A New Design Identification and Control Based on GA Optimization for An Autonomous Wheelchair

Abstract

The daily lifestyle of an average human has changed drastically. Robotics and AI systems are applied to many fields, including the medical field. An autonomous wheelchair that improves the degree of independence that a wheelchair user has can be a very useful contribution to society. This paper presents the design and implementation of an autonomous wheelchair that uses LIDAR to navigate and perform SLAM. It uses the ROS framework and allows the user to choose a goal position through a touchscreen or using deep learning-based voice recognition. It also presents a practical implementation of system identification and optimization of PID control gains, which are applied to the autonomous wheelchair robot. Input/output data were collected using Arduino, consisting of linear and angular speeds and wheel PWM signal commands, and several black-box models were developed to simulate the actual wheelchair setup. The best-identified model was the NLARX model, which had the highest square error (0.1259) among the other candidate models. In addition, using MATLAB, Optimal PID gains were obtained from the genetic algorithm. Performance on real hardware was evaluated and compared to the identified model response. The two responses were identical, except for some of the noise due to the encoder measurement errors and wheelchair vibration.

Visual Simultaneous Localization and Mapping Optimization Method Based on Object Detection in Dynamic Scene

“…This affects the accuracy of the SLAM algorithm [12]. As a result, studying SLAM algorithms in dynamic environments is very crucial [13,14].…”

Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle

“…𝑋 𝐹0 = 𝐿 𝑋 + (𝑈 𝑋 − 𝐿 𝑋 )𝑆 𝑅𝑅 (40) The third step investigates if Jt > PDIE then this patient is dead and generates a newly infected patient. In the case of Jt < PDIE then the newly infected patient will be as follows.…”

“…Due to its simplicity and ease of tuning, traditional PID controllers are frequently utilized in a variety of industrial applications. However, they do not guarantee desired dynamic performance and do not operate efficiently under a variety of operating situations [38]- [40]. Advanced control techniques such as adaptive control, variable structure control, fuzzy control, and neural networks can be used to solve this challenge [41].…”

Dual-Quaternion-Based SLERP MPC Local Controller for Safe Self-Driving of Robotic Wheelchairs

“…To address these concerns and enhance the quality of life for the aging population, robotic wheelchairs have emerged as a promising assistive innovation, offering potential solutions. While advancements in robotic wheelchair technology have been notable in recent years [4,5], ensuring the safety and autonomous operation of these devices remains a critical challenge. Enhancing wheelchair intelligence to minimize the reliance on manual control is key to improving the quality of life for the elderly who are experiencing mobility impairments.…”