On the Velocity and Acceleration Estimation from Discrete Time-Position Sensors

In this work is addressed the topic of estimation of velocity and acceleration from digital position data. It is presented a review of several classic methods and implemented with real position data from a low cost digital sensor of a hydraulic linear actuator. The results are analyzed and compared. It is shown that static methods have a limited bandwidth application, and that the performance of some methods may be enhanced by adapting its parameters according to the current state.

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

Electrical characteristics of eddy current position sensor

In the thesis the principle of work of eddy current position sensors and the main cautions that must be taken into account while sensor design process are explained. A way of automated eddy current position sensor electrical characteristics measurement is suggested. A prototype of the eddy current position sensor and its electrical characteristics are investigated. The results obtained by means of the automated measuring system are explained.

Position sensorless electrically excited synchronous motor drive for industrial use based on direct flux linkage and torque control

Synchronous machines with an AC converter are used mainly in large drives, for example in ship propulsion drives as well as in rolling mill drives in steel industry. These motors are used because of their high efficiency, high overload capacity and good performance in the field weakening area. Present day drives for electrically excited synchronous motors are equipped with position sensors. Most drives for electrically excited synchronous motors will be equipped with position sensors also in future. This kind of drives with good dynamics are mainly used in metal industry. Drives without a position sensor can be used e.g. in ship propulsion and in large pump and blower drives. Nowadays, these drives are equipped with a position sensor, too. The tendency is to avoid a position sensor if possible, since a sensor reduces the reliability of the drive and increases costs (latter is not very significant for large drives). A new control technique for a synchronous motor drive is a combination of the Direct Flux Linkage Control (DFLC) based on a voltage model and a supervising method (e.g. current model). This combination is called Direct Torque Control method (DTC). In the case of the position sensorless drive, the DTC can be implemented by using other supervising methods that keep the stator flux linkage origin centered. In this thesis, a method for the observation of the drift of the real stator flux linkage in the DTC drive is introduced. It is also shown how this method can be used as a supervising method that keeps the stator flux linkage origin centered in the case of the DTC. In the position sensorless case, a synchronous motor can be started up with the DTC control, when a method for the determination of the initial rotor position presented in this thesis is used. The load characteristics of such a drive are not very good at low rotational speeds. Furthermore, continuous operation at a zero speed and at a low rotational speed is not possible, which is partly due to the problems related to the flux linkage estimate. For operation in a low speed area, a stator current control method based on the DFLC modulator (DMCQ is presented. With the DMCC, it is possible to start up and operate a synchronous motor at a zero speed and at low rotational speeds in general. The DMCC is necessary in situations where high torque (e.g. nominal torque) is required at the starting moment, or if the motor runs several seconds at a zero speed or at a low speed range (up to 2 Hz). The behaviour of the described methods is shown with test results. The test results are presented for the direct flux linkage and torque controlled test drive system with a 14.5 kVA, four pole salient pole synchronous motor with a damper winding and electric excitation. The static accuracy of the drive is verified by measuring the torque in a static load operation, and the dynamics of the drive is proven in load transient tests. The performance of the drive concept presented in this work is sufficient e.g. for ship propulsion and for large pump drives. Furthermore, the developed methods are almost independent of the machine parameters.

Combining WLAN fingerprint-based localization with sensor data for indoor navigation using mobile devices

This project proposes an approach for supporting Indoor Navigation Systems using Pedestrian Dead Reckoning-based methods and by analyzing motion sensor data available in most modern smartphones. Processes suggested in this investigation are able to calculate the distance traveled by a user while he or she is walking. WLAN fingerprint- based navigation systems benefit from the processes followed in this research and results achieved to reduce its workload and improve its positioning estimations.

Desenvolvimento de Uma Órtese Ativa Para os Membros Inferiores Com Sistema Eletrônico Embarcado

This work presents the development of a prototype of an intelligent active orthosis for lower limbs whit an electronic embedded system. The proposed orthosis is an orthopedical device with the main objective of providing walking capacity to people with partial or total loss of lower limbs movements. In order to design the kinematics, dynamics and the mechanical characteristics of the prototype, the biomechanics of the human body was analized. The orthosis was projected to reproduce some of the movements of the human gait as walking in straight forward, sit down, get up, arise and go down steps. The joints of the orthosis are controlled by DC motors equipped with mechanical reductions, whose purpose is to reduce rotational speed and increase the torque, thus generating smooth movements. The electronic embedded system is composed of two motor controller boards with two channels that communicate with a embedded PC, position sensors and limit switches. The gait movements of the orthosis will be controlled by high level commands from a human-machine interface. The embedded electronic system interprets the high level commands, generates the angular references for the joints of the orthosis, controls and drives the actuators in order to execute the desired movements of the user

Controle inteligente aplicado a uma mesa de coordenadas de dois graus de liberdade

This work presents the design and construction of an X-Y table of two degrees of freedom, as well as the development of a fuzzy system for its position and trajectory control. The table is composed of two bases that move perpendicularly to each other in the horizontal plane, and are driven by two DC motors. Base position is detected by position sensors attached to the motor axes. A data acquisition board performs the interface between a laptop and the plant. The fuzzy system algorithm was implemented in LabVIEW® programming environment that processes the sensors signals and determines the control variables values that drive the motors. Experimental results using position reference signals (step type signal) and straight and circular paths reference signals are presented to demonstrate the dynamic behavior of fuzzy system

Aligning the CMS muon chambers with the muon alignment system during an extended cosmic ray run

The alignment system for the muon spectrometer of the CMS detector comprises three independent subsystems of optical and analog position sensors. It aligns muon chambers with respect to each other and to the central silicon tracker. System commissioning at full magnetic field began in 2008 during an extended cosmic ray run. The system succeeded in tracking muon detector movements of up to 18 mm and rotations of several milliradians under magnetic forces. Depending on coordinate and subsystem, the system achieved chamber alignment precisions of 140-350 μm and 30-200 μrad, close to the precision requirements of the experiment. Systematic errors on absolute positions are estimated to be 340-590 μm based on comparisons with independent photogrammetry measurements. © 2010 IOP Publishing Ltd and SISSA.

Hastes instrumentadas com controle automatizado do escarificador atuando em profundidades variáveis

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Modelling and Control of Stepper Motors for High Accuracy Positioning Systems Used in Radioactive Environments

Hybrid Stepper Motors are widely used in open-loop position applications. They are the choice of actuation for the collimators in the Large Hadron Collider, the largest particle accelerator at CERN. In this case the positioning requirements and the highly radioactive operating environment are unique. The latter forces both the use of long cables to connect the motors to the drives which act as transmission lines and also prevents the use of standard position sensors. However, reliable and precise operation of the collimators is critical for the machine, requiring the prevention of step loss in the motors and maintenance to be foreseen in case of mechanical degradation. In order to make the above possible, an approach is proposed for the application of an Extended Kalman Filter to a sensorless stepper motor drive, when the motor is separated from its drive by long cables. When the long cables and high frequency pulse width modulated control voltage signals are used together, the electrical signals difer greatly between the motor and drive-side of the cable. Since in the considered case only drive-side data is available, it is therefore necessary to estimate the motor-side signals. Modelling the entire cable and motor system in an Extended Kalman Filter is too computationally intensive for standard embedded real-time platforms. It is, in consequence, proposed to divide the problem into an Extended Kalman Filter, based only on the motor model, and separated motor-side signal estimators, the combination of which is less demanding computationally. The efectiveness of this approach is shown in simulation. Then its validity is experimentally demonstrated via implementation in a DSP based drive. A testbench to test its performance when driving an axis of a Large Hadron Collider collimator is presented along with the results achieved. It is shown that the proposed method is capable of achieving position and load torque estimates which allow step loss to be detected and mechanical degradation to be evaluated without the need for physical sensors. These estimation algorithms often require a precise model of the motor, but the standard electrical model used for hybrid stepper motors is limited when currents, which are high enough to produce saturation of the magnetic circuit, are present. New model extensions are proposed in order to have a more precise model of the motor independently of the current level, whilst maintaining a low computational cost. It is shown that a significant improvement in the model It is achieved with these extensions, and their computational performance is compared to study the cost of model improvement versus computation cost. The applicability of the proposed model extensions is demonstrated via their use in an Extended Kalman Filter running in real-time for closed-loop current control and mechanical state estimation. An additional problem arises from the use of stepper motors. The mechanics of the collimators can wear due to the abrupt motion and torque profiles that are applied by them when used in the standard way, i.e. stepping in open-loop. Closed-loop position control, more specifically Field Oriented Control, would allow smoother profiles, more respectful to the mechanics, to be applied but requires position feedback. As mentioned already, the use of sensors in radioactive environments is very limited for reliability reasons. Sensorless control is a known option but when the speed is very low or zero, as is the case most of the time for the motors used in the LHC collimator, the loss of observability prevents its use. In order to allow the use of position sensors without reducing the long term reliability of the whole system, the possibility to switch from closed to open loop is proposed and validated, allowing the use of closed-loop control when the position sensors function correctly and open-loop when there is a sensor failure. A different approach to deal with the switched drive working with long cables is also presented. Switched mode stepper motor drives tend to have poor performance or even fail completely when the motor is fed through a long cable due to the high oscillations in the drive-side current. The design of a stepper motor output fillter which solves this problem is thus proposed. A two stage filter, one devoted to dealing with the diferential mode and the other with the common mode, is designed and validated experimentally. With this ?lter the drive performance is greatly improved, achieving a positioning repeatability even better than with the drive working without a long cable, the radiated emissions are reduced and the overvoltages at the motor terminals are eliminated.

Sensors on mobile devices for AAL

Com o envelhecimento da população, as preocupações com a garantia do seu bem-estar aumentam criando a necessidade de desenvolver ferramentas que permitam monitorizar em permanência este sector da população. A utilização de smartphones pelos mais velhos pode ser crucial no seu bem-estar e na sua autonomia contribuindo para a recolha de informação importante já que estes estão muitas vezes equipados com sensores que podem dar indicações preciosas ao cuidador sobre o estado atual do paciente. Os sensores podem fornecer dados sobre a atividade física do paciente, bem como detetar quedas ou calcular a sua posição, com a ajuda do acelerómetro, do giroscópio e do sensor de campo magnético. No entanto, funcionalidades como essas requerem, obrigatoriamente, uma frequência de amostragem mínima por parte dos sensores que permita a implementação de algoritmos, que determinarão esses parâmetros da forma mais exata possível. Dado que nem sempre os pacientes se fazem acompanhar do seu smartphone quando estão na sua residência, a criação de ambientes de AAL (Ambient Assisted Living) com recurso a dispositivos externos que podem ser “vestidos” pelos pacientes pode também ser uma solução adequada. Estes contêm normalmente os mesmos sensores que os smartphones e comunicam com estes através de tecnologias sem fios, como é o caso do Bluetooth Low Energy. Neste trabalho, avaliou-se a possibilidade de alteração da frequência dos sensores em diferentes sistemas operativos, tendo sido efectuadas modificações nas instalações por defeito de alguns sistemas operativos abertos. Com o objectivo de permitir a criação de uma solução de AAL com recurso a um dispositivo externo implementaram-se serviços e perfis num dispositivo externo, o SensorTag.

2D position system for a mobile robot in unstructured environments

Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

Probabilistic position and orientation estimation of rigid objects using an RGB-D sensor

The recent emergence of low-cost RGB-D sensors has brought new opportunities for robotics by providing affordable devices that can provide synchronized images with both color and depth information. In this thesis, recent work on pose estimation utilizing RGBD sensors is reviewed. Also, a pose recognition system for rigid objects using RGB-D data is implemented. The implementation uses half-edge primitives extracted from the RGB-D images for pose estimation. The system is based on the probabilistic object representation framework by Detry et al., which utilizes Nonparametric Belief Propagation for pose inference. Experiments are performed on household objects to evaluate the performance and robustness of the system.

Map matching by using inertial sensors: literature review

This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.