DEVELOPMENT OF INTELLIGENT SELF-BALANCING E-BIKE USING MACHINE LEARNING

The self-driving autonomous cars is becoming an increasingly popular concept all around the world butthe area of self-driving two wheelers is still under developed. For developing countries like India, two wheelers areaffordable than cars for most of the population. The project aims at developing intelligent self-balancing bike usingartificial intelligence because the major problem in developing an autonomous bike is in the area of balancing. Eventhough there are many working mechanisms available for self-balancing of bike, the implementation of AI will be anedge over others from the point of computational power requirement and the programming complexity incurred.A prototype of the bike was developed with reaction wheel mechanism for self-balancing. The mechanism was fullycontrolled by AI by preventing the need of explicit programming for balancing which was the earlier technique used inself-balancing bike. Reinforcement learning, a type of machine learning technique is adopted for this purpose. The policygradient algorithm was used to make the bike learn by itself for balancing. Even though the AI algorithm worked well inthe virtual environment (balancing a cart-pole) it fails in the real environment. (i.e. it fails to balance the bike). It isbecause of the noisy data from the sensor, which gives inaccurate information about the orientation of the bike. The noisein the data is due to the vibration of the body when the reaction wheel rotates. This could be solved if the AI is fed withaccurate information about the orientation of the vehicle.