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Navigation of Self-Balancing Mobile Robot through Sensors

机译：通过传感器导航自平衡移动机器人

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The aim of this paper is the design, simulation, construction and programming of a self-balancing (inverted pendulum) mobile robot, capable of obstacle avoidance through the MPU6050 sensor, and ultrasonic sensor. The robot will only use a MPU6050 sensor for evaluating and navigating the terrain, a triple axis accelerometer and gyro for calculating angular velocities and accelerations, and Arduino. The design of the robot is performed in CAD-Inventor and Fusion360. The simulation is done mainly on Matlab. The mechanical parts have been printed at the 3D printer that we developed at our university. The modeling of the robot is performed using the inverted pendulum as a reference and a space state model of the robot is generated. This comes as a natural requirement in order to use the Linear Quadratic Regulator and Kalman filter, as the main process controller of this system. The required states are obtained by processing the MPU6050 sensor. This information is used to calculate the feedback controller gains, in order to have an overall better system response. The application of the algorithm after some of the examinations made has shown precision in detecting objects and finding the path for the fastest time.
机译：本文的目的是设计，仿真，构造和编程自平衡（倒摆）移动机器人，该机器人能够通过MPU6050传感器和超声波传感器避开障碍物。该机器人将仅使用MPU6050传感器评估和导航地形，使用三轴加速度计和陀螺仪计算角速度和加速度，以及使用Arduino。机器人的设计在CAD-Inventor和Fusion360中进行。仿真主要在Matlab上完成。机械零件已在我们大学开发的3D打印机上打印。使用倒立摆作为参考进行机器人的建模，并生成机器人的空间状态模型。为了使用线性二次调节器和卡尔曼滤波器作为该系统的主要过程控制器，这是很自然的要求。通过处理MPU6050传感器可以获得所需的状态。该信息用于计算反馈控制器的增益，以便获得总体上更好的系统响应。经过一些检查后，该算法的应用已显示出在检测物体和找到最快路径上的精度。

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