Infrared (IR) sensors can be used for obstacle detection because of their high resolution, low cost, and fast response times. However, IR sensors require knowledge of the surface properties prior to implementation due to their non-linear characteristics and dependence on reflectance properties. Various surface materials reflect and absorb IR energy differently, so target material identification is required for accurate distance measurements.

Optical-based sensing technologies have a similar principle to ultrasonic technology. Instead of using sound waves, however, optical technology uses LEDs to emit light waves and detect the time-of-flight, which can then convert based on the speed of light principle. The speed of light is much faster than the speed of sound, therefore optical-based sensing is faster than ultrasonic. It does have limitations in bright ambient lighting conditions and smoky or foggy environments, however, as these environments make it difficult for the light receptor to detect the emitted light. Optical sensing also has limitations in detecting clear materials like glass or water. Light passes through these materials, whereas ultrasonic bounces off.

Radar and LIDAR-based technologies aim to provide a multi-point array of data, instead of a single time-of-flight measurement. This allows for highly accurate data points and the ability to map out and distinguish tiny moments within the environment. However, the increased functionality makes these systems much more expensive than the other solutions mentioned previously.

Table 1-1 summarizes differences between PIR, ultrasonic, optical ToF, and mmWave.

To view TI's full proximity sensing table, refer to TI’s proximity sensing technology infographic.