Design And Implementation Of Bio-Robot Scientific Research Assistant System

Bio-robot is a new type of robot that realizes the integration of robot brain and biological brain through microelectronics technology,computer network technology,artificial intelligence technology,etc.Its research can help better understand brain science and behavior control science,thus revealing the working mechanism of brain,which has great value in the fields of medicine,biology,military,disease rehabilitation and so on.Compared with traditional robots,bio-robot have strong autonomous consciousness,as well as advantages in motion flexibility,rapid response,energy sustainability and self-concealment,so the research on bio-robot has become a hot spot in current scientific research institutions.Through research,domestic current lack of a collection of neural signal acquisition,multi-channel dynamic waveform display,import neural signal algorithm analysis and experimental data management,remote control,behavior training,test,evaluation of the basic subjects such as scientific research system,thus developing an auxiliary system can help researchers on the study of bio-robot more efficient.The bio-robot research assistance system established in this paper can meet the current conditions for domestic research institutions to assist research on bio-robots.Based on the basic needs of domestic bio-robot research,complete the overall design and implementation of the assistance system.Macroscopically,the architecture design of the three-layer model was built,and the whole system was divided into interface display layer,business logic layer and data access layer,and the functional design of each layer was described in detail.C# was used to write software functions and interact with the underlying C language and JavaScript language for data.Micro,according to the specific design scheme of the assistance system,complete the function development of the assistance system,including user management and user security,multi-channel neural signal real-time acquisition,multi-channel waveform sparse display,single-channel waveform fine display,neural signal data storage,historical data display,GPRS-based UDP/TCP remote control network construction,motion track tracking,attitude display,motion height display,behavior instruction trigger,control mode switching,map coordinate extraction,test data management,offline backpack data reading and display,test sample evaluation,behavior training and video monitoring and other contents.In view of the key technical difficulties in the system implementation,such as multi-channel data thinning,single-channel data refinement,data splicing processing,and multi-language interaction,solutions are presented and implemented.In the actual test,pigeons were used as subjects.Through multiple tests,the platform runs well and can meet the overall design requirements.Combined with hardware devices to complete the test of the whole system and deliver a third party to use.