Introduction

LIDAR (Light Detection and Ranging) is a technique that uses pulses of light to perform distance measurements. Most LIDAR systems are based on measuring the time it takes for a laser pulse to complete a round trip between the LIDAR device and the target. After the distance to the target is calculated, the laser beam is scanned in different directions to create a 3D point cloud that provides spatial location and depth information, which can be used to identify and track objects.

A typical LIDAR system includes:

  • Transmitter: usually an “eyesafe” laser, emitting short pulses of light in the infrared, near-infrared, visible or ultraviolet wavelengths, depending on the application field
  • Scanner: rotating mirrors that steer the laser beam in different directions
  • Receiver: a lens to collect the reflected light pulses and focus them on a sensor
  • Timing circuitry: to measure the time difference between the launch of a pulse and the arrival of the reflected pulse
  • Signal processing and device control: to drive the subsystems in a coordinated manner and perform data processing algorithms, signal filtering and object detection

LIDAR is popularly used to make high-resolution maps, with applications in several fields of geoscience. However, the number of high-quality components that go into a single LIDAR system makes these devices bulky, fragile and extremely expensive, preventing its broader use.

Our solution

Imec is developing solutions to enable the efficient integration of semiconductor materials and devices into a silicon platform (chip), without reducing the efficiency or accuracy. This will reduce the size of LIDAR systems by a factor of 20 or more, and reduce the cost from tens of thousands of dollars to less than 200 dollars - consequently opening the technology to a widespread use in a new range of applications, including the Internet of Things (IoT).

This research is conducted in partnership with imec Leuven and imec USA - in collaboration with BRIDG and the College of Optics (CREOL) at the University of Central Florida.

Application domains

  • Intelligent machine vision and robotics
  • Assisted surgery
  • Air quality monitoring
  • Spectroscopic chemical sensing
  • Aerospace applications
  • Aerial drones
  • Autonomous vehicles
  • Automation of factory robots
  • High resolution fault analysis in factory lines
  • Service robots in hospitals and other customer oriented environments
  • 3D representation of objects

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