Think 3D customers have master robots such as main functions, Huituo and Easy Control.
In the autonomous driving industry, mining is far less glamorous than Robot-Taxi, but the mining area is one of the most suitable scenes for automatic driving, because the mining roads are closed, and each mine has a single shift. Point-to-point transportation on relatively fixed routes, often at speeds below 30 km/h. However, there have been many pain points in the production and transportation of mining areas: personnel safety hazards, driver recruitment difficulties, and high operational management costs. Ideally, these problems can be solved by autonomous driving techniques.
Because of the optimistic advantage of the commercialization of mining areas, some high-precision map service providers began to shift their eyes from the open road to the closed area of the mining area. Recently, Siddi 3D Technology Co., Ltd. (hereinafter referred to as “Spirit 3D”) is one of them.
The company was established in January 2017. Its core technologies include 3D data, high-precision maps, spatial information, remote sensing vision, etc. Its goal is to provide high-precision map services for engineering and provide a complete digital solution for mining areas. .
In particular, the high-precision map provides overall path planning for the transportation vehicles in the mining area, including the slope and curvature of the road, lane markings, and marking of roadside objects, and provides a high-precision lane model to assist the vehicle in adjusting the spacing and Speed, etc.
At present, Siddi 3D mainly provides high-precision map solutions for auto-driving startups such as main function, Huituo and Yikong, and provides smart mining solutions for state-owned mining companies such as China Coal Group. The coal mines in Xilinhot, Inner Mongolia and Pingyi, Shanxi have established cooperation. The business model includes collaborative research and development, technical services and product sales.
The company’s founder and CEO Chen Buke told the mining area that the automatic driving is essentially saving fuel and labor costs. For example, in terms of manpower expenditure, a mine car needs 3-4 drivers to perform 3-4 shifts per day, and each driver’s annual salary ranges from 200,000 to 300,000, so that one car per year The labor cost is 1 million to 1.2 million. The automatic driving transformation is a one-time equipment investment, the transformation cost will need about 500,000, about a year or so after the operation can return to the original, and start to profit.
Spirit 3D mine 3D model perspective (Source: 3D)
Talk about why these mine autopilot companies don’t do high-precision maps themselves, and the three-dimensional technical consultant and CMO Tang Wei told the autopilot solution developers to focus on vehicle perception, decision-making and In the research and development of control and other aspects, there are also considerable technical barriers in the fields of remote sensing, mapping and positioning. Therefore, it is better to cooperate with professional companies.
According to the information provided by Sidi Di, they received more than 1 million orders from China Coal Group in the first half of this year for the development of smart mining areas. Tang Wei said that China Coal Group is a leader in the domestic coal mining industry and has more than 80 open pit mines. “Once we take the China Coal project as the core and build the overall system of the smart mining area, we can apply the complete system and solution to other mining areas.”
Chen Bu Ke said that the cost of upgrading and upgrading of each mining area is over 100 million. If only high-precision maps and 3D modeling business are counted, the average investment per mine is estimated to be 5 million to 8 million. With the high-precision map and 3D modeling business as the breakthrough, Sidi 3D will gradually expand the business scope and influence in the upgrading, transformation and operation of the mining area, and eventually become the operational information service provider of the smart mining area.
Situ 3D expects that they will have about 5 million revenues in the smart mining area next year, and 30 million revenues in 2021; in the high-precision map, this year is expected to have more than 3 million revenues, next year 12 million, 30 million in 2021.
Talking about whether or not to worry about the company doing the “high-definition strike” of the open road high-precision map to do the mining area. Tang Wei said that in terms of technology, the high-precision map of the mining area pays great attention to the real-time update speed of the data, because the coal mine is constantly Mining, the map has been changing; from the market point of view, mining areas for automatic driving transformation are almost open-pit mines, not wells, and the cost of the open-pit mines is high, only the state-owned units have the strength to go The possibility that the state-owned units are open to the outside world is very small. Therefore, the company that first established cooperation with the state-owned mining area has a first-mover advantage.
With regard to the update of the data, Chen Buke said that the mining area is divided into several areas, including dumping operations, excavation operations, road transportation and marginal areas. Each area has different timeliness and frequency requirements for data update. For example, the changes on the road are not so frequent. You can use mobile scanning (unmanned or in-vehicle) to update data every 3 days. For marginal areas with little change, you can scan with drones, 2-3 days. Update the data once; for the core work area, a fixed scan can be used to ensure that it is updated in a few hours.
Chen Bu Ke said that the current transformation of the smart mining area is still in its infancy, and the entire upgrade process will be very long. It is expected to take 5 to 8 years to complete.
Chenbuck graduated from the University of Calgary, Canada, majoring in remote sensing engineering, and is a certified professional in the Canadian Engineering Association.