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Found 3 papers, 0 papers with code
Human-Centric Aware UAV Trajectory Planning in Search and Rescue Missions Employing Multi-Objective Reinforcement Learning with AHP and Similarity-Based Experience Replay
Our contributions include (1) a reinforcement learning framework for UAV trajectory planning that dynamically integrates multi-objective considerations, (2) an analysis of human perceptions towards gendered and anthropomorphized drones in SAR contexts, and (3) the application of similarity-based experience replay for enhanced learning efficiency in complex SAR scenarios.
Multi-Objective Reinforcement Learning
reinforcement-learning
+1
Safe Hierarchical Reinforcement Learning for CubeSat Task Scheduling Based on Energy Consumption
This paper presents a Hierarchical Reinforcement Learning methodology tailored for optimizing CubeSat task scheduling in Low Earth Orbits (LEO).
Hierarchical Reinforcement Learning
reinforcement-learning
+1
UAV Path Planning Employing MPC- Reinforcement Learning Method Considering Collision Avoidance
In this paper, we tackle the problem of Unmanned Aerial (UA V) path planning in complex and uncertain environments by designing a Model Predictive Control (MPC), based on a Long-Short-Term Memory (LSTM) network integrated into the Deep Deterministic Policy Gradient algorithm.
