AmanTifli/IMU_IR_Motion_Capture_Teleoperation

This project is a personal thesis repository with zero traction (0 stars, 0 forks) and no active development since its creation. While the technical approach of fusing IR and IMU data is sound for academic research, it represents a 'reimplementation' of existing sensor fusion techniques applied to a specific hardware setup. From a competitive standpoint, it lacks any moat; it is highly reproducible for any robotics engineer. In the broader market, hardware-intensive teleoperation (requiring IR markers and IMUs) is being rapidly displaced by computer-vision-only approaches (e.g., MediaPipe, Move.ai) or commodity XR hardware (Meta Quest 3, Apple Vision Pro) which provide hand and body tracking out-of-the-box. The 'defensibility' is low because there is no community, proprietary dataset, or unique algorithmic breakthrough. Frontier labs are unlikely to build this specific niche hybrid, but the problem it solves (robot control) is being addressed by much more scalable vision-foundation models. It serves as a solid reference implementation for students but has no commercial or infrastructure-grade viability in its current state.