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A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Towards Real-Time Path Planning through Deep Reinforcement Learning for a UAV in Dynamic Environments
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Evolutionary Autopilot Design Approach for UAV Quadrotor by Using GA
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Reinforcement learning based optimizer for improvement of predicting tunneling-induced ground responses
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A hybrid algorithm of particle swarm optimization, metropolis criterion and RTS smoother for path planning of UAVs
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Multi-robot path planning using improved particle swarm optimization algorithm through novel evolutionary operators
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Deep learning, reinforcement learning, and world models
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A Gaussian process-based RRT planner for the exploration of an unknown and cluttered environment with a UAV
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Path Planning via an Improved DQN-Based Learning Policy
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Trajectory Planning for UAV Based on Improved ACO Algorithm
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B-APFDQN: A UAV Path Planning Algorithm Based on Deep Q-Network and Artificial Potential Field
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Autonomous UAV Path Planning Using Modified PSO for UAV-Assisted Wireless Networks
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Path Planning for Outdoor Mobile Robots Based on IDDQN
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Unmanned Aerial Vehicle Path Planning Based on Improved DDQN Algorithm
inferredcites →https://doi.org/10.1109/ccdc.2014.6852877openalex-snapshot
Three-dimensional path planning for UAV based on improved PSO algorithm
inferredcites →https://doi.org/10.1109/icc51166.2024.10622205openalex-snapshot
Multi-UAV Multi-RIS QoS-Aware Aerial Communication Systems Using DRL and PSO
inferredcites →https://doi.org/10.1109/iciai.2019.8850744openalex-snapshot
Path planning for UAV tracking target based on improved A-star algorithm
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Intelligent Path Planning of Underwater Robot Based on Reinforcement Learning
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UAV Path Planning under Dynamic Threats Using an Improved PSO Algorithm
inferredcites →https://doi.org/10.1155/2023/8821906openalex-snapshot
An Improved Quantum-Behaved Particle Swarm Optimization Algorithm Combined with Reinforcement Learning for AUV Path Planning
inferredcites →https://doi.org/10.23919/ccc63176.2024.10661693openalex-snapshot
UAV path planning algorithm based on Global Optimal Solution Tracking Enhanced Particle Swarm Optimization
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Multiple UAVs Path Planning Based on Deep Reinforcement Learning in Communication Denial Environment
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Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm Optimization
inferredcites →https://doi.org/10.7763/ijcte.2009.v1.80openalex-snapshot
Particle Swarm Optimization Methods, Taxonomy and Applications
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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