Rotary Encoder Based Self-Positioning Method for Mobile Robot

In this paper, we present a mobile robot self-positioning method based on a rotary encoder. Firstly, we analyze the wheel speed information about the robot by using the rotary encoder. Secondly, we use the micro-offset accumulation-based trace estimation algorithm to measure the distance and direction deviation information of the current robot relative to the start position. Finally, we apply the error correction method to reduce the excessive self-positioning deviation caused by accumulated errors to achieve the mobile robot self-positioning. The experiments show that the proposed self-positioning method can achieve high accuracy under the effect of the error correction method, and it has a certain degree of robustness.

I. Introduction

Artificial intelligence (AI) is one of the biggest technologies of the 21st century and has evolved from academic research to become one of the biggest drivers of business today. Recently, more and more countries have released a strategic plan for AI research. The AI field draws upon many research theories, including computer science, mathematics, psychology, linguistics, philosophy and so on. AI has been used to develop and advance many fields and industries, such as finance, healthcare, education, and transportation.