PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion
Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to the limited field of view (FOV). In this paper, we propose PerchRL, a reinforcement learning (RL) framework for vision-based agile perching on inclined platforms under rapid and irregular motion. Specifically, we employ a two-stage learning strategy consisting of state-based pre-training followed by vision-based fine-tuning. To improve generalization across diverse platform motions, we employ randomized platform trajectories to prevent overfitting and temporal augmentation methods to capture latent motion patterns from historical observations....
| Authors | Zihong Lu, Zongzhuo Liu, Huaxu Li et al. |
|---|---|
| Primary category | cs.RO |
| Published | 2 June 2026 |
| Last updated at source | 19 September 2026 |
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