyroscopic Stabilization

Two wheeled vehicles offer many advantages over other configurations such as greater maneuverability, smaller size, and greater efficiency. These advantages come at the sacrifice of stability and safety. The goal of this work is to improve the stability and safety of a two wheeled vehicle by the development of Control Moment Gyroscopic Stabilization. This technology integrated into a vehicle can deliver unparalleled maneuverability and stability for users compared to any vehicle in use today. The goal of my work was to develop and validate the system of gyroscopic stabilization to be implemented into a vehicle. To validate the concept, a MATLAB/Simulink program was created, modeling the behavior and response of an unstable body with gyroscopic stabilization applied. After completing multiple simulations on this model, a physical structure, similar to an inverted pendulum, was constructed and CMG stabilization has been tested on this setup. Gyroscopic stabilization has been validated in this configuration and has led to further study in multiple degree of freedom situations. The implementation of a vehicle which utilizes this technology can generate safer and more maneuverable vehicles for the public, military, and recreational users.Ohio State Center for Automotive ResearchAir Force Research LaboratorySpecial-Ops Transport ChallengeOhio State Control and Intelligent Transportation LaboratoryNo embargoAcademic Major: Mechanical Engineerin

Control Moment Gyroscope Stabilization and Maneuverability of Inherently Unstable Vehicles and Mobile Robots

The control problem of stabilizing an inherently unstable body, such as the inverted pendulum, is a classic control theory problem. Traditionally, the solution to this problem has been approached through methods of dynamic stabilization where the inverted pendulum is placed on a wheeled cart that can travel with one translational degree of freedom. This cart essentially accelerates the pivot of the inverted pendulum to accelerate the pendulum to induce a rotation that counteracts the imbalance in the system. A different approach to stabilizing a static or stationary inverted pendulum makes use of the intriguing phenomena known as gyroscopic precession. Precession and the physics of gyros are governed by conservation of angular momentum. By utilizing this technology in a novel way, groundbreaking progress can be made in the field of autonomous stability of inherently unstable mobile robots and vehicles (e.g. two wheeled vehicles). Gyroscopic effects can be found today in simple devices such as a spinning top or a bicycle’s wheel in motion. Gyros are also found in very complex mechanisms such as those used for satellite attitude and large ship anti-roll systems. Recent gyro studies have shown tremendous promise for providing unparalleled capabilities in stabilization and maneuverability for both on and off-road vehicle applications.Air Force Research LabSpecial Ops Transport ChallengeThe Ohio State University's Center for Automotive ResearchThe Ohio State University's Control and Intelligent Transportation LaboratoryNo embargoAcademic Major: Mechanical Engineerin

Development of a self balanced robot and its controller

Two wheeled balancing robots are based on inverted pendulum configuration which relies upon dynamic balancing systems for balancing and maneuvering. This project is based on the development of a self-balanced two wheeled robot which has a configuration similar to a bicycle. These robot bases provide exceptional robustness and capability due to their smaller size and power requirements. Outcome of research in this field had led to the birth of robots such as Segway, Murata boy etc. Such robots find their applications in surveillance & transportation purpose. Here, in particular, the focus is on the electro-mechanical mechanisms & control algorithms required to enable the robot to perceive and act in real time for a dynamically changing world. Using an Ultrasonic sensor and an accelerometer we get the information about the tilt of the robot from its equilibrium position. Balancing was done using a servo motor, a DC motor and a control momnt gyroscope. While these techniques are applicable to many robot applications, the construction of sensors, filters and actuator system is a learning experience

Design and Development of a Self-Balancing Bicycle Using Control Moment Gyro

Master'sMASTER OF ENGINEERIN

Gyrubot: nonanthropomorphic stabilization for a biped

International audienceDemands on leg degrees of freedom and control precision for bipedal robotics are steadily increasing, especially for the tasks involving walking on a rough terrain. In this paper we present an alternative, as well as a working proof-of-concept. Meet gyrubot: a 5-link almost planar bipedal robot with a torso complemented by a nonanthropomorphic stabilization system, capable of blindly walking through uneven areas. Despite being almost planar, the robot does not need any support in the frontal plane! This paper describes the mechanical design and the architecture of the controllers. We also provide the experimental evidence of the ability of gyrubot to navigate across non-flat terrains

Magnetically Geared Electrical Machines

Considerable research efforts are being carried out worldwide to develop technologies which meet the increasing demand for the efficient utilisation of energy resources. Modern applications, such as renewable energy and electrical vehicles, place a premium on electro-mechanical energy conversion in a power dense and high efficiency manner. Magnetic gears (MG) and magnetically geared machines, offer an attractive alternative to existing systems which may favour the combination of a high speed electrical machine with a mechanical gearbox. This has led to the opportunity to use Pseudo Direct Drives (PDDs) and MGs to be developed for use on an industrial scale. Therefore, in this thesis techniques for facilitating the manufacture and robustness of PDDs are presented, for both radial and axial field topologies. This includes use of alternative windings and soft magnetic composites. PDDs and MGs has so far mainly been developed in the radial topology and little attention has been given to axial topologies. The pole piece (PP) rotor required for MG operation, represents the main difference between PDD/MG and a conventional electrical machine. As such the PP shape and supporting structures have been investigated both in terms of electromagnetic and mechanical performance. Furthermore, detailed electromagnetic and thermal design and analysis of an axial field PDD (AFPDD) with improved robustness was undertaken, and a prototype was manufactured to demonstrate the operation of the AFPDD and validate the predictions

Learning object behaviour models

The human visual system is capable of interpreting a remarkable variety of often subtle, learnt, characteristic behaviours. For instance we can determine the gender of a distant walking figure from their gait, interpret a facial expression as that of surprise, or identify suspicious behaviour in the movements of an individual within a car-park. Machine vision systems wishing to exploit such behavioural knowledge have been limited by the inaccuracies inherent in hand-crafted models and the absence of a unified framework for the perception of powerful behaviour models. The research described in this thesis attempts to address these limitations, using a statistical modelling approach to provide a framework in which detailed behavioural knowledge is acquired from the observation of long image sequences. The core of the behaviour modelling framework is an optimised sample-set representation of the probability density in a behaviour space defined by a novel temporal pattern formation strategy. This representation of behaviour is both concise and accurate and facilitates the recognition of actions or events and the assessment of behaviour typicality. The inclusion of generative capabilities is achieved via the addition of a learnt stochastic process model, thus facilitating the generation of predictions and realistic sample behaviours. Experimental results demonstrate the acquisition of behaviour models and suggest a variety of possible applications, including automated visual surveillance, object tracking, gesture recognition, and the generation of realistic object behaviours within animations, virtual worlds, and computer generated film sequences. The utility of the behaviour modelling framework is further extended through the modelling of object interaction. Two separate approaches are presented, and a technique is developed which, using learnt models of joint behaviour together with a stochastic tracking algorithm, can be used to equip a virtual object with the ability to interact in a natural way. Experimental results demonstrate the simulation of a plausible virtual partner during interaction between a user and the machine

e-mission: an open source, extensible platform for human mobility systems

Transportation is the single largest source of carbon emissions in the US. Decarbonizing it is challenging because it depends on individual behaviors, which in turn, depend on local land use planning. The interdisciplinary field of Computational Mobility, focusing on collecting, analysing and influencing human travel behavior, can frame solutions to this challenge.Innovation flows in interdisciplinary fields are bi-directional. The flow to the domain is focused on building a strong foundation for methodological improvements. As the improvements are deployed, they result in use-inspired computational research. This temporal dependency results in our initial focus on the modularity, accuracy and reproducibility of e-mission, an extensible platform for instrumenting human mobility. This open source platform has a modular architecture that supports power efficient duty cycling using virtual sensors, a read-only data model and a pipeline with novel algorithm adaptations for smartphone sensing.We also perform the first empirical evaluations of smartphone-based platforms in this domain. The architectural evaluation is based on three real world deployments: a classic travel diary, a crowdsourcing initiative, and a behavioral study. The accuracy evaluation is based on an novel procedure that uses artificial trips and multiple parallel phones to mitigate concerns over privacy, context sensitive power consumption and inherent sensing error. Data collected from three artifical timelines was used to evaluate the trajectory, segmentation and classification accuracies vs. power for various configurations.On computational side, challenges derived from the deployments can contribute to ongoing CS research in privacy, trustworthiness, incentivization and decision making. On the mobility side, this enables methodological innovations such as Agile Urban Planning for prototyping infrastructure changes