A Stereo Visual-Inertial Odometry Using Structural Lines for Localizing Indoor Wheeled Robots

This paper proposes an optimization-based stereo visual-inertial odometry (VIO) to locate indoor wheeled robots. Multiple Manhattan worlds assumption is adopted to model the interior environment. Instead of treating these worlds as isolated ones, we fuse the latest Manhattan world with the previous ones if they are in the same direction, reducing the calculated errors on the orientation of the latest Manhattan world. Then the structural lines which encode the orientation information of these worlds are taken as additional landmarks to improve positioning accuracy and reduce accumulated drift of the system, especially when the system is in a challenging environment (i.e., scenes with continuous turning and low textures). Besides, the structural lines are parameterized by only two variables, which improves the computational efficiency and simplifies the initialization of lines. Experiments on public benchmark datasets and in real-world environments demonstrate that the proposed VIO system can accurately position the wheeled robot in a complex indoor environment.

Implementasi Kendali Keseimbangan Gerak Two Wheels Self Balancing Robot Menggunakan Fuzzy Logic

Self balancing robot is a two-wheeled robot that only has two fulcrums so that this robot is an unbalanced system. Therefore, a control system that can maintain the stability of the robot is needed so that the robot can keep in standing position. This study aims to design a self-balancing robot and its control system which improves the robot's performance against the maximum angle of disturbance that can be overcome. The control system used is based on fuzzy logic with 9 membership functions and 81 rules. The control system is applied to the ESP-32 microcontroller with the MPU-6050 sensor as a feedback position of the robot and DC motor as an actuator. Complementary filters are added to the MPU-6050 sensor readings to reduce noise to obtain better robotic tilt angle readings. The improvement of this research compared to previous research based on fuzzy is the addition of the number of membership functions from 7 to 9 and the embedding of a complementary filter on the MPU-6050 sensor output reading. The result shows that the designed self balancing robot which has dimensions of 10cm x 18cm x 14.5cm can cope with the maximum disturbance angle up to 17.5⁰.

Advanced Proportional-Integral-Derivative Control Compensation Based on a Grey Estimated Model in Dynamic Balance of Single-Wheeled Robot

This paper aims to design a one-wheeled robot as regards its pitch freedom and balance control on the one hand and to assess the application feasibility of the GM (1,1) swing estimation controller on the other. System control focuses mainly on one-wheeled robot stability, body swings in position, and speed control. Mathematical modeling and GM (1,1) prediction control are under investigation. The mathematical modeling is firstly conducted through referencing to the Newtonian mechanics and the Lagrange equation, from which the robot transfer function and state-space differential equation are derived. Next, the linear quadratic regulator is applied as the control rule at the balance point. Applying GM (1,1) to assess the robot gyro signal at a dynamic state is a discussion. Next, model reference estimation control is processed, and a mathematical model of the balance control method is completed. Finally, a simulation is conducted to verify the feasibility of the GM (1,1) estimation reference model. The linear quadratic regulator, which is credited with tenacity, can provide pitch swing and balance control of the one-wheeled robot.

Obstacle Avoidance Control for Multisteering Mode of Multiaxle Wheeled Robot Based on Trajectory Prediction Strategy

A multiaxle wheeled robot is difficult to be controlled due to its long body and a large number of axles, especially for obstacle avoidance and steering in narrow space. To solve this problem, a multisteering mode control strategy based on front and rear virtual wheels is proposed, and the driving trajectory prediction of the multiaxle wheeled robot is analyzed. On this basis, an obstacle avoidance control strategy based on trajectory prediction is proposed. By calculating the relationship between the lidar points of the obstacle and the trajectory coverage area, the iterative calculation of the obstacle avoidance scheme for the proposed steering is carried out, and the feasible obstacle avoidance scheme is obtained. The mechanical structure, hardware, and software control system of a five-axle wheeled robot are designed. Finally, to verify the effectiveness of the obstacle avoidance strategy, a Z-shaped obstacle avoidance experiment was carried out. The results confirm the effectiveness of the proposed control strategy.

Embedding ROS and AI-Based Perception Capabilities in a Novel Low-Cost Assistive Robotic Platform

This paper describes how we developed a novel low-cost assistive robotic platform, with AI-based perception capabilities, able to navigate autonomously using Robot Operating System (ROS). The platform is a differential wheeled robot, equipped with two motors and encoders, which are controlled with an Arduino board. It also includes a Jetson Xavier processing board on which we deploy all AI processes, and the ROS architecture. As a result of the work, we have a fully functional platform, able to recognize actions online, and navigate autonomously through environments whose map has been preloaded.

Wheeled Robot Development for Obstruction Avoidance Mechanism

Consolidating the current improvement status of clever robots, impediment aversion and programmed following are the focal point of robot travel issues. In light of the improvement status of homegrown clever control frameworks, current innovation, and so on, this paper utilizes Arduino as the centre control framework, joined with an infrared following module. Four modules, for example, ultrasonic impediment aversion module, engine drive module and force module have planned a decent control conspire, accordingly understanding the insightful following and hindrance evasion capacity of the wheeled robot. Keywords: Arduino, Wheel robot, Tracking, Obstacle Avoidance