Baidu’s unmanned self-driving bicycles for China should have a prototype by the end of this year

Google’s driverless cars have been in the technology and futurist news for years, but Chinese search giant Baidu recently revealed development of unmanned autonomous bicycles. Self-driving cars face more regulatory and safety hurdles. Automated bikes are much more well-suited to most of Asia, where bicycle ownership outstrips car ownership.

Update – Nextbigfuture has looked at several self driving robotic trikes and bicycle projects. Technologically this is feasible and there are strong economic benefits for doing it.

A prototype for the world’s first unmanned bike should be revealed before the end of this year, according to Techweb. The bike can reportedly identify its owner in some way, and presumably putts around using an electric motor. Sources told Techweb the bike sans rider can sense its environment well enough to avoid obstacles and navigate complicated road conditions.

Baidu deep learning laboratory (Institute of Deep Learning, Idl) is developing unmanned bike will come out during the year, which may be the world’s first unmanned bike in the true sense.

China has 551 million bike riders, of which 181 million use electric bikes.

The bikes could be used for package delivery and for old people or young people who cannot drive themselves. Self balancing technology could be used or tricycles could be used.

Baidu Institute is responsible for research and development of the unmanned deep learning bike, machine learning research by a group of outstanding scientists and engineers to develop the depth of learning platforms and algorithms, computer vision, 3D vision, pattern recognition, human-computer interaction and other areas of the composition.

Google’s driverless car has a Velodyne 64-beam laser (laser range finder) on the roof. It emits a laser to measure the distance from the other moving objects by radar sensors and infrared cameras perceive the surrounding environment, the resulting 3D maps and high-resolution map of the real environment combine to produce the data model to let the car make car.

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