Basic Proposal on Position Estimation with Small Calculation Amount using a Velocity Sensor for Mini4WD Speed Control

Abstract

In the Mini4WD-AI, a non-powerful microcontroller executes the processes of sensor measurement, self-position estimation, and speed control during high-speed laps. Among these, self-position estimation is quite computationally intensive and memory-intensive, making it very difficult to obtain the estimation results online. Standard inertial sensor values contain a large amount of noise. When using them as material for self-position estimation, appropriate design is required for similarity tolerance and filter processing. Since the increase in computational complexity makes it difficult to obtain results online, only sensor threshold processing and short-time running history information can be used for speed control, which requires a high response. Therefore, we propose a one-dimensional motion and inertial information that does not depend on running speed. We also propose a simple map representation and a computationally inexpensive position estimation method. We verify the effectiveness of the method on actual vehicles using a variety of driving data.