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@@ -28,6 28,6 @@ The VPE process involves the four main steps:
### Inertial fusion
We use an Extended Kalman Filter (EKF) to fuse the VPE estimates with the inertial data from the accelerometer and gyroscope, and refine the estimates in real-time using the Rauch-Tung-Striebel (RTS) algorithm. To account for time delay from the camera frames, we use a negative-time measurement update algorithm.
We use an Extended Kalman Filter (EKF) to fuse the VPE estimates with the inertial data from the accelerometer and gyroscope, and refine the estimates in real-time using the Rauch-Tung-Striebel (RTS) algorithm. To account for time delay from the camera frames, we use a negative-time measurement update algorithm. The EKF is implemented using NumPy and [Numba](https://numba.pydata.org/).
The use of inertial measurements dramatically reduces latency compared to a camera-only implementation, while also improving accuracy and report rate for fast movements.
