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.
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
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