Master–Slave Control System for Virtual–Physical Interactions Using Hands

• Published in: Sensors (Basel, Switzerland) Vol. 23; no. 16; p. 7107
• Main Authors: Liu, Siyuan, Sun, Chao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2023; MDPI
• Subjects: Algorithms; Analysis; Cameras; Control systems; Data collection; Design; Gloves; Hands; Kalman attitude fusion algorithm; master–slave control system; Motion capture; Multimedia industry; Protective clothing; Real time; Robotics; Sensors; Software; stable virtual grasping algorithm; Technology application; Virtual reality; virtual–physical interaction; Wearable computers
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s23167107

Among the existing technologies for hand protection, master–slave control technology has been extensively researched and applied within the field of safety engineering to mitigate the occurrence of safety incidents. However, it has been identified through research that traditional master–slave control technologies no longer meet current production and lifestyle needs, and they have even begun to pose new safety risks. To resolve the safety risks exposed by traditional master–slave control, this research fuses master–slave control technology for hands with virtual reality technology, and the design of a master–slave control system for hands based on virtual reality technology is investigated. This study aims to realize the design of a master–slave control system for virtual–physical interactions using hands that captures the position, orientation, and finger joint angles of the user’s hand in real time and synchronizes the motion of the slave interactive device with that of a virtual hand. With amplitude limiting, jitter elimination, and a complementary filtering algorithm, the original motion data collected by the designed glove are turned into a Kalman-filtering-algorithm-based driving database, which drives the synchronous interaction of the virtual hand and a mechanical hand. As for the experimental results, the output data for the roll, pitch, and yaw were in the stable ranges of −0.1° to 0.1°, −0.15° to 0.15°, and −0.15° to 0.15°, respectively, which met the accuracy requirements for the system’s operation under different conditions. More importantly, these data prove that, in terms of accuracy and denoising, the data-processing algorithm was relatively compatible with the hardware platform of the system. Based on the algorithm for the virtual–physical interaction model, the authors introduced the concept of an auxiliary hand into the research, put forward an algorithmic process and a judgement condition for the stable grasp of the virtual hand’s, and solved a model-penetrating problem while enhancing the immersive experience during virtual–physical interactions. In an interactive experiment, a dynamic accuracy test was run on the system. As shown by the experimental data and the interactive effect, the system was satisfactorily stable and interactive.