Alibaba Group’s Cainiao Network and RoboSense have jointly released G Plus, a solid-state LiDAR unmanned logistics vehicle. Announced at Alibaba Group’s Cainiao Network 2018 Global Smart Logistics Summit held in Hangzhou, China, the most important feature of the newly announced G Plus driverless delivery vehicles is the solid-state LiDAR technology, the RS-LiDAR-M1Pre, developed by China’s RoboSense. This is claimed to be the first time that solid-state LiDAR has been officially used in the development of an unmanned vehicle, and, says Alibaba, heralds the beginning of a new solid-state LiDAR era in driverless vehicles.
RoboSense has reached a strategic partnership with Alibaba to provide delivery vehicles with solid-state LiDARs for all G Plus unmanned logistics cars, and says that this can drastically reduce the cost of the driverless vehicles. The vehicles can be mass-produced, allowing the expansion of unmanned logistics vehicles and streamlining mass market delivery logistics, for the rapid popularization of the vehicles. The unmanned cars and trucks can also be equipped with different smart devices according to demand, turning the vehicle into a courier vehicle, a mobile self-pickup station, a mobile coffee vending cart, etc., which can be applied to various new retail scenarios.
RoboSense told Connected Car that RS-LiDAR-M1Pre is the first MEMS solid-state LiDAR it has launched. The technology was first publicly presented and demonstrated at CES 2018 in Las Vegas and has apparently attracted widespread attention in the industry. The core technology of the MEMS solid-state LiDAR is disruptive to traditional mechanical multi-beam radars. The MEMS micro mirror scanning scheme used in the RS-LiDAR-M1Pre requires only a few laser emitters and receivers to scan through the MEMS micro-mirror in both directions because of the swing angle. The resolution is a very fine, high angle and vertical angle resolution that reaches 0.2° throughout the angle of view.
In contrast, for traditional mechanical multi-beam LiDAR to achieve the same effect, they require more than a hundred laser transmitters and receivers to rotate and scan at the same time, which increases material and human costs and reduces yield and reliability. While improving the performance of LiDAR, the cost savings is also great – RoboSense suggestst that its LiDAR costs as little as a few hundred dollars – and at the same time the miniaturization of the scanning structure is said to greatly improve the stability of LiDAR.