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- Collaborative Target Search With a Visual Drone Swarm: An Adaptive Curriculum Embedded Multistage Reinforcement Learning Approach63
This work decomposes the CTS task into several subtasks including individual obstacle avoidance, target search, and inter-agent collaboration, and progressively train the agents with multistage learning, and designs an adaptive embedded curriculum (AEC) where the task difficulty level can be adaptively adjusted based on the success rate achieved in training.
- Toward Collaborative Multitarget Search and Navigation with Attention‐Enhanced Local Observation16
The POsthumous Mix‐credit assignment with Attention (POMA) framework integrates adaptive curriculum learning and mixed individual‐group credit assignments to efficiently balance individual and group contributions in a sparse reward environment and leverages an attention mechanism to manage variable local observations, enhancing the framework's scalability.
- Clustering-based Learning for UAV Tracking and Pose Estimation4
This work develops a clustering-based learning detection approach, CL-Det, for UAV tracking and pose estimation using two types of LiDARs, namely Livox Avia and LiDAR 360, and shows competitive pose estimation performance and ranks 5th on the final leaderboard of the CVPR 2024 UG2+ Challenge.
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