WP4-16
| ID | WP4-16 |
| Contributor | ACORDE |
| Levels | Platform, Function |
| Require | GLAD+ platform WP3-15_2 |
| Provide | Navigation data (position, attitude, velocity) |
| Input | Raw sensed data from multi-constellation GNSS receivers, gyroscope and accelerometer data, barometer data |
| Output | Position, Attitude, Velocity |
| C4D building block | |
| TRL | 4 |
| Parent Building block | WP3-15_2 |
| Contact | fernando.herrera at acorde.com |
This page describes the algorithmc improvements brought to GLAD+ by ACORDE in COMP4DRONES, taking as baseline, its outdoor geo-referenced position&attitude system GLAD+.
Description
In WP4 of COMP4DRONES, ACORDE has tackled the enhancement of the navigation software of its low-cost outdoor geo-referenced position and attitude estimation system GLAD+ WP3-15_2.
One aspect of the navigation software enhancement tackled by ACORDE has been the exploitation of the novel low-cost receivers integrated in the HW platform developed in COMP4DRONES. The new receivers enable low-cost multi-constellation data, which need to be integrated and exploited in the navigation algorithm. These receivers also enable specific reactive security features, an aspect also addressed in C4D and further explained in WP5-11_ACO.
Another aspect addressed in the context of WP4 is an analysis to assess if state-of-the-art deep learning methodologies might provide feasible and advantageous solutions for embedded targets. Specifically, the possibility to enhance a currently heuristic functionality integrated on the multi-baseline attitude estimation algorithm of GLAD+ was assessed.
Last, but not least, in the framework of WP4, ACORDE has also provided a "Mavlink interface" to ease SW, and therefore GLAD+ system integration.
Improvements
The following figures show GLAD+ position output (blue) vs RTK-postprocesed output (green) in one flight test performed in COMP4DRONES in a case where GLAD+ is configured to use only GPS, and in another case where GLAD+ is confiured to use multiconstellation (both GPS and Galileo).
- Accuracy improvement with Multi-Constellation (GPS-Galileo) in one flight test performed in COMP4DRONES
Only GPS
Multiconstellation (GPS-GAL)
Validation
The validation of the improved navigation software has been done relying on raw data captured with the support of FADA-CATEC, drone integrator&operator partner in Use Case 2 of COMP4DRONES.
- Validation of the software development has been done from GPS-Galileo) raw data caputred in real flight tests
Drone used for the flight tests
Outdoor location where the flight tests where performed
