Urtis: a Small 3d Imaging Sonar Sensor for Robotic Applications

Verellen, Thomas; Kerstens, Robin; Laurijssen, Dennis; Steckel, Jan

doi:10.1109/icassp40776.2020.9053536

Cited by 6 publications

(13 citation statements)

References 15 publications

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“…The DOA algorithms that will be compared are DAS, Capon FBSS, MUSIC, MUSIC FSS, and MUSIC FBSS. For which we selected the frequency with the highest energy to be used in (7), which was equal to 31.250 kHz. This frequency satisfies the half-wavelength criteria for our array where the distance between the microphones is equal to 5 mm.…”

Section: Methodsmentioning

confidence: 99%

“…The Capon beamformer is also forwardbackward spatially smoothed to ensure the localization of the present coherent sources. We also include the first real-life processed imaging results of the µRTIS while using different beamforming algorithms which were first presented in [7]. This paper is structured as follows: firstly, we explain the used signal model and used algorithms in Section III.…”

Section: Volume 4 2016mentioning

confidence: 99%

“…Currently we use spatially smoothed MUSIC to process the recorded data, which requires a URA and therefore was not an option with the eRTIS. Initial real-life results and a more in-depth description of the hardware and processing of the µRTIS is available in [7]. However, as previously mentioned we will in this paper use a simulation of a rectangular array of 8 × 8 which has been spatially smoothed with subarrays of 5 × 5.…”

Section: µRtismentioning

confidence: 99%

“…This new version features a smaller footprint for all kind of robotic applications in need for cost-effective 3D environmental perception which do not rely on optics. This smaller version is named the micro Real Time Imaging Sonar (µRTIS) [7]. The µRTIS features 30 microphones placed in Uniform Rectangular Array (URA) of 5 by 6 microphones in a footprint of 5.7 cm by 4.6 cm.…”

Section: Introductionmentioning

confidence: 99%

“…Figure from[7] showing a side by side view of the µRTIS (left) and the eRTIS (right), which are two 3D imaging sonar sensors developed by CoSys-Lab. The microphone array in the eRTIS sensor consists of a pseudo-random 32 microphone array placed using Poisson Disc-Sampling, whereas the microphone array in the µRTIS consists of a 30 microphone URA of 5 × 6.…”

mentioning

confidence: 99%

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High-Resolution Ultrasound Sensing for Robotics Using Dense Microphone Arrays

2020

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State-of-the-art autonomous vehicles use all kinds of sensors based on light, such as a camera or LIDAR (Laser Imaging Detection And Ranging). These sensors tend to fail when exposed to airborne particles. Ultrasonic sensors have the ability to work in these environments since they have longer wavelengths and are based on acoustics, making them able to pass through the mentioned distortions. However, they have a lower angular resolution compared to their optical counterparts. In this paper a 3D in-air sonar sensor is simulated, consisting of a Uniform Rectangular Array similar to the newly developed micro Real Time Imaging Sonar (µRTIS) by CoSys-Lab. Different direction of arrival techniques will be compared for an 8 by 8 uniform rectangular microphone array in a simulation environment to investigate the influence of different parameters in a completely controlled environment. We will investigate the influence of the signal-to-noise ratio and number of snapshots to the angular and spatial resolution in the direction parallel and perpendicular to the direction of the emitted signal, respectively called the angular and range resolution. We will compare these results with real-life imaging results of the µRTIS. The results presented in this paper show that, despite the fact that in-air sonar applications are limited to only one snapshot, more advanced algorithms than Delay-And-Sum beamforming are viable options, which is confirmed with the real-life data captured by the µRTIS. INDEX TERMS Acoustic signal processing, array signal processing, beamforming, microphone arrays, sonar.

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Section: Methodsmentioning

confidence: 99%

Section: Volume 4 2016mentioning

confidence: 99%

Section: µRtismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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High-Resolution Ultrasound Sensing for Robotics Using Dense Microphone Arrays

2020

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HiRIS: An Airborne Sonar Sensor With a 1024 Channel Microphone Array for In-Air Acoustic Imaging

Laurijssen,

Daems,

Steckel

2024

IEEE Access

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Airborne 3D imaging using ultrasound is a promising sensing modality for robotic applications in harsh environments. Over the last decade, several high-performance systems have been proposed in the literature. Most of these sensors use a reduced aperture microphone array, leading to artifacts in the resulting acoustic images. This paper presents a novel in-air ultrasound sensor that incorporates 1024 microphones, in a 32-by-32 uniform rectangular array, in combination with a distributed embedded hardware design to perform the data acquisition. Using a broadband Minimum Variance Distortionless Response (MVDR) beamformer with Forward-Backward Spatial Smoothing (FB-SS), the sensor is able to create both 2D and 3D ultrasound images of the full-frontal hemisphere with high angular accuracy with up to 70dB main lobe to side lobe ratioin the array response in a single-source scenario. This paper describes both the hardware infrastructure needed to obtain such highly detailed acoustical images, as well as the signal processing chain needed to convert the raw acoustic data into said images. Utilizing this novel highresolution ultrasound imaging sensor, we wish to investigate the limits of both passive and active airborne ultrasound sensing by utilizing this virtually artifact-free imaging modality.

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SonoTraceLab—A Raytracing-Based Acoustic Modeling System for Simulating Echolocation Behavior of Bats

Jansen,

Steckel

2024

IEEE Access

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Echolocation is the prime sensing modality for many species of bats, who show the intricate ability to perform a plethora of tasks in complex and unstructured environments. Understanding this exceptional feat of sensorimotor interaction is a key aspect into building more robust and performant manmade sonar sensors. In order to better understand the underlying perception mechanisms it is important to get a good insight into the nature of the reflected signals that the bat perceives. While ensonification experiments are an important way to better understand the nature of these signals, they are as timeconsuming to perform as they are informative. In this paper we present SonoTraceLab, an open-source software package for simulating both technical as well as biological sonar systems in complex scenes. Using simulation approaches can drastically increase insights into the nature of biological echolocation systems, while reducing the time-and material complexity of performing them.

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Urtis: a Small 3d Imaging Sonar Sensor for Robotic Applications

Cited by 6 publications

References 15 publications

High-Resolution Ultrasound Sensing for Robotics Using Dense Microphone Arrays

High-Resolution Ultrasound Sensing for Robotics Using Dense Microphone Arrays

HiRIS: An Airborne Sonar Sensor With a 1024 Channel Microphone Array for In-Air Acoustic Imaging

SonoTraceLab—A Raytracing-Based Acoustic Modeling System for Simulating Echolocation Behavior of Bats

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