Environmental robot company received 100 million yuan in financing!Fired the first shot at the swimming pool cleaning track
It is reported that the environmentrobotThe company Zhongqing Technology has recently obtained nearly 100 million yuan in round B financing. The investors are China Overseas Entrepreneurship Fund, Six Prism Capital, First Industry Capital, and Suzhou Wuzhong Economic and Technological Development Zone Industrial Investment. This round of financing will be used for product development, brand building and global market expansion.
Zhongqing Technology was established in 2015. At present, more than 70% of the employees are engaged in technology research and development, all of whom are from world-renowned universities and technology companies. Many of them have worked in well-known international companies such as Honeywell, Panasonic, Siemens, and IBM. experience in scientific research, so the team has both hardware, software, Robots andAIAlgorithmic ability. Founder and CEO Fei Zhao graduated from Tsinghua University with a bachelor’s degree and a doctorate degree from Georgia Institute of Technology in the United States. He once served as the chief scientist of Retroficiency, an artificial intelligence company in Boston, and has been deeply involved in the field of artificial intelligence and data fusion.
At present, the company has more than 100 patents in the world. The core technology involves the fields of particle aerodynamics, air cleaning technology and indoor environment control algorithm. Living environment.
Zhao Fei, founder and CEO of Zhongqing Technology, said that courtyards and outdoors are one of the important scenes of family life in Europe and the United States. At present, there are about 30 million private swimming pools in the world, with an annual growth rate of about 5%. Among them, Europe and the United States account for nearly 90% of the number. Pool cleaning robots are in high demand. Therefore, in 2020, it established the global brand Degrii in Silicon Valley, and launched the wireless swimming pool cleaning robot Degrii Zima Pro based on ultrasonic SLAM technology earlier this year, cutting into courtyards and outdoor scenes.
under water robotIt is not a simple research and development work. Around the swimming pool cleaning robot, Zhongqing Technology spent 8 years to overcome the core through self-researchsensorelectronic control system and control algorithm, and applied for more than 140 patents worldwide, laying a solid foundation for the realization of underwater wireless SLAM.
At present, the Degrii swimming pool cleaning robot developed by Zhongqing Technology integrates more than 20 sensors, including four-way ultrasonic radar, and cooperates with six-axis gyroscope, mileage sensor, water immersion sensor, etc. 3D path planning of swimming pool bottom and wall.
Nowadays, using slam technology to map and navigate robots on land has become one of the most commonly used autonomous action solutions for robots, but robots using this technology underwater are not common. This is due to the underwater characteristics that bring many difficulties that slam technology does not face on land or indoors. The limited illumination range, the existence of ocean currents, turbidity and uniformity of the environment will all become challenges in robot positioning and mapping applications. some problems.
Although the triangulation method can be used in the underwater environment, this method will consume a lot of manpower and material resources, and it is difficult to implement. When the robot is in a position and does not know its own posture, the triangulation The measurement method will bring a lot of trouble, so the underwater slam algorithm is a technology that must be introduced into underwater robots.
In addition, the selection of sensor materials, feature extraction, determination of absolute positions, and the complexity of algorithms are all technical problems encountered by underwater robots. Underwater is a complex environment, and sensors are easily included in this environment. Too much deformed data. These incorrect data are likely to cause map construction failure or map distortion. When the robot uses such a wrong map to work, it cannot perform tasks according to the design of the program.
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