lidar
In plain wordsA sensor that measures distances by firing laser pulses and timing their reflections, building a 3D picture of its surroundings out of millions of points; widely used on robots and self-driving cars.
A remote-sensing method, and the sensor implementing it, that measures distance by emitting laser light and timing its return (time of flight) or, in frequency-modulated continuous-wave (FMCW) designs, by measuring the frequency shift of a chirped beam, which also yields each point's radial velocity. Scanning the beam — with spinning multi-beam heads, oscillating or microelectromechanical (MEMS) mirrors, or optical phased arrays — or flooding the scene with one wide pulse (flash lidar) produces a point cloud: up to millions of 3D points per second, usually with reflectance intensity. Automotive units mostly operate in the near infrared, around 905 or 1,550 nanometers. Lidar gives precise geometry in any lighting, but it costs more than cameras, has lower resolution, sees no color or text, and degrades in heavy rain, fog and snow. On autonomous vehiclesautonomous vehicle, n.: A vehicle, usually a car, truck or shuttle, that can drive itself, sensing the road, deciding what to do and steering, braking and accelerating with no human driving. and mobile robotsmobile robot, n.: A robot that travels around by itself — on wheels, tracks, legs, propellers or thrusters — such as a robot vacuum, warehouse cart, delivery robot or planetary rover. it supports simultaneous localization and mappingsimultaneous localization and mapping, n.: How a robot, drone or headset builds a map of an unfamiliar place while at the same time working out where it is on that map, using its cameras or laser scanners., obstacle detection and sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone. with cameras and radar; airborne lidar maps terrain, forests and cities.
The lidar sees the curb perfectly at night, but only the camera can read the stop sign.
Origin
Originally a blend of 'light' and 'radar' (a 1963 New Scientist article glossed it as 'light radar'), later backronymed as 'light detection and ranging'. Laser ranging followed the invention of the laser in 1960: Hughes Aircraft's 'Colidar' appeared in 1961, and Apollo 15 (1971) mapped the Moon with a laser altimeter. Lidar became central to self-driving research with the DARPA challenges of 2005 and 2007.
Usage note
Spelling is unsettled: LIDAR, LiDAR and lidar all occur, and many publications prefer lowercase. Whether self-driving cars need lidar is a long-running industry dispute, with Tesla's camera-only approach the best-known dissent.
Related
- simultaneous localization and mappingsimultaneous localization and mapping, n.: How a robot, drone or headset builds a map of an unfamiliar place while at the same time working out where it is on that map, using its cameras or laser scanners.
- sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone.
- autonomous vehicleautonomous vehicle, n.: A vehicle, usually a car, truck or shuttle, that can drive itself, sensing the road, deciding what to do and steering, braking and accelerating with no human driving.
- occupancy gridoccupancy grid, n.: A robot's map of the world drawn as a grid of small squares or cubes, each marked with the chance that something solid is there, so the robot knows where it can safely go.
- odometryodometry, n.: Estimating how far and in which direction a robot or vehicle has moved by adding up its own motion, such as wheel turns or how camera images shift, like counting your steps.
- 3D reconstruction3D reconstruction, n.: Building a 3D model of an object or place, its shape and often its colors, from photos, video or depth-sensor scans.
- depth estimationdepth estimation, n.: Working out how far away each point in a scene is from the camera, producing a 'depth map' that turns a flat picture into a sense of near and far.
Sources
- Thrun, S. et al. (2006). Stanley: The robot that won the DARPA Grand Challenge. Journal of Field Robotics 23(9), 661–692.
Mentioned in
autonomous vehicleautonomous vehicle, n.: A vehicle, usually a car, truck or shuttle, that can drive itself, sensing the road, deciding what to do and steering, braking and accelerating with no human driving., 3D reconstruction3D reconstruction, n.: Building a 3D model of an object or place, its shape and often its colors, from photos, video or depth-sensor scans., advanced driver-assistance systemadvanced driver-assistance system, n.: Car features that help the driver but do not replace them, such as automatic emergency braking, lane-keeping help, adaptive cruise control and blind-spot warnings., bounding boxbounding box, n.: The rectangle a vision system draws around an object it has found, stored as a handful of numbers giving the rectangle's position and size., DARPA Grand ChallengeDARPA Grand Challenge, prop. n.: A series of US government-sponsored races for driverless vehicles held in 2004, 2005 and 2007. No robot finished the first race; within three years, cars were navigating mock city traffic., depth estimationdepth estimation, n.: Working out how far away each point in a scene is from the camera, producing a 'depth map' that turns a flat picture into a sense of near and far., mobile robotmobile robot, n.: A robot that travels around by itself — on wheels, tracks, legs, propellers or thrusters — such as a robot vacuum, warehouse cart, delivery robot or planetary rover., perceptionperception, n.: How an AI system or robot turns raw sensor signals, such as camera pixels, microphone sound or laser scans, into an understanding of what is around it: objects, people, words and distances., physics simulatorphysics simulator, n.: Software that imitates how real objects move, collide, bend and fall, so robots and their AI can be designed, trained and tested on a computer before touching the real world., point cloudpoint cloud, n.: A 3D picture made of many dots floating in space, each marking a spot on a surface, as captured by a laser scanner or worked out from photos., robotaxirobotaxi, n.: A taxi with no human driver: you summon it with a phone app, and a self-driving car picks you up and drives you to your destination., sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone., simultaneous localization and mappingsimultaneous localization and mapping, n.: How a robot, drone or headset builds a map of an unfamiliar place while at the same time working out where it is on that map, using its cameras or laser scanners., WaymoWaymo, prop. n.: A company owned by Google's parent, Alphabet, that runs fully driverless robotaxi services in several American cities., occupancy gridoccupancy grid, n.: A robot's map of the world drawn as a grid of small squares or cubes, each marked with the chance that something solid is there, so the robot knows where it can safely go., proprioceptionproprioception, n.: A robot's sense of its own body: where its joints are, how fast they are moving and how hard its motors are pushing, measured by internal sensors rather than cameras.