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Velodyne Lidar is a Silicon Valley-based lidar technology company spun off from Velodyne Acoustics. As of August 2016, the company worked with 25 self-driving car programs. Velodyne Lidar ships sensors to mobility industry customers for testing and commercial use.

History
David Hall founded Velodyne in 1983 as an audio company specializing in subwoofer technology.

Velodyne's experience with laser distance measurement started in 2005, when David Hall and his brother Bruce (then president of Velodyne) entered a vehicle in a driverless car race called DARPA Grand Challenge sponsored by the Defense Advanced Research Projects Agency (DARPA). The experience led them to realize shortcomings both in camera-centric approaches and in existing lidar technology, which only scanned a single, fixed line of sight. Velodyne developed new sensors for the 2007 race. The brothers sold their perception detection system as a steering input to five of the six teams that finished the 2007 race. The system rotated 64 lasers and measured the time of flight to calculate distance of surrounding objects. This created a 360 degree 3D map of the environment. The new system produced one million data points per second, while earlier systems produced 5,000 data points per second.



Velodyne donated one of its early prototype sensors to the Robotics Collection at the Smithsonian Institution's National Museum of American History in 2011.

In 2016, Velodyne's Lidar department was spun off from Velodyne Acoustics as Velodyne Lidar, Inc. On August 16, 2016, Velodyne announced a $150M investment from Ford and Baidu. In 2017, the company opened their fully automated megafactory in San Jose, California, to speed up production while reducing the cost of sensors. Velodyne also has a production facility in Morgan Hill, California, and an R&D center in Alameda, California.

In 2017, Velodyne provided their sensors as a sponsor of the SAE GM AutoDrive Challenge, a three-year competition in which eight university teams develop a Level 4 automated vehicle.

In 2018, Velodyne partnered with Mothers Against Drunk Driving in a campaign to advance autonomous vehicles for improving roadway safety and preventing impaired driving deaths.

In October 2018, Velodyne organized the inaugural World Safety Summit on Autonomous Technology. In the same year, the company also signed agreements to collaborate with Nikon and Veoneer for manufacturing and mass production.

In January 2020, Hall announced he was stepping down as CEO in favor of Anand Gopalan, who was previously CTO.

Technology


Applications for Velodyne Lidar's technology include autonomous vehicles, advanced driver assistance systems, mapping, security, and unmanned aerial vehicles. Velodyne's sensors have a range of up to 300 meters and can be used for immediate object detection without additional sensor fusion. When in use on a moving vehicle, a Velodyne sensor can create a precise image of the road ahead, including detailed street signs and foliage.

In April 2017, Velodyne announced Velarray, a sensor that produces a directional image rather than the surround view provided by previous sensors. The range, resolution, and field of view facilitate object detection, allowing for longer braking distance and increased safety. Designed for seamless vehicle integration, this compact sensor generates a detailed directional image, day or night. It can be concealed within roof lines, in bumpers and behind windshields.

Also in 2017, the company introduced the Alpha Puck (previously known as VLS-128) sensor with a range of up to 300 meters. This sensor is made for autonomous driving and advanced vehicle safety at highway speeds.

In 2019, Velodyne introduced the VelaDome™, a compact embeddable lidar that provides a 180° x 180° image for near-object avoidance. The company also introduced Vella™, software that establishes the Velarray™ as an integral component for advanced driver assistance systems (ADAS).

Partners and customers


In 2010, Google (now Alphabet) began testing self-driving cars on the streets in the San Francisco Bay Area using Velodyne's Lidar technology. Alphabet's first self-driving car prototype (built on Toyota's Prius model) used Velodyne's HDL-64E lidar sensor. Since then, Alphabet has stopped using Velodyne sensors in its vehicles.

In 2012, Velodyne Lidar signed a contract with Caterpillar for a supply of lidar sensors to be used for off-road vehicles. These sensors help Caterpillar map quarries, farms and work sites during construction.

In 2012 through 2015, Velodyne's spinning HDL-32E sensors have been seen on mobile mapping vehicles by Nokia Here, Microsoft Bing Maps, Tencent, Baidu, and TomTom. Leading mapping providers like Topcon and Leica Geosystems also use Velodyne's scanners for their turnkey mobile solutions.

In 2016, Ford Motor Company announced that it will expand its fleet of self-driving R&D vehicles and use Velodyne Lidar's Ultra Puck sensors.

In 2017, Velodyne partnered with Renovo as Reference Lidar provider for AWare automated mobility operating system and with Mercedes-Benz for a Perception System Contract.

In 2018, the company partnered with Embark, Geodetics, Voyage, Exyn Technologies, Yellowscan, Phoenix LiDAR, NAVYA, ThorDrive and Postmates. Velodyne Lidar also partnered with Nikon as a new strategic investor with an investment of $25M.

Awards and recognition

 * In 2015, Frost & Sullivan gave Velodyne's VLP-16 sensor the North American Automotive ADAS (Advanced Driver Assistance System) Sensors Product Leadership Award
 * In 2017, Velodyne Lidar was an Honoree at the CES Innovation Awards, Drones & Unmanned Systems, for the Puck Lite
 * In 2017, Velodyne was recognized as one of the Top 10 Most Innovative Companies in Transportation
 * In 2018, Velodyne Lidar was selected as “Industry Choice Company of the Year” by a panel of industry expert judges at the TU-Automotive Detroit Conference
 * In 2018, Velodyne was honored with East Bay Innovation Awards in the Engineering & Design Category
 * In 2018, the Ultra Puck won the silver 2018 Edison Award for Autonomous Vehicle Technology