Where is the development path of Chinese service robots?

In 2016, China's service robot market has entered a state of blind development. The products lack uniform standards, low technical content, and serious homogenization. Many enterprises are taking advantage of the policy to make money, and the capital “high fever” is serious.

Under the capital bubble and hidden dangers of the market, how should Chinese service robots develop, and where is the future development path?

Sensor development

The sensors are the "eyes", "ears" and "nose" of the service robot. With the help of sensors, the service robot can obtain various information such as the expression, tone, and surroundings of the owner. The accuracy and integration of the sensor directly determine the choice and execution quality of robot cognitive observation, spatial positioning and autonomous avoidance strategies. In the future, infrared sensors, ultrasonic sensors, tactile sensors, and visual sensors will become more and more accurate, helping service robots to complete more complex tasks and provide better services.

The Pepper service robot, which has been on sale, integrates a large number of 3D sensors, touch sensors, buffer sensors, and laser sensors to recognize and make a richer and more humane response based on people's emotions.

Chip development

The chip is the "brain" of the service robot, and undertakes the task of data analysis and processing, which in turn determines the computing power and mobility of the service robot. In the future, the performance of service robots will increase the requirements for chips. The relevant person in charge of Qualcomm said that in the near future, robots will demand more chips than smart phones.

In August 2014, IBM released the SyNAPSE chip, which integrates "neuron" and "synaptic" cores, which can simulate the human brain and promote the development of service robots toward intelligence. In December 2016, researchers at Duke University developed a motion planning chip for the robotics field that increased the speed of object avoidance by three orders of magnitude.

Advances in deep learning algorithms

The essence of the service robot "serving people" determines that the service robot will eventually develop in a humanized and intelligent direction. Current service robots face many bottlenecks in function, such as the inability to understand the complexity of human spoken language, and deep learning algorithms will change this situation. Deep learning algorithm makes the service robot no longer a "curing" tool through the imitation of the human brain neural network, but a thoughtful "secretary" who can think better, better understand human language, actions and intentions, and provide more Intimate service.

Advancement of positioning navigation algorithms

The primary problem facing service robots in real life is how to efficiently avoid obstacles. The Positioning Navigation Algorithm (SLAM) is the basis for the service robot to complete the path planning. By optimizing the algorithm, the service robot can better generate maps and plan routes in an unknown environment, so as to avoid obstacles safely and efficiently.

Since Google used the radar SLAM algorithm based on laser radar technology in driverless cars, the radar SLAM algorithm has attracted the attention of service robot enterprises. The algorithm has the advantages of small error, good directivity and high focusing, and will gradually become an industry in the future. The mainstream inside. At present, the company has already adopted the radar SLAM algorithm in its service robots.

On the whole, with the development of sensors and chips, the advancement of deep learning algorithms and SLAM algorithms, and the refinement of application fields, the service robot market will face a “big reshuffle”, and the service robot market will return to rationality and be more conducive to the market. Healthy development is also more conducive to bringing convenience to consumers.

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