Systems and methods for augmented reality
Systems and methods for reducing error from noisy data received from a high frequency sensor by fusing received input with data received from a low frequency sensor by collecting a first set of dynamic inputs from the high frequency sensor, collecting a correction input point from the low frequency sensor, and adjusting a propagation path of a second set of dynamic inputs from the high frequency sensor based on the correction input point either by full translation to the correction input point or dampened approach towards the correction input point.
1. A method comprising:
collecting a first set of dynamic inputs from at least one first sensor at a first frequency;
collecting a correction input point from at least one second sensor at a second frequency and with latency relative to the collection of the first set of dynamic inputs;
collecting a second set of dynamic inputs from the at least one first sensor at the first frequency; and
adjusting a propagation path of the second set of dynamic inputs based on the correction input point and the latency.
2. The method of claim 1 , wherein the second frequency is lower than the first frequency.
3. The method of claim 1 , wherein adjusting the propagation path comprising originating the propagation path from the correction input point.
4. The method of claim 1 , wherein adjusting the propagation path comprising adjusting a rate of change of the propagation path based on weighted average time domain adjustments.
5. The method of claim 4 , wherein the rate of change of the propagation path is adjusted by applying a coefficient to an extended Kalman filter accepting the second set of dynamic inputs.
6. The method of claim 1 , wherein adjusting the propagation path comprising originating the propagation path from the correction input point and the latency.
7. The method of claim 1 , wherein adjusting the propagation path comprising adjusting a rate of change of the propagation path based on weighted average time domain adjustments and the latency.
8. The method of claim 7 , wherein the rate of change of the propagation path bed on the latency is adjusted by applying a coefficient to an extended Kalman filter accepting the second set of dynamic inputs.
9. An visualization reality system:
a first sensor positioned to collect a first set of dynamic inputs from at a first frequency;
a second sensor positioned to collect a correction input point at a second frequency and with latency relative to the collection of the first set of dynamic inputs,
wherein the first sensor positioned to collect a second set of dynamic inputs at the first frequency; and
a fusion system connected to the first and second sensors and to adjust a propagation path of the second set of dynamic inputs based on the correction input point and the latency.