Aurora has introduced its FirstLight LiDAR as a sensor on its next-generation test vehicles, where the company says it helps the perception system see and track objects farther, faster, and with greater precision. A fleet of Aurora vehicles, fully integrated with the FirstLight LiDAR, is expected to be on roads later this summer.

“Of course, architecting and integrating isn’t enough; the Aurora Driver needs to see well enough and far enough — a critical requirement for safe, effective long-haul and middle-mile trucking. For this, we needed long-range, multi-modal sensing and for a long time, that didn’t exist,” said the Aurora team.

Last year, the company acquired Blackmore, which has experience with frequency-modulated, continuous-wave (FMCW) LiDAR development. Over the last year, the teams have combined Blackmore’s LiDAR team with Aurora’s hardware and software engineering teams. Together, they specified, designed, prototyped, and fabricated a LiDAR system designed to let the Aurora Driver to see further and better.

FMCW LiDAR sends out a constant stream of light (continuous-wave) and changes the frequency of that light at regular intervals (frequency-modulated). This allows the company to both determine the location of objects and precisely measure their velocity using the Doppler effect.

The company says that FMCW LiDAR provides advantages over even AM LiDAR systems, especially when it comes to long-haul trucking. For instance, it reportedly sees farther, well beyond 983 ft (300 m) even on targets that don’t reflect much light.

It also reportedly provides accurate velocity for each data point instantaneously to help the perception system process incoming data faster because it no longer has to estimate velocity from changes in object position. Instantaneous velocity also makes it easier for the perception system to recognize distant and sparse data points as objects, and track how those objects are moving over time.

The company adds that FMCW LiDAR has less “static” than traditional AM LiDAR systems, which can be affected by:

  • Solar loading: they may perform poorly in bright sunlight
  • Sensor crosstalk: sensors may be confused by other sensors’ light pulses
  • Self-interference: a sensor may be confused by its own previous pulse(s)

All of these events can cause errors in the data, resulting in problems like “ghost” objects that don’t actually exist or objects that are reported in the wrong location. According to the company, vehicles using AM LiDAR need extra hardware, complex software, and more computational power than FMCW LiDAR to manage these types of data artifacts.

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