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Every year, millions of workers worldwide suffer from workplace injuries. Work-related musculoskeletal disorders are a group of injuries that can affect any part of the body due to frequent lifting of heavy objects or performing repetitive forceful tasks. To address this issue, robotic arms can function as assistants in shared workplaces to limit manual handling and enhance the ergonomics of manual tasks, thereby minimizing the need for humans to work in hazardous environments. The hand gesture-controlled robotic (ARMO) involves developing a robotic arm that can be controlled using human hand gestures. The robotic arm will mimic the motion of a human hand with the help of latest technology in computer vision and artificial intelligence. The proposed ARMO is tested on a PC and servos. Smart hand gesture detection model is proposed for fast and smooth real-time response time, making the arm more suitable for work requirements. Moreover, a control system is developed to map servo motors to the robotic arm, allowing users to effortlessly control its movements with their hands. The findings indicate that the proposed ARMO decreases the processing load by 70.7% and achieves 75.8% speed up in the system performance, without compromising the core gesture recognition capability.
El‐Moursy et al. (Sat,) studied this question.