Human Gait Based Relative Foot Sensing for Personal Navigation

Human gait dynamics were studied to aid the design of a robust personal navigation and tracking system for First Responders traversing a variety of GPS-denied environments. IMU packages comprised of accelerometers, gyroscopes, and magnetometer are positioned on each ankle. Difficulties in eliminating drift over time make inertial systems inaccurate. A novel concept for measuring relative foot distance via a network of RF Phase Modulation sensors is introduced to augment the accuracy of inertial systems. The relative foot sensor should be capable of accurately measuring distances between each node, allowing for the geometric derivation of a drift-free heading and distance. A simulation to design and verify the algorithms was developed for five subjects in different gait modes using gait data from a VICON motion capture system as input. These algorithms were used to predict the distance traveled up to 75 feet, with resulting errors on the order of one percent

Inperlys – independente personal location system

O desenvolvimento de sistemas de localização pedestre com recurso a técnicas de dead reckoning tem mostrado ser uma área em expansão no mundo académico e não só. Existem algumas soluções criadas, no entanto, nem todas as soluções serão facilmente implementadas no mercado, quer seja pelo hardware caro, ou pelo sistema em si, que é desenvolvido tendo em conta um cenário em particular. INPERLYS é um sistema que visa apresentar uma solução de localização pedestre, independentemente do cenário, utilizando recursos que poderão ser facilmente usados. Trata-se de um sistema que utiliza uma técnica de dead reckonig para dar a localização do utilizador. Em cenários outdoor, um receptor GPS fornece a posição do utilizador, fornecendo uma posição absoluta ao sistema. Quando não é possível utilizar o GPS, recorre-se a um sensor MEMS e a uma bússola para se obter posições relativas à última posição válida do GPS. Para interligar todos os sensores foi utilizado o protocolo de comunicações sem fios ZigBee™. A escolha recaiu neste protocolo devido a factores como os seus baixos consumos e o seu baixo custo. Assim o sistema torna-se de uso fácil e confortável para o utilizador, ao contrário de sistemas similares desenvolvidos, que utilizam cabos para interligarem os diferentes componentes do sistema. O sensor MEMS do tipo acelerómetro tem a função de ler a aceleração horizontal, ao nível do pé. Esta aceleração será usada por um algoritmo de reconhecimento do padrão das acelerações para se detectar os passos dados. Após a detecção do passo, a aceleração máxima registada nesse passo é fornecida ao coordenador, para se obter o deslocamento efectuado. Foram efectuados alguns testes para se perceber a eficiência do INPERLYS. Os testes decorreram num percurso plano, efectuados a uma velocidade normal e com passadas normais. Verificou-se que, neste momento, o desempenho do sistema poderá ser melhorado, quer seja a nível de gestão das comunicações, quer a nível do reconhecimento do padrão da aceleração horizontal, essencial para se detectar os passos. No entanto o sistema é capaz de fornecer a posição através do GPS, quando é possível a sua utilização, e é capaz de fornecer a orientação do movimento.The development of pedestrian localization systems using the dead reckoning technique has been growing not only in academic world, but also in the industrial one. There are some solutions that can be found, however, not all of them are easy be implemented due to factors like expensive hardware, or the system architecture which was developed to work in a particular scenario. INPERLYS is a pedestrian location system intended to give a solution for pedestrian location, regardless of the surrounding environment, using resources that can be handled easily. It implements a dead reckoning technique to achieve the user localization. In outdoor environments, it uses the GPS to give the localization, providing an absolute coordinate to the system. When it is not possible establish communication between GPS receiver and satellites, the system uses a MEMS sensor to estimate the distance traveled and a digital compass for orientation. To connect the sensors and the GPS, it is used the wireless ZigBee™ network protocol. This protocol was chosen because it has low power consumption and low cost. The system uses a wireless network because it is comfortable to use with clothes, unlike many similar systems, that use cables to connect all modules of the system. The MEMS accelerometer sensor has the purpose of measuring the horizontal acceleration, at foot level. This acceleration will be used by an algorithm developed to detect steps by recognizing particular patterns in the measured acceleration. When a step is detected, it will be sent to the network coordinator the maximum measured step acceleration, in order to obtain the distance traveled. The system was evaluated in order to understand his reliability. The test consisted in user walking in a flat path, at constant velocity. As result from the test, I realize that the system performance can be improved. The acceleration messages routing management can be enhanced and there are some steps that are not detected. However, the system is able to give the users position, whenever it´s possible to use GPS and it is also able to provide the user´s movement orientation

Robust localization with wearable sensors

Measuring physical movements of humans and understanding human behaviour is useful in a variety of areas and disciplines. Human inertial tracking is a method that can be leveraged for monitoring complex actions that emerge from interactions between human actors and their environment. An accurate estimation of motion trajectories can support new approaches to pedestrian navigation, emergency rescue, athlete management, and medicine. However, tracking with wearable inertial sensors has several problems that need to be overcome, such as the low accuracy of consumer-grade inertial measurement units (IMUs), the error accumulation problem in long-term tracking, and the artefacts generated by movements that are less common. This thesis focusses on measuring human movements with wearable head-mounted sensors to accurately estimate the physical location of a person over time. The research consisted of (i) providing an overview of the current state of research for inertial tracking with wearable sensors, (ii) investigating the performance of new tracking algorithms that combine sensor fusion and data-driven machine learning, (iii) eliminating the effect of random head motion during tracking, (iv) creating robust long-term tracking systems with a Bayesian neural network and sequential Monte Carlo method, and (v) verifying that the system can be applied with changing modes of behaviour, defined as natural transitions from walking to running and vice versa. This research introduces a new system for inertial tracking with head-mounted sensors (which can be placed in, e.g. helmets, caps, or glasses). This technology can be used for long-term positional tracking to explore complex behaviours

User Localization Using Wearable Electromagnetic Tracker and Orientation Sensor

ISWC'06 : IEEE International Symposium on Wearable Computers , Oct 11-14, 2006 , Montreux, SwitzerlandThis paper describes a localization method with wearable electromagnetic sensor and orientation sensor for wearable computer users. Many user localization methods have been investigated to realize location-based services in a wide environment. The localization methods usually employ a hybrid approach in which user's position is estimated by using positioning infrastructures and dead reckoning such as a pedometer. However, the installation cost of infrastructures increases when the area expands, and the error of the pedometer is frequently caused by failures in walking locomotion detection and the difference between ideal and estimated step lengths. If the relative distance is accurately estimated by dead reckoning approach, the installation cost of infrastructures can be reduced. This paper proposes a new localization method that improves the estimation accuracy of step length in dead reckoning approach. The proposed method measures user's orientation and geometrical relationship between user's heel and waist with an orientation sensor and an electromagnetic tracker attached to user's body. When both feet come into contact with the ground, user's position is updated by adding the estimated step length which means the relationship between user's heels and the position estimated in the previous step. The proposed localization method has been experimented using a prototype system to evaluate the accuracy of the proposed method