5.4: Sensors using Sound

Last updated
Save as PDF

Page ID: 14798

\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

5.4.1. Ultra-sound Distance Sensors

An ultra-sound distance sensor operates by emitting an ultrasound pulse and measures its reflection. Unlike a light-based sensor that measures the amplitude of the reflected signal, a sound-based sensor measures the time it took the sound to travel. This is possible, because sound travels at much lower speed (300m/s) than light (300,000km/s). The fact that the sensor actually has to wait for the signal to return leads to a trade-off between range and bandwidth. (Look these definitions up above before you read on.) In other words, allowing a longer range requires waiting longer, which in turn limits how often the sensor can provide a measurement. Although US distance sensors have become less and less common in robotics, they have an advantage over light-based sensors: instead of sending out a ray, the ultra-sound pulse results in a cone with an opening angle of 20 to 40 degrees. By this, US sensors are able to detect small obstacles without the requirement of directly hitting them with a ray. This property makes them the sensor of choice in automated parking helpers in cars.

5.4.2. Texture Recognition

Audible sound consists of high frequency vibrations in the range between 20 Hz and roughly 15 kHz. Microphones are therefore ideally suited to measure vibrations in this range. This allows them to double as the Pascinian corpuscle in human skin cells, which is known to have a resonance frequency of 250 Hz and is mostly responsible for texture recognition. Indeed, rubbing a texture against a microphone can indeed be used for differentiating between tens and hundreds of different textures (Hughes & Correll 2014), with a number of commercial sensors available. These sensors usually calculate the frequency spectrum of the recorded signal, which can then be classified using machine learning techniques. Being able to recognize a texture by touch is important in applications like grasping and navigation through cluttered terrain.