InfoFusion Controller: Informed TRRT Star with Mutual Information based on Fusion of Pure Pursuit and MPC for Enhanced Path Planning

작성자 최성준
학과 또는 소속(회사명) 소프트웨어융합학과
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In this paper, we propose the InfoFusion Controller, an advanced path planning algorithm that integrates both global and local planning strategies to enhance autonomous driving in complex urban environments.

The global planner utilizes the informed Theta-Rapidly-exploring Random Tree Star (Informed- TRRT*) algorithm to generate an optimal reference path, while the local planner combines Model Predictive Control (MPC) and Pure Pursuit algorithms. Mutual Information (MI) is employed to fuse the outputs of the MPC and Pure Pursuit controllers, effectively balancing their strengths and compensating for their weaknesses.

The proposed method addresses the challenges of navigating in dynamic environments with unpredictable obstacles by reducing uncertainty in local path planning and improving dynamic obstacle avoidance capabilities. Experimental results demonstrate that the InfoFusion Controller outperforms traditional methods in terms of safety, stability, and efficiency across various scenarios, including complex maps generated using SLAM techniques.

Index Terms—Path Planning, MPC, Pure Pursuit, Mutual Information

InfoFusion Controller: Informed TRRT Star with Mutual Information based on Fusion of Pure Pursuit and MPC for Enhanced Path Planning

조회수 6
평가(좋아요)수 1
댓글수 0
게시 : 2024년 11월 20일
최성준 소프트웨어융합학과

InfoFusion Controller: Informed TRRT Star with Mutual Information based on Fusion of Pure Pursuit and MPC for Enhanced Path Planning

조회수 6
평가(좋아요)수 1
댓글수 0
게시 : 2024-11-20

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Keyword

Path Planning, MPC, Pure Pursuit, Mutual Information, Planning, Autonomous Driving, Safety,

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