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Motion planning and collision avoidance using MPC and strong duality

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RoyaFiroozi/Centralized-Planning

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Centralized-Planning

Optimization-based formation and reconfiguraiton of multi-lane vehicle platoons is performed using Model Predictive Control (MPC). The collision avoidance constraints among the vehicles (dynamic obstacles) as well as static obstacles on the road are modeled using strong duality theory. This formulation allows for motion planning and obstacle avoidance in tight environments. Paper describing the theory can be found here.

The requirements to run the code are MATLAB, YALMIP, and IPOPT solver for nonlinear optimization.

Examples

Obstacle Avoidance Scenario

Platoon Reconfiguration Scenario

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Motion planning and collision avoidance using MPC and strong duality

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