The project focuses on optimizing the control of a Dubins vehicle, which follows a path with constrained curvature. The primary goal is to develop strategies for avoiding obstacles and reaching targets efficiently.
Dubins vehicles are characterized by their nonholonomic constraints, limiting their turning capabilities. This project utilizes the vehicle's dynamics to compute optimal paths to a target while avoiding obstacles.
Four possible paths (LSR, LSL, RSR, RSL) are considered to find the minimum time route.
A distance-based penalty function is introduced to ensure the vehicle avoids obstacles.
The approach involves solving a partial differential equation using dynamic programming. The cost function and value function are key components, helping to compute the optimal control strategies.
6 Pillar: Simulation results with six obstacles.
6 Pillar: Simulation results with six obstacles using YAPPS (animations made in MATLAB).
The project highlights challenges such as grid discretization and computational time. Future work aims to extend the approach to 3D Dubins dynamics and explore control barrier functions.