Difference between revisions of "MERL"
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| + | * This page is not affiliated with MERL and is updated by Cogniteam internally to track general available information | ||
* We demonstrate MERL's particle filter-based planning for autonomous vehicle using Hamster mini-cars. One car is controlled by MERL's planning algorithm and executes different driving maneuvers in traffic, constituted by two cars that follow the center of pre-assigned lanes. The path planner algorithm generates target trajectories and velocities that are tracked by decoupled PID loops. | * We demonstrate MERL's particle filter-based planning for autonomous vehicle using Hamster mini-cars. One car is controlled by MERL's planning algorithm and executes different driving maneuvers in traffic, constituted by two cars that follow the center of pre-assigned lanes. The path planner algorithm generates target trajectories and velocities that are tracked by decoupled PID loops. | ||
Latest revision as of 09:23, 31 March 2019
- This page is not affiliated with MERL and is updated by Cogniteam internally to track general available information
- We demonstrate MERL's particle filter-based planning for autonomous vehicle using Hamster mini-cars. One car is controlled by MERL's planning algorithm and executes different driving maneuvers in traffic, constituted by two cars that follow the center of pre-assigned lanes. The path planner algorithm generates target trajectories and velocities that are tracked by decoupled PID loops.
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- We demonstrate MERL's particle filter-based planning and MPC control using PRESAS solver for autonomous vehicle using Hamster mini-cars. One car is controlled by MERL's planning algorithm and executes different driving maneuvers in traffic, constituted by two cars that follow the center of pre-assigned lanes. The path planner algorithm generates target trajectories and velocities that are tracked by a single multi-variable MPC controller solving the optimization problem in real-time.
[[2]]
