Researchers have developed a new robust motion control system for ballbots, which are highly mobile robotic systems that can navigate in all directions. Traditional control methods, such as PID controllers, often struggle in maintaining stability and balance. The study, led by Dr. Van-Truong Nguyen, introduces an innovative proportional integral derivative (PID) controller that combines with radial basis function neural networks. This integrated approach addresses the challenges faced by ballbots, making it suitable for applications in service, assistive, and delivery robots. The findings were released online on December 4, 2024, and published in January 2025.
Controlling a ballbot's movement is challenging due to its unique mobility; this study proposes a PID controller integrated with a radial basis function neural network for robust motion control.
Traditional PID controllers struggle with maintaining balance in ballbots, leading to the need for an advanced controller that combines PID's simplicity with the adaptability of neural networks.
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