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Novosibirsk State University (Russia) has developed and patented an autonomous mobile robotic platform based on artificial intelligence for year-round scavenging the streets, footpaths and lawns from leaves and garbage as well as shoveling snow away. The robots are highly manoeuvrable, can work autonomously at any time of a day, year, in any terrain, in any weather conditions and when any obstacles appear. The university is looking for partners for commercial and licensing agreements
Currently, large and bulky equipment is used to scavenge the streets, footpaths and courtyards from dirt and refuse and for removing snow from the streets, while manual scavenging requires a lot of labour. Existing robotic systems for street and lawn scavenging often need an operator to handle them. They have poor manoeuvrability, cannot deal with new obstacles. They also often require additional equipment such as positioning controllers or they use complex and expensive satellite positioning systems. Moreover there are mostly industrial robots which are being developed in the world, while non-industrial robotics is very underdeveloped.
The university from Russia has developed and patented an autonomous mobile robotic platform with the use of artificial intelligence technologies for scavenging the streets and lawns of dirt and garbage in summer and for shoveling the snow away in winter. The platform consists of a self-propelled wheeled vehicle with a battery, motor-wheels and a bucket. The platform is also equipped with a control unit, a computer with internal memory to which ultrasonic location sensor, video cameras, encoders, reed switches are connected, it has a self-recharging system, computer vision and image recognition, infrared sensors, microcontrollers. The platform can also be equipped with multiple autonomous engines.
The mobile autonomous robot will fully automate scavenging of small areas, parking lots, pavements, street and lawns and for shoveling the snow away even during moderate snowfalls. It can be used to scavenge the grounds of apartment buildings or private residences from dirt and refuse as well.
The main innovative aspect of the robotic platform is the use of deep machine learning and neural network technologies to enable the robot to recognize the environment it must work in as well as any changes in it and also recognize power sockets to recharge itself by plugging to them.
The advantages of the developed robotic platform include:
- high manoeuvrability, enabling it to scavenge even small areas from garbage and shovel the snow away from constrained spaces;
- the ability to work day and night with the same efficiency;
- the use of interchangeable equipment and attachments for summer and winter conditions;
- independent recharging of the robot from available on-site electric power sources;
- the possibility of working in fully autonomous mode, as well as in the operator's handled mode;
- the possibility of building an optimum route;
- the possibility of additional development of a self-diagnostic system for the robot.
The university may sign commercial agreements with technical assistance to manufacture and supply robotic equipment to partners, and may also enter into licensing agreements to transfer the rights to manufacture, sell and use the robotic systems.
Intellectual property status
Granted Patent
Patent number :
Where : Russia
Current development status
Working prototypes
Desired business relationship
Patent licensing
New technology applications
Adaptation of technology to other markets
https://english.nsu.ru/
Novosibirsk State University is located in the worldwide famous scientific center – Akademgorodok. 80% of NSU faculty members are scientists from the Siberian Branch of the Russian Academy of Sciences. So education is carried out in close cooperation with the world-class science and R&D.
We represent the Center for Technology Transfer and Commercialization of Novosibirsk State University.
Our objective is to audit technologies developed by university teams and laboratories, prepare technologies with commercialization potential for technology transfer, initiate contacts with prospective partners.
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