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This paper develops a novel learning-based local path planning method for Unmanned Aerial Vehicles (UAVs) in unknown environments.
Abstract—This paper develops a novel learning-based local path planning method for Unmanned Aerial Vehicles (UAVs) in unknown environments.
This paper presents an extended approach of local optimization strategy (ELOS) for generation of a collision free shortest distance path for the unmanned aerial ...
Aug 6, 2020 · In this paper, a deep reinforcement learning (DRL) method is proposed to address the problem of UAV navigation in an unknown environment.
Missing: Path Planning
A Q-learning algorithm is proposed in this work to facilitate efficient path planning for UAVs with both static and dynamic obstacle avoidance.
The main goal of the project is to use Reinforcement Learning (RL) to implement an exploration algorithm capable of driving a small fleet of UAVs in the ...
Jan 8, 2024 · This paper presents an autonomous local path planning algorithm for UAVs, based on the TD3 algorithm. The algorithm can help UAVs quickly and ...
In this paper we propose an offline path planning method for static environments using Q-learning. ... path planning problems in an unknown cluster environment.
Duration: 5:47
Posted: Sep 1, 2023
Posted: Sep 1, 2023
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Nov 22, 2024 · In contrast, local path planning uses the robot's real-time sensor data to navigate unknown or partially known environments, allowing it to ...