Apr 13, 2022 · This paper proposes a receding-horizon reinforcement learning approach for kinodynamic motion planning (RHRL-KDP) of autonomous vehicles.
A Receding-Horizon Reinforcement Learning Approach for ...
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To address this issue, this paper proposes a receding-horizon reinforcement learning approach for kinodynamic motion planning (RHRL-KDP) of autonomous vehicles ...
To address this issue, this paper proposes a receding-horizon reinforcement learning approach for kinodynamic motion planning (RHRL-KDP) of autonomous vehicles ...
March 30, 2022, Our paper “A Receding-Horizon Reinforcement Learning Approach for Kinodynamic Motion Planning of Autonomous Vehicles” accepted to IEEE ...
This work proposes a reinforcement learning (RL) based solution to manage uncertainty by optimizing for the worst case outcome, built on top of the ...
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Aug 9, 2023 · Xu, “Receding-horizon reinforcement learning approach for kinodynamic motion planning of autonomous vehicles,” IEEE Transactions on ...
In this paper, the Rapidly exploring Random Trees algorithm and Deep Reinforcement Learning are combined for the trajectory tracking of autonomous vehicles.
To address this issue, this paper proposes a receding-horizon reinforcement learning approach for kinodynamic motion planning (RHRL-KDP) ...
공동 저자 ; Receding-horizon reinforcement learning approach for kinodynamic motion planning of autonomous vehicles. X Zhang, Y Jiang, Y Lu, X Xu. IEEE ...
To address this issue, this paper proposes a receding-horizon reinforcement learning approach for kinodynamic motion planning (RHRL-KDP) of autonomous vehicles ...