Safe and Reliable Path Planning for the Autonomous Vehicle Verdino
This paper introduces a native planner that computes a collection of commands, permitting an autonomous vehicle to follow a given trajectory. To do so, the platform depends on a localization system, a map and a price map that represents the obstacles within the environment. The presented technique computes a collection of tentative trajectories, employing a schema primarily based on a Fren?t frame obtained from the world planner. These trajectories are then scored employing a linear combination of weighted cost functions. In the presented approach, new weights are introduced so as to satisfy the specificities of our autonomous platform, Verdino. A study on the influence of the outlined weights in the final behavior of the vehicle is introduced. From these tests, several configurations have been chosen and ranked consistent with two completely different proposed behaviors. The tactic has been tested each in simulation and in real conditions.
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