mlsanityData to 14 Oct 2026

Learn by Observation: Imitation Learning for Drone Patrolling from Videos of A Human Navigator

arXiv 2008.13193 ↗First posted 30 Aug 2020cs.CV cs.ROcited by 5

On the map: Offline RL and imitation learning from data → Imitation learning methods

Abstract (arXiv)

We present an imitation learning method for autonomous drone patrolling based only on raw videos. Different from previous methods, we propose to let the drone learn patrolling in the air by observing and imitating how a human navigator does it on the ground. The observation process enables the automatic collection and annotation of data using inter-frame geometric consistency, resulting in less manual effort and high accuracy. Then a newly designed neural network is trained based on the annotated data to predict appropriate directions and translations for the drone to patrol in a lane-keeping manner as humans. Our method allows the drone to fly at a high altitude with a broad view and low risk. It can also detect all accessible directions at crossroads and further carry out the integration of available user instructions and autonomous patrolling control commands. Extensive experiments are conducted to demonstrate the accuracy of the proposed imitating learning process as well as the reliability of the holistic system for autonomous drone navigation. The codes, datasets as well as video demonstrations are available at https://vsislab.github.io/uavpatrol

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Imitation learning methods, one of 13 directions in Offline RL and imitation learning from data. Builds on 16 of its 35 references that are in the map. First posted on arXiv 30 Aug 2020.

Builds on

16 of 35 references.

Closest ancestors · 2

Same direction, newest first

  1. 2019Recent Advances in Imitation Learning from Observation30 May
  2. 2018Behavioral Cloning from Observation4 May

Other references · 14

  1. 2016Identity Mappings in Deep Residual Networkscited by 1,965
  2. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 523
  3. 2017End-to-end Driving via Conditional Imitation Learningcited by 485
  4. 2017Time-Contrastive Networks: Self-Supervised Learning from Videocited by 459
  5. 2017Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translationcited by 167
  6. 2019Deep Drone Racing: From Simulation to Reality with Domain Randomizationcited by 76
  7. 2016Discriminative Correlation Filter with Channel and Spatial Reliabilitycited by 45
  8. 2018Variational End-to-End Navigation and Localizationcited by 34
  9. 2017Uncertainty-Aware Learning from Demonstration using Mixture Density Networks with Sampling-Free Variance Modelingcited by 25
  10. 2017Toward Low-Flying Autonomous MAV Trail Navigation using Deep Neural Networks for Environmental Awarenesscited by 19
  11. 2016Efficient Optical flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Dronecited by 11
  12. 2015Deep Neural Network for Real-Time Autonomous Indoor Navigationcited by 9
2 more
  1. 2019Learning Actions from Human Demonstration Video for Robotic Manipulationcited by 9
  2. 2018Learning Transferable UAV for Forest Visual Perceptioncited by 3

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 3; 2024: 0; 2025: 1.

5 papers.

  1. 2023Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrationscited by 75
  2. 2022Aerial Vision-and-Dialog Navigationcited by 49
  3. 2025AeroDuo: Aerial Duo for UAV-based Vision and Language Navigationcited by 13
  4. 2023Learning with Chemical versus Electrical Synapses -- Does it Make a Difference?cited by 5
  5. 2023Multi-model fusion for Aerial Vision and Dialog Navigation based on human attention aidscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2018Learning to Navigate Autonomously in Outdoor Environments : MAVNet
  2. 2025FlightDiffusion: Revolutionising Autonomous Drone Training with Diffusion Models Generating FPV Video
  3. 2018OIL: Observational Imitation Learning
  4. 2021VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation
  5. 2019Learning Vision-based Flight in Drone Swarms by Imitation
  6. 2025Dream to Fly: Model-Based Reinforcement Learning for Vision-Based Drone Flight
  7. 2026SkyDrive: Learning to Drive in a New City from Aerial Traffic Monitoring
  8. 2025UAV-Flow Colosseo: A Real-World Benchmark for Flying-on-a-Word UAV Imitation Learning