Altitude estimation using differential pressure sensors in ground effect
A plurality of sensor datasets is received including: (1) an interference sensor dataset which is associated with interference between airflow from a first rotor in a multicopter and airflow from a second rotor in the multicopter, (2) a first and a second isolated sensor dataset which are associated with isolated airflows from the first rotor and the second rotor, respectively. A generalized flow model associated with a generalized rotor is received and an altitude for the multicopter is generated based at least in part on the plurality of sensor datasets and the generalized flow model, including by using a non-linear filter that builds a consolidated probability function associated with altitude that reconciles the plurality of sensor datasets with the generalized flow model.
1. A system, comprising:
a processor which is configured to:
receive a plurality of sensor datasets including: (1) an interference sensor dataset which is associated with interference between airflow from a first rotor in a multicopter and airflow from a second rotor in the multicopter, (2) a first and a second isolated sensor dataset which are associated with isolated airflows from the first rotor and the second rotor, respectively;
receive a generalized flow model associated with a generalized rotor; and
generate an altitude for the multicopter based at least in part on the plurality of sensor datasets and the generalized flow model, including by using a non-linear filter that builds a consolidated probability function associated with altitude that reconciles the plurality of sensor datasets with the generalized flow model;
the first rotor;
the second rotor;
a plurality of sensors which is configured to output the interference sensor dataset, the first isolated sensor dataset, and the second isolated sensor dataset; and
storage which is configured to store the generalized flow model.
2. The system of claim 1 , wherein the non-linear filter includes one or more of the following: a non-linear Bayesian filter or a grid-based recursive Bayesian filter.
3. The system of claim 1 , wherein the plurality of sensor datasets excludes sensor data associated with a rotor that is surrounded such that the altitude generated is not based on the sensor data from the surrounded rotor.
4. The system of claim 1 , wherein:
the plurality of sensor datasets excludes sensor data associated with a rotor that is surrounded such that the altitude generated is not based on the sensor data from the surrounded rotor; and
the surrounded rotor is surrounded by a plurality of rotors and a fuselage.
5. The system of claim 1 , wherein:
the plurality of sensor datasets excludes sensor data associated with a rotor that is surrounded such that the altitude generated is not based on the sensor data from the surrounded rotor; and
the surrounded rotor overlaps with at least one other rotor.
6. The system of claim 1 , wherein in the event the multicopter's rotors are symmetric and the multicopter's attitude does not exceed a threshold, only half of the generalized flow model, a first half, is generated and the other half of the generalized flow model, a second half, uses values of the first half of the generalized flow model.
7. The system of claim 1 , wherein:
in the event the multicopter's rotors are symmetric and the multicopter's attitude does not exceed a threshold, a first half of the generalized flow model is generated and a second half of the generalized flow model uses values of the first half of the generalized flow model; and
during at least one iteration, the entirety of the generalized flow model is calculated even if the multicopter's attitude does not exceed the threshold.
8. A method, comprising:
receiving a plurality of sensor datasets including: (1) an interference sensor dataset which is associated with interference between airflow from a first rotor in a multicopter and airflow from a second rotor in the multicopter, (2) a first and a second isolated sensor dataset which are associated with isolated airflows from the first rotor and the second rotor, respectively;
receiving a generalized flow model associated with a generalized rotor; and
generating an altitude for the multicopter based at least in part on the plurality of sensor datasets and the generalized flow model, including by using a non-linear filter that builds a consolidated probability function associated with altitude that reconciles the plurality of sensor datasets with the generalized flow model.
9. The method of claim 8 , wherein the non-linear filter includes one or more of the following: a non-linear Bayesian filter or a grid-based recursive Bayesian filter.
10. The method of claim 8 , wherein the plurality of sensor datasets excludes sensor data associated with a rotor that is surrounded such that the altitude generated is not based on the sensor data from the surrounded rotor.
11. The method of claim 8 , wherein:
the plurality of sensor datasets excludes sensor data associated with a rotor that is surrounded such that the altitude generated is not based on the sensor data from the surrounded rotor; and
the surrounded rotor is surrounded by a plurality of rotors and a fuselage.
12. The method of claim 8 , wherein:
the plurality of sensor datasets excludes sensor data associated with a rotor that is surrounded such that the altitude generated is not based on the sensor data from the surrounded rotor; and
the surrounded rotor overlaps with at least one other rotor.
13. The method of claim 8 , wherein in the event the multicopter's rotors are symmetric and the multicopter's attitude does not exceed a threshold, only half of the generalized flow model, a first half, is generated and the other half of the generalized flow model, a second half, uses values of the first half of the generalized flow model.
14. The method of claim 8 , wherein:
in the event the multicopter's rotors are symmetric and the multicopter's attitude does not exceed a threshold, a first half of the generalized flow model is generated and a second half of the generalized flow model uses values of the first half of the generalized flow model; and
during at least one iteration, the entirety of the generalized flow model is calculated even if the multicopter's attitude does not exceed the threshold.
15. A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
receiving a plurality of sensor datasets including: (1) an interference sensor dataset which is associated with interference between airflow from a first rotor in a multicopter and airflow from a second rotor in the multicopter, (2) a first and a second isolated sensor dataset which are associated with isolated airflows from the first rotor and the second rotor, respectively;
receiving a generalized flow model associated with a generalized rotor; and
generating an altitude for the multicopter based at least in part on the plurality of sensor datasets and the generalized flow model, including by using a non-linear filter that builds a consolidated probability function associated with altitude that reconciles the plurality of sensor datasets with the generalized flow model.