PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion

arXiv:2606.03441 · cs.RO, cs.LG · Submitted 2026-06-02 · Read on arXiv

cs.RO, cs.LG

Submitted: 2026-06-02

Updated: 2026-09-19

Code: https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_apriltag

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Generalization — 15× in this paper · explained in 13 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Reinforcement Learning — 11× in this paper · explained in 4 episodes
• Active Perception — 10× in this paper · explained in 2 episodes
• Fine-Tuning — 8× in this paper · explained in 5 episodes
• Robustness — 8× in this paper · explained in 5 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Adaptability — 6× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 5× in this paper · explained in 2 episodes
• Sim-to-Real Gap — 4× in this paper · explained in 6 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Ablation Studies — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• International Conference on Robotics and Automation — 3× in this paper
• Systematic Bias — 3× in this paper · explained in 3 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Decoupling — 2× in this paper · explained in 2 episodes
• Geometric Distribution — 2× in this paper · explained in 2 episodes
• Reward Function — 2× in this paper · explained in 2 episodes
• Actor-Critic Architecture — 1× in this paper · explained in 1 episode
• Closed-Loop Control — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Ornstein–Uhlenbeck Process — 1× in this paper · explained in 3 episodes
• PID Controller — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Zero-Shot Generalization — 1× in this paper · explained in 5 episodes

Sources

• EAGERx: Graph-Based Framework for Sim2real Robot Learning
• Bootstrapping Reinforcement Learning with Imitation for Vision-Based Agile Flight
• Proximal Policy Optimization Algorithms

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