Difference between revisions of "Private Bee 3D GPS"
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| − | + | == Path Flight Optimization == | |
[[File:BELMANT-CLERC-DIAPORAMA.pdf]] | [[File:BELMANT-CLERC-DIAPORAMA.pdf]] | ||
| + | Objectives | ||
| + | Develop a Hybrid VTOL (Vertical Take-Off and Landing) aircraft for flying ambulance applications. | ||
| + | Navigate optimally in a 3D environment from point S to F. | ||
| + | Key Features | ||
| + | 3D collaborative GPS system. | ||
| + | Obstacle avoidance, accounting for static and dynamic objects. | ||
| + | Meteorological constraints integrated into the flight model. | ||
| + | Fuel consumption and flight time minimization. | ||
| + | Methodology | ||
| + | Physical Modeling: Uses control inputs for thrust and angular velocity to define state equations | ||
| + | � | ||
| + | ′ | ||
| + | ( | ||
| + | � | ||
| + | ) | ||
| + | = | ||
| + | � | ||
| + | ( | ||
| + | � | ||
| + | ( | ||
| + | � | ||
| + | ) | ||
| + | , | ||
| + | � | ||
| + | ( | ||
| + | � | ||
| + | ) | ||
| + | ) | ||
| + | X | ||
| + | ′ | ||
| + | (t)=F(X(t),U(t)). | ||
| + | Cost Function: Linear combination of flight time and fuel consumption ( | ||
| + | � | ||
| + | ( | ||
| + | � | ||
| + | , | ||
| + | � | ||
| + | , | ||
| + | � | ||
| + | � | ||
| + | ) | ||
| + | J(X,U,t | ||
| + | f | ||
| + | | ||
| + | )) for optimization. | ||
| + | Constraints: Involves end-to-end states, control bounds, and obstacle avoidance. | ||
| + | Optimization Techniques | ||
| + | Generalized LQR, Approximate Dynamic Programming, Finite Elements, and Pseudospectral methods reviewed. | ||
| + | Legendre Pseudospectral method chosen for resolution due to proven convergence. | ||
| + | Resolution | ||
| + | Transformation to Finite Dimensional Problem using polynomial basis. | ||
| + | Legendre Pseudospectral method applied for solving nonlinear optimization problem. | ||
| + | Challenges | ||
| + | Complex constraints on flight parameters. | ||
| + | Ensuring real-time collaboration and efficient flight management. | ||
| + | Applications | ||
| + | Use case in flying ambulance service. | ||
| + | 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 == | ||
[[File:Présentation 14 03 2019.pdf]] | [[File:Présentation 14 03 2019.pdf]] | ||
Revision as of 14:19, 25 September 2023
Presentation of work done for a 3D GPS
Project is to calculate an optimized flight path with IA.
Path Flight Optimization
File:BELMANT-CLERC-DIAPORAMA.pdf
Objectives Develop a Hybrid VTOL (Vertical Take-Off and Landing) aircraft for flying ambulance applications. Navigate optimally in a 3D environment from point S to F. Key Features 3D collaborative GPS system. Obstacle avoidance, accounting for static and dynamic objects. Meteorological constraints integrated into the flight model. Fuel consumption and flight time minimization. Methodology Physical Modeling: Uses control inputs for thrust and angular velocity to define state equations � ′ ( � ) = � ( � ( � ) , � ( � ) ) X ′
(t)=F(X(t),U(t)).
Cost Function: Linear combination of flight time and fuel consumption ( � ( � , � , � � ) J(X,U,t f
)) for optimization.
Constraints: Involves end-to-end states, control bounds, and obstacle avoidance. Optimization Techniques Generalized LQR, Approximate Dynamic Programming, Finite Elements, and Pseudospectral methods reviewed. Legendre Pseudospectral method chosen for resolution due to proven convergence. Resolution Transformation to Finite Dimensional Problem using polynomial basis. Legendre Pseudospectral method applied for solving nonlinear optimization problem. Challenges Complex constraints on flight parameters. Ensuring real-time collaboration and efficient flight management. Applications Use case in flying ambulance service. 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
File:Présentation 14 03 2019.pdf
- Aircraft parametrical configuration
File:TMO02.pdf File:Rapport finalv2.pdf
- Aircraft takeoff