Short Title: Int. J. Mech. Eng. Robot. Res.
Frequency: Bimonthly
Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
2024-06-06
2024-09-03
2024-07-09
Abstract—This paper introduces a Two-Wheeled Self-Balancing Robot (TWSBR) which is controlled to avoid obstacles. The TWSBR is a type of the inverted pendulum and is treated as an inherently unstable nonlinear system. Therefore, a continuous appropriate control is required to maintain the inverted state. The TWSBR consists of two DC motors with encoders and 6-axis sensor (accelerometer and gyroscope). All peripherals are connected to a 32-bit RISC-V soft microprocessor implemented on an FPGA, and all control circuits for the peripherals are also implemented on the same FPGA. An attitude control system of the TWSBR is provided through 3 Proportional-Integral- Differential (PID) controllers with a sensor fusion-based on a Kalman Filter, which is implemented on the 32-bit RISC-V soft microprocessor. The obstacle avoidance system of the TWSBR is based on a fuzzy control using multiple ultrasonic sensors. The 32-bit RISC-V soft microprocessor includes a 32-bit fixed-point (Q16.16) arithmetic instructions of addition, subtraction, multiplication, maximum and minimum as a custom instruction set architecture (ISA) extensions for calculation of a speed improvement. The software program is written in C language and compiled by the GNU GCC cross-compiler for the RISC-V ISA. Index Terms—Two-Wheeled Self-Balancing Robot (TWSBR), MPU-6500, Kalman Filter, PID controller, fuzzy controller, obstacle avoidance, RISC-V, fixed-point arithmetic Cite: Ryuichi Tsutada, Trong-Thuc Hoang, and Cong-Kha Pham, "An Obstacle Avoidance Two-Wheeled Self-Balancing Robot," International Journal of Mechanical Engineering and Robotics Research, Vol. 11, No. 1, pp. 1-7, January 2022. DOI: 10.18178/ijmerr.11.1.1-7 Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.