Drone-Mounted Low-Frequency pMUTS for > 6-Meter Rangefinder in Air

This paper reports a low-frequency piezoelectric micromachined ultrasonic transducer (pMUT) with a small attenuation coefficient to realize the long-distance range finding applications in air. Pulse-detection measurements of one pair of pMUT devices show a >6-meter traveling distance in air under a 37.32 kHz driving frequency. As an example, two pMUT chips are mounted on two drones as the transceiver and receiver, respectively. Measurements of the separation distance are conducted based on the time-of-flight (ToF) principle with up to 32 fps (frames per second) for real-time detections. This demo of drone-mounted pMUT system illustrates the advantages of pMUT in terms of compactness and low power consumption for applications in drones including obstacle avoidance, inter collision prevention, aerial coordination, and acoustic-based vision

Ultrasound Indoor Positioning System Based on a Low-Power Wireless Sensor Network Providing Sub-Centimeter Accuracy

This paper describes the TELIAMADE system, a new indoor positioning system based on time-of-flight (TOF) of ultrasonic signal to estimate the distance between a receiver node and a transmitter node. TELIAMADE system consists of a set of wireless nodes equipped with a radio module for communication and a module for the transmission and reception of ultrasound. The access to the ultrasonic channel is managed by applying a synchronization algorithm based on a time-division multiplexing (TDMA) scheme. The ultrasonic signal is transmitted using a carrier frequency of 40 kHz and the TOF measurement is estimated by applying a quadrature detector to the signal obtained at the A/D converter output. Low sampling frequencies of 17.78 kHz or even 12.31 kHz are possible using quadrature sampling in order to optimize memory requirements and to reduce the computational cost in signal processing. The distance is calculated from the TOF taking into account the speed of sound. An excellent accuracy in the estimation of the TOF is achieved using parabolic interpolation to detect of maximum of the signal envelope at the matched filter output. The signal phase information is also used for enhancing the TOF measurement accuracy. Experimental results show a root mean square error (rmse) less than 2 mm and a standard deviation less than 0.3 mm for pseudorange measurements in the range of distances between 2 and 6 m. The system location accuracy is also evaluated by applying multilateration. A sub-centimeter location accuracy is achieved with an average rmse of 9.6 mm.Junta de Andalucía P08-TIC-0388

A sensor data fusion-based locating method for large-scale metrology

The measurement of geometric and dimensional variations in the context of large-sized products is a complex operation. One of the most efficient ways to identify deviations is by comparing the nominal object with a digitalisation of the real object through a reverse engineering process. The accurate digitalisation of large geometric models usually requires multiple acquisitions from different acquiring locations; the acquired point clouds must then be correctly aligned in the 3D digital environment. The identification of the exact scanning location is crucial to correctly realign point clouds and generate an accurate 3D CAD model. To achieve this, an acquisition method based on the use of a handling device is proposed that enhances reverse engineering scanning systems and is able to self-locate. The present paper tackles the device’s locating problem by using sensor data fusion based on a Kalman filter. The method was firstsimulated in a MatLAB environment; a prototype was then designed and developed using low-cost hardware. Tests on the sensor data fusion have shown a locating accuracy better than that of each individual sensor. Despite the low-cost hardware, the results are encouraging and open to future improvements

Localization and detection of wireless embeddable structural sensors using an unmanned aerial vehicle in the absence of visual markers

The objective of this thesis is to develop a fully integrated UAV based platform for autonomous collection of data from embedded sensors. Passive (battery-less) embedded sensors provide means for periodic long-term monitoring of civil structures like bridges. However, collection of data from these sensors requires extensive manual effort of locating them. UAVs can automate this process, although localization of these embedded tags in absence of visual markers pose a challenge. A RF (13.56MHz) reader is used to capture data from RF tags wirelessly. Different tag coil sizes are tested to observe effects on read range as well as to characterize the interaction volume between reader and tag. The UAV platform is integrated with the RF reader to autonomously capture data from tags using GPS based localization. Different sensor configurations are tested and characterized to meet the requirements of X,Y,Z localization set by the reader and tag interaction volume. Flight characteristics are also observed for various UAV navigation parameters. Results suggest that by using low-cost RTK GPS unit, the UAV is capable of detecting and localizing RF tags without any visual markers or aides.Electrical and Computer Engineerin

The Ant and the Trap: Evolution of Ant-Inspired Obstacle Avoidance in a Multi-Agent Robotic System

Interest in swarm robotics, particularly those modeled on biological systems, has been increasing with each passing year. We created the iAnt robot as a platform to test how well an ant-inspired robotic swarm could collect resources in an unmapped environment. Although swarm robotics is still a loosely defined field, one of the included hallmarks is multiple robots cooperating to complete a given task. The use of multiple robots means increased cost for research, scaling often linearly with the number of robots. We set out to create a system with the previously described capabilities while lowering the entry cost by building simple, cheap robots able to operate outside of a dedicated lab environment. Obstacle avoidance has long been a necessary component of robot systems. Avoiding collisions is also a difficult problem and has been studied for many years. As part of moving the iAnt further towards the real-world we needed a method of obstacle avoidance. Our hypothesis is that use of biological methods including evolution, stochastic movements and stygmergic trails into the iAnt Central Place Foraging Algorithm (CPFA) could result in robot behaviors suited to navigating obstacle-filled environments. The result is a modification of the CPFA to include pheromone trails, CPFA-Trails or CPFAT. This thesis first demonstrates the low-cost, simple and robust design of the physical iAnt robot. Secondly we will demonstrate the adaptability of the the system to evolve and succeed in an obstacle-laden environment

Millimeter-Precision Laser Rangefinder Using a Low-Cost Photon Counter

In this book we successfully demonstrate a millimeter-precision laser rangefinder using a low-cost photon counter. An application-specific integrated circuit (ASIC) comprises timing circuitry and single-photon avalanche diodes (SPADs) as the photodetectors. For the timing circuitry, a novel binning architecture for sampling the received signal is proposed which mitigates non-idealities that are inherent to a system with SPADs and timing circuitry in one chip

Measuring 3D indoor air velocity via an inexpensive low-power ultrasonic anemometer

The ability to inexpensively monitor indoor air speed and direction on a continuous basis would transform the control of environmental quality and energy use in buildings. Air motion transports energy, ventilation air, and pollutants around building interiors and their occupants, and measured feedback about it could be used in numerous ways to improve building operation. However indoor air movement is rarely monitored because of the expense and fragility of sensors. This paper describes a unique anemometer developed by the authors, that measures 3-dimensional air velocity for indoor environmental applications, leveraging new microelectromechanical systems (MEMS) technology for ultrasonic range-finding. The anemometer uses a tetrahedral arrangement of four transceivers, the smallest number able to capture a 3-dimensional flow, that provides greater measurement redundancy than in existing anemometry. We describe the theory, hardware, and software of the anemometer, including algorithms that detect and eliminate shielding errors caused by the wakes from anemometer support struts. The anemometer has a resolution and starting threshold of 0.01 m/s, an absolute air speed error of 0.05 m/s at a given orientation with minimal filtering, 3.1° angle- and 0.11 m/s velocity errors over 360° azimuthal rotation, and 3.5° angle- and 0.07 m/s velocity errors over 135° vertical declination. It includes radio connection to internet and is able to operate standalone for multiple years on a standard battery. The anemometer also measures temperature and has a compass and tilt sensor so that flow direction is globally referenced regardless of anemometer orientation. The retail cost of parts is $100 USD, and all parts snap together for ease of assembly

9-Meter-Long 3d Ultrasonic Objects Detection via Packaged Lithium-Niobate PMUTs

This paper reports a 9-meter-long ultrasonic 3D detector based on a packaged lithium niobate PMUTs (piezoelectric micromachined ultrasonic transducers). Compared with the state-of-the-art reports, three distinctive achievements have been demonstrated: (1) high uniformity and wide bandwidth PMUTs by optimized package designs for highly efficient ultrasonic energy transfer; (2) a long-range receiving beamforming detection scheme on a 4×4 PMUT array for up to 9 m detection rang - comparable to the longest reported range via PMUTs; and (3) 3D detection of multiple static/moving objects with the field of view exceeding 50°. As such, this device is valuable for various applications such as obstacle avoidance when both low power consumption and small form factor are desirable, including aerial drones