Omnidirectional Mobile Robot Path Finding Using Deep Deterministic ...
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Therefore, the objective of this study is to develop an autonomous mobile robot that can search for a path to the goal while avoiding static and dynamic ...
... The Deep Deterministic Policy Gradients (DDPG) algorithm can easily deal with continuous high-dimensional control problems through improving DQN by ...
Therefore, the goal of this research is to learn a policy that can keep approaching a given goal while avoiding static and dynamic obstacles. In this paper, the ...
Sep 9, 2024 · ... Control (MPC) with Deep Deterministic Policy Gradient (DDPG). Firstly, we apply the MPC algorithm to predict the trajectory of dynamic obstacles ...
Sep 25, 2020 · This paper proposes a novel incremental training mode to address the problem of Deep Reinforcement Learning (DRL) based path planning for a mobile robot.
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Sep 24, 2021 · Application of Deep Reinforcement Learning for Tracking Control of 3WD Omnidirectional Mobile Robot ... A deep deterministic policy gradient ...
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Abstract - The article, the implementation of the Deep. Deterministic Policy Gradient algorithm on the Gazebo model and the reality of a multi-directional ...
In this paper an optimized algorithm based on TD3 (Twin Deep Deterministic Policy gradient) used in Deep Reinforcement Learning is proposed.
Dec 7, 2022 · In this paper, we propose a deep deterministic policy gradient (DDPG)-based path-planning method for mobile robots by applying the hindsight experience replay ...
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Sep 13, 2021 · It is known that the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm is a highly efficient algorithm with a few changes compared ...