Sonar drives gesture recognition startup
The work was conducted by PhD students and company co-founders Richard Przbyla and Stefon Shelton. The company is led by co-founder and CEO Michelle Meng-Hsuing Kiung, a former executive with the Micron Technology Inc. (Boise, Idaho) imaging group, now Aptina Imaging Inc. (San Jose, Calif.).
The company claims on its website that the use of sound waves to locate moving objects is more energy efficient than trying to recognize then from an image sensor. The company compares a camera consuming 1W to record video while the Chirp transducer consumes 400-microwatts to perform 3D range finding.
As part of his PhD studies at University California Berkeley Przbyla developed the system with Stefon Shelton who studied at University California Davis and worked in the Berkeley Sensor and Actuator Center (BSAC). To show of the micro-machined ultrasound transducer and its companion ASIC the pair developed applications for gesture recognition with computer operating systems for such things as page turning and controlling an airplane within a flight simulator.
The systems works by driving an array of silicon membranes in the MEMS device to emit an ultrasonic wave from the device and then uses the membranes in a microphone mode – to detect the return signal. The use of time-of-flight information from the array of sensors allows calculation of the distance and direction and the build-up a 3D depth map in front of the sensor.
This is similar to the way a bat uses ultrasound to map its surroundings and also puts Chirp Microsystems in the same technology camp as Elliptic Labs Inc. (Palo Alto, Calif.). Elliptic Labs was founded as a spin-off from the University of Oslo in 2006. The company grew from initial research background in multi-path interference management for multi-antenna mobile communications.
Chirp’s claims its technology is not only more efficient than light-based systems but can be made small enough to embed in portable equipment such as smartwatches.
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