Advancing Assistive Mobility: A ROS-Powered Autonomous Wheelchair with Dynamic Posture Intelligence
Keywords:
Assistive Technology, Autonomous Navigation, Multi-Posture Wheelchair, Robot Operating System (ROS), RoboticsAbstract
This paper presents the design, implementation, and testing of a ROS-powered multi-posture transformation wheelchair integrating autonomous navigation and dynamic seating adjustment. Addressing limitations of traditional wheelchairs in adaptability, comfort, and navigation, the system combines a modular 6063-T5 aluminium frame, custom linear actuators for sitting, relaxing, and bed configurations, and a rear-wheel drive mechanism with high-torque brushless DC motors. The software stack, based on ROS Melodic, incorporates LIDAR-based SLAM for mapping and obstacle avoidance, a navigation stack for path planning, and an ESP32-enabled smartphone interface for manual control. Structural testing validated the frame under a 981 N load, while posture transformation trials confirmed reliable operation with minor jerkiness at transition points. Navigation experiments demonstrated efficient path generation from multiple start positions in controlled environments, with limitations observed in dynamic, cluttered spaces. The remote-control interface was intuitive, though occasional latency was noted. Identified areas for improvement include navigation robustness in dynamic settings, targeted structural reinforcement, refined motion profiles for actuators, and optimized wireless communication. Future enhancements will focus on sensor fusion, advanced SLAM algorithms, adaptive motor control via machine learning, and extended real-world trials. The results establish a foundation for next-generation, user-centric mobility solutions that integrate intelligent navigation with customizable posture control to enhance independence and health outcomes.
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