Private Bee 3D GPS - Revision history

Wiki.admin at 18:14, 22 December 2024

2024-12-22T18:14:57Z

Wiki.admin at 13:52, 29 September 2023

2023-09-29T13:52:59Z

Wiki.admin at 11:06, 29 September 2023

2023-09-29T11:06:51Z

Wiki.admin: /* Path Flight Optimization */

2023-09-25T22:12:22Z

Path Flight Optimization

Wiki.admin at 22:10, 25 September 2023

2023-09-25T22:10:16Z

Wiki.admin at 13:19, 25 September 2023

2023-09-25T13:19:39Z

Wiki.admin at 08:38, 25 June 2021

2021-06-25T08:38:28Z

Wiki.admin at 08:36, 25 June 2021

2021-06-25T08:36:30Z

Wiki.admin at 08:35, 25 June 2021

2021-06-25T08:35:07Z

Wiki.admin at 08:33, 25 June 2021

2021-06-25T08:33:45Z

← Older revision		Revision as of 18:14, 22 December 2024
Line 64:		Line 64:
	Our primary objective was to develop a Hybrid VTOL (Vertical Take-Off and Landing) aircraft with a specific focus on its application as a flying ambulance. This project aimed to navigate optimally in a complex 3D environment from point S to F.		Our primary objective was to develop a Hybrid VTOL (Vertical Take-Off and Landing) aircraft with a specific focus on its application as a flying ambulance. This project aimed to navigate optimally in a complex 3D environment from point S to F.

−	~~Key Features~~

−	~~3D collaborative GPS system.~~
−	~~Advanced obstacle avoidance capabilities, considering both static and dynamic objects.~~
−	~~Integration of meteorological constraints into the flight model.~~
−	~~Minimization of fuel consumption and flight time.~~
−	~~Methodology~~
−	~~The project's methodology included:~~
−
−	~~Physical modeling, utilizing control inputs for thrust and angular velocity to define state equations.~~
−	~~A cost function that combined flight time and fuel consumption for optimization.~~
−	~~Comprehensive constraints, covering end-to-end states, control bounds, and obstacle avoidance.~~
−	~~Optimization Techniques~~
−	We explored a range of optimization techniques, including Generalized LQR, Approximate Dynamic Programming, Finite Elements, and Pseudospectral methods. Ultimately, the Legendre Pseudospectral method was selected for resolution due to its proven convergence.
−
−	~~Resolution~~
−	~~To solve the nonlinear optimization problem, we employed the Legendre Pseudospectral method, transforming it into a finite-dimensional problem using polynomial basis functions.~~
−
−	~~Challenges~~
−	~~The project was not without its challenges, particularly in managing complex flight parameter constraints and ensuring real-time collaboration for efficient flight management.~~
−
−	~~Applications~~
−	While initially designed for use in flying ambulance services, the insights and technology developed in this project hold broader applications in the field of aerial navigation. These extend to drone routing, search and rescue operations, and beyond.
−
−	This summary underscores the project's alignment with existing optimization concerns in supply chain management and various industrial applications, especially in navigating intricate constraint environments.

	[[Category:Private Bee 3D GPS]]		[[Category:Private Bee 3D GPS]]

← Older revision		Revision as of 13:52, 29 September 2023
Line 53:		Line 53:
	[[File:Rapport Bee-plane.pdf]]		[[File:Rapport Bee-plane.pdf]]

		+	== Presentation of 3D GPS Flight Optimization Project ==

		+	In our relentless pursuit of cutting-edge aviation technology, we present the remarkable work accomplished in the realm of 3D GPS flight optimization, specifically designed to calculate an optimized flight path using artificial intelligence (AI).
		+
		+	=== Path Flight Optimization ===
		+	Presentation: [[File:BELMANT-CLERC-DIAPORAMA.pdf]]
		+	Final Report: [[File:Insa minibee gps final.pdf]]
		+
		+	Objectives
		+	Our primary objective was to develop a Hybrid VTOL (Vertical Take-Off and Landing) aircraft with a specific focus on its application as a flying ambulance. This project aimed to navigate optimally in a complex 3D environment from point S to F.
		+
		+	Key Features
		+
		+	3D collaborative GPS system.
		+	Advanced obstacle avoidance capabilities, considering both static and dynamic objects.
		+	Integration of meteorological constraints into the flight model.
		+	Minimization of fuel consumption and flight time.
		+	Methodology
		+	The project's methodology included:
		+
		+	Physical modeling, utilizing control inputs for thrust and angular velocity to define state equations.
		+	A cost function that combined flight time and fuel consumption for optimization.
		+	Comprehensive constraints, covering end-to-end states, control bounds, and obstacle avoidance.
		+	Optimization Techniques
		+	We explored a range of optimization techniques, including Generalized LQR, Approximate Dynamic Programming, Finite Elements, and Pseudospectral methods. Ultimately, the Legendre Pseudospectral method was selected for resolution due to its proven convergence.
		+
		+	Resolution
		+	To solve the nonlinear optimization problem, we employed the Legendre Pseudospectral method, transforming it into a finite-dimensional problem using polynomial basis functions.
		+
		+	Challenges
		+	The project was not without its challenges, particularly in managing complex flight parameter constraints and ensuring real-time collaboration for efficient flight management.
		+
		+	Applications
		+	While initially designed for use in flying ambulance services, the insights and technology developed in this project hold broader applications in the field of aerial navigation. These extend to drone routing, search and rescue operations, and beyond.
		+
		+	This summary underscores the project's alignment with existing optimization concerns in supply chain management and various industrial applications, especially in navigating intricate constraint environments.

	[[Category:Private Bee 3D GPS]]		[[Category:Private Bee 3D GPS]]

← Older revision		Revision as of 11:06, 29 September 2023
Line 52:		Line 52:
	* Aircraft takeoff<BR>		* Aircraft takeoff<BR>
	[[File:Rapport Bee-plane.pdf]]		[[File:Rapport Bee-plane.pdf]]
		+
		+
		+
		+	[[Category:Private Bee 3D GPS]]

@@ Line 6: / Line 6: @@
 == Path Flight Optimization ==
 [[File:BELMANT-CLERC-DIAPORAMA.pdf]]
 Objectives
@@ Line 33: / Line 39: @@
 Applicable to broader range of aerial navigation tasks, such as drone routing, search and rescue.
 This summary aligns well with existing optimization concerns in supply chain management and other industrial applications, particularly in navigating complex constraint environments.
 == 3D GPS ==

@@ Line 18: / Line 18: @@
 Methodology
 Physical Modeling: Uses control inputs for thrust and angular velocity to define state equations
-�
+Cost Function: Linear combination of flight time and fuel consumption for optimization.
 Constraints: Involves end-to-end states, control bounds, and obstacle avoidance.
 Optimization Techniques

@@ Line 5: / Line 5: @@
-* Path Flight Optimization
+== Path Flight Optimization ==
 [[File:BELMANT-CLERC-DIAPORAMA.pdf]]
-* 3D GPS
 [[File:Présentation 14 03 2019.pdf]]

← Older revision		Revision as of 08:38, 25 June 2021
Line 1:		Line 1:
	Presentation of work done for a 3D GPS		Presentation of work done for a 3D GPS
		+
		+	Project is to calculate an optimized flight path with IA.
		+

← Older revision		Revision as of 08:36, 25 June 2021
Line 1:		Line 1:
	Presentation of work done for a 3D GPS		Presentation of work done for a 3D GPS

		+
		+	* Path Flight Optimization
		+	[[File:BELMANT-CLERC-DIAPORAMA.pdf]]

← Older revision	Revision as of 08:35, 25 June 2021
Line 3:	Line 3:


	+	* 3D GPS
	+	[[File:Présentation 14 03 2019.pdf]]

@@ Line 8: / Line 8: @@
 * Aircraft parametrical configuration<BR>
 [[File:TMO02.pdf]]
 * Aircraft takeoff<BR>
 [[File:Rapport Bee-plane.pdf]]