Optimal Vehicle Path Planning Using Quadratic Optimization for Baidu Apollo Open Platform | IEEE Conference Publication | IEEE Xplore

Optimal Vehicle Path Planning Using Quadratic Optimization for Baidu Apollo Open Platform


Abstract:

Path planning is a key component in motion planning for autonomous vehicles. A path specifies the geometrical shape that the vehicle will travel, thus, it is critical to ...Show More

Abstract:

Path planning is a key component in motion planning for autonomous vehicles. A path specifies the geometrical shape that the vehicle will travel, thus, it is critical to safe and comfortable vehicle motions. For urban driving scenarios, autonomous vehicles need the ability to navigate in cluttered environment, e.g., roads partially blocked by a number of vehicles/obstacles on the sides. How to generate a kinematically feasible and smooth path, that can avoid collision in complex environment, makes path planning a challenging problem. In this paper, we present a novel quadratic programming approach that generates optimal paths with resolution-complete collision avoidance capability.
Date of Conference: 19 October 2020 - 13 November 2020
Date Added to IEEE Xplore: 08 January 2021
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Conference Location: Las Vegas, NV, USA

References

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