Design of a low-cost optical motion capture system using a multi-camera configuration and an asynchronous extended Kalman filter

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Motion capture technology, with its vast applications in robotics, control systems, and biomedical engineering, is highly sought after for its ability to provide precise pose estimation. However, the high cost of commercial motion capture devices can place them out of reach for many smaller institutions and businesses. This paper presents the development of a low-cost, optical motion capture system using a multi-camera setup and a novel algorithm that embeds the camera model within an extended Kalman filter for precise tracking of a robot's pose. Initial simulations in MATLAB, enhanced with real-world experiments, showcase the system’s capability to track predefined features on a rigid-body robot using affordable cameras. Results highlight the challenges of balancing cost with performance; the system can achieve a position and orientation accuracy of less than 1 cm and 2°, respectively, within a 2x2x2m workspace, at a significantly lower cost compared to off-the-shelf commercial systems. The implications of this research are broad, offering a foundation for future explorations into cost- effective motion capture solutions. The current work is completely opensource and offered as an invitation to share and collaborate with other institutes of interest.