SLAM algorithm enables robots to achieve autonomous movement and accurate spatial positioning

In recent years, the level of research and development of robots is being improved step by step, and various robots have been applied to various industries. Nowadays, the biggest limitation of robots lies in its autonomous mobility and accurate spatial positioning technology.

According to the 2025 China Manufacturing Strategy, intelligent robots will be the focus of China's future development. Service robots will take root in the fields of national defense, aerospace, medical, agriculture, education, entertainment, etc., and their development will gradually become intelligent, networked and humanized. Diversified and so on. According to the Analysys think tank: In 2015, the scale of China's service robot market will be about 8.2 billion yuan. In 2016, it will grow to about 14 billion yuan, and the market size in 2017 is expected to exceed 20 billion yuan.

With the rapid development of the service robot market, there is a growing demand for higher functionality. Service robots want to better serve humans and must solve two major problems:

The first problem is voice interaction, which is used to solve human-machine conversations.

The second problem is the movement of the robot. A robot that doesn't move properly is just a humanoid tablet. Mobile can't be realized, and there is no service at all.

Dalian and Chuanglao Co., Ltd., which have been in contact with us recently, are a company that develops core algorithms related to machine vision movement in the field of artificial intelligence.

And the lazy people just launched the first generation of products AIEs1-1 (indoor environment mobile) this year, which is equipped with a set of core algorithms for SLAM (map construction and real-time positioning), path planning and dynamic obstacle avoidance through machine vision. system. The product will be used to solve the problem of autonomous movement of service robots. Compared with the current laser SLAM products on the market, and the products of the lazy people have a large price advantage, and the function and use effect is better than the laser. In the future, the company will also launch the semantic map SLAM (outdoor environment mobile) and the logical map SLAM (complete complex tasks). The complex tasks mainly refer to complex terrain movement, complex scene understanding and spatial positioning. The robot can make environmental judgments on language tasks and complete the usual A complex task that only humans can accomplish.

SLAM algorithm enables robots to achieve autonomous movement and accurate spatial positioning

In terms of profitability, and the lazy people are currently adopting the toB model, which provides robot manufacturers with visual navigation core technology. Currently, there are 7 cooperative manufacturers. This year's estimated revenue is around 3 million.

The relevant person in charge of the company said that in the future, machine vision will be increasingly used in service robots, including image recognition, face recognition, and human skeleton recognition. And the lazy people will slowly introduce these technologies into their subsequent series of products. In the long run, with the diversification of application scenarios, service robots are expected to become the next important data entry after mobile phones and become intelligent terminals. The market size will be between smartphones and cars, meaning it will be a market that is expected to reach trillions.

Liu Yang, the founder of the company, is a continuous entrepreneur with 10 years of experience in the management of his own IT technology company. Technical Team Dr. Zhang is an electrical engineering and automation chemist at Beijing University of Aeronautics and Astronautics, a master's degree in electronic science and technology from Peking University, and a Ph.D. in intelligent mechanical information science at the University of Tokyo. He specializes in visual environment perception and modeling for human-oriented robots, lasers. Sensor point cloud data understanding and reconstruction, robot motion planning, robotic autonomous positioning and mapping based on color depth camera.

It is understood that the company is currently seeking Pre-A round financing.

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