AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles

A survey of transfer learning

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Comprehensive Simulation of Quadrotor UAVs Using ROS and Gazebo

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Practical Meteorology : An Algebra-based Survey of Atmospheric Science

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Introduction to Fluid Mechanics

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Classical Mechanics

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The GGM03 Mean Earth Gravity Model from GRACE

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The earth's magnetism: an introduction for geologists

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An Invitation to Imitation

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ROSflight: A lightweight, inexpensive MAV research and development tool

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A Stochastic Approach to Noise Modeling for Barometric Altimeters

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History of fluid mechanics

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How Safe are our Nation’s Assets – Reverse Threats in Today’s World

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Deep reinforcement learning for autonomous driving: A survey

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Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey

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Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems

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Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

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Gibson Env: Real-World Perception for Embodied Agents

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Applications of Physics-Informed Neural Networks in Power Systems - A Review

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Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives

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ChatGPT for Robotics: Design Principles and Model Abilities

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LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving

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Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys

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3D Object Detection for Autonomous Driving: A Comprehensive Survey

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TartanAir: A Dataset to Push the Limits of Visual SLAM

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R 3 LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

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Synthetic Data for Deep Learning

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Kernel Mean Embedding of Distributions: A Review and Beyond

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Voxelized GICP for Fast and Accurate 3D Point Cloud Registration

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Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment

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Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation

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ESIM: an Open Event Camera Simulator

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Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding

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Micro Air Vehicle Link (MAVlink) in a Nutshell: A Survey

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Autonomous Vehicles and Intelligent Automation: Applications, Challenges, and Opportunities

Bathla, G., Bhadane, K. V., Singh, R. K., Kumar, R., Aluvalu, R., Krishnamurthi, R., Kumar, A., Thakur, R. N., & Basheer, S. (2022) · Mobile Information Systems · doi:10.1155/2022/7632892 · Cited by 343 · see citing works

Real-Time Monocular Depth Estimation Using Synthetic Data with Domain Adaptation via Image Style Transfer

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Orbital Edge Computing

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When2com: Multi-Agent Perception via Communication Graph Grouping

Liu, Y., Tian, J., Glaser, N., & Kira, Z. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00416 · Cited by 284 · see citing works

A Review of Physics Simulators for Robotic Applications

Collins, J., Chand, S., Vanderkop, A., & Howard, D. (2021) · IEEE Access · doi:10.1109/access.2021.3068769 · Cited by 281 · see citing works

A Survey on Safety-Critical Driving Scenario Generation—A Methodological Perspective

Ding, W., Xu, C., Arief, M., Lin, H., Li, B., & Zhao, D. X. (2023) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2023.3259322 · Cited by 277 · see citing works

Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments

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Time-optimal planning for quadrotor waypoint flight

Foehn, P., Romero, Á., & Scaramuzza, D. (2021) · Science Robotics · doi:10.1126/scirobotics.abh1221 · Cited by 248 · see citing works

Learning to Navigate in Cities Without a MapPreprint

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A review of AI-enabled routing protocols for UAV networks: Trends, challenges, and future outlook

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MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement Learning

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LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World

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A review of artificial intelligence applied to path planning in UAV swarms

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Foundation models in robotics: Applications, challenges, and the future

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Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering

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Is it Safe to Drive? An Overview of Factors, Metrics, and Datasets for Driveability Assessment in Autonomous Driving

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RoboTHOR: An Open Simulation-to-Real Embodied AI Platform

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3D-LaneNet: End-to-End 3D Multiple Lane Detection

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AADS: Augmented autonomous driving simulation using data-driven algorithms

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Explainable Deep Reinforcement Learning for UAV autonomous path planning

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Learning to Fly—a Gym Environment with PyBullet Physics for Reinforcement Learning of Multi-agent Quadcopter Control

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Learning Robust Control Policies for End-to-End Autonomous Driving From Data-Driven Simulation

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Multi-Agent Systems for Search and Rescue Applications

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End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners

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A survey of Open-Source UAV flight controllers and flight simulators

Ebeid, E., Skriver, M., Terkildsen, K. H., Jensen, K., & Schultz, U. P. (2018) · Microprocessors and Microsystems · doi:10.1016/j.micpro.2018.05.002 · Cited by 189 · see citing works

UAV navigation in high dynamic environments: A deep reinforcement learning approach

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Who2com: Collaborative Perception via Learnable Handshake Communication

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UnrealCV

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The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

Liang, J., Jiang, L., Murphy, K. P., Yu, T., & Hauptmann, A. G. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.01052 · Cited by 183 · see citing works

X-View: Graph-Based Semantic Multi-View Localization

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Test Your Self-Driving Algorithm: An Overview of Publicly Available Driving Datasets and Virtual Testing Environments

Kang, Y., Yin, H., & Berger, C. (2019) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2018.2886678 · Cited by 183 · see citing works

MINOS: Multimodal Indoor Simulator for Navigation in Complex EnvironmentsPreprint

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Sim4CV: A Photo-Realistic Simulator for Computer Vision Applications

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Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Hu, Z., Lou, S., Xing, Y., Wang, X., Cao, D., & Lv, C. (2022) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2022.3195635 · Cited by 178 · see citing works

A review of UAV autonomous navigation in GPS-denied environments

Chang, Y., Cheng, Y., Manzoor, U., & Murray, J. F. (2023) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2023.104533 · Cited by 183 · see citing works

UniSim: A Neural Closed-Loop Sensor Simulator

Yang, Z., Chen, Y., Wang, J., Manivasagam, S., Ma, W.-C., Yang, A. J., & Urtasun, R. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52729.2023.00140 · Cited by 170 · see citing works

A Survey of Wireless Networks for Future Aerial Communications (FACOM)

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Scalable End-to-End Autonomous Vehicle Testing via Rare-event SimulationPreprint

O’Kelly, M., Sinha, A., Namkoong, H., Duchi, J. C., & Tedrake, R. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.00145 · Cited by 163 · see citing works

On the use of simulation in robotics: Opportunities, challenges, and suggestions for moving forward

Choi, H., Crump, C., Duriez, C., Elmquist, A., Hager, G., Han, D., Hearl, F., Hodgins, J., Jain, A., Leve, F., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1907856118 · Cited by 162 · see citing works

Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Models

Liu, Y., Yang, D., Wang, Y., Liu, J., Liu, J., Boukerche, A., Sun, P., & Song, L. (2024) · ACM Computing Surveys · doi:10.1145/3645101 · Cited by 177 · see citing works

Learning Decentralized Controllers for Robot Swarms with Graph Neural NetworksPreprint

Tolstaya, E. I., Gama, F., Paulos, J., Pappas, G. J., Kumar, V., & Ribeiro, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.10527 · Cited by 170 · see citing works

A Survey on Automated Driving System Testing: Landscapes and Trends

Tang, S., Zhang, Z., Zhang, Y., Zhou, J., Guo, Y. R., Liu, S., Guo, S., Li, Y., Ma, L., Xue, Y., et al. (2023) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3579642 · Cited by 162 · see citing works

A Review on Viewpoints and Path Planning for UAV-Based 3-D Reconstruction

Maboudi, M., Homaei, M., Song, S., Malihi, S., Saadatseresht, M., & Gerke, M. (2023) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2023.3276427 · Cited by 164 · see citing works

Aligning Cyber Space With Physical World: A Comprehensive Survey on Embodied AI

Liu, Y., Chen, W., Bai, Y., Liang, X., Li, G., Gao, W., & Lin, L. (2025) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2025.3574943 · Cited by 220 · see citing works

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

Ghamari, M., Rangel, P., Mehrübeoğlu, M., Tewolde, G., & Sherratt, R. S. (2022) · IEEE Access · doi:10.1109/access.2022.3208571 · Cited by 163 · see citing works

A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance

Fraga‐Lamas, P., Ramos, L., Mondéjar-Guerra, V. M., & Fernández‐Caramés, T. M. (2019) · Remote Sensing · doi:10.3390/rs11182144 · Cited by 158 · see citing works

Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

Yan, Y., Lin, H., Zhou, C., Wang, W., Sun, H., Zhan, K., Lang, X., Zhou, X., & Peng, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-73464-9_10 · Cited by 172 · see citing works

Application specific drone simulators: Recent advances and challenges

Mairaj, A., Baba, A. I., & Javaid, A. Y. (2019) · Simulation Modelling Practice and Theory · doi:10.1016/j.simpat.2019.01.004 · Cited by 149 · see citing works

Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning

Palanisamy, P. (2020) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn48605.2020.9207663 · Cited by 148 · see citing works

Transferring policy of deep reinforcement learning from simulation to reality for robotics

Ju, H., Juan, R., Gomez, R., Nakamura, K., & Li, G. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00573-6 · Cited by 147 · see citing works

RFlySim: Automatic test platform for UAV autopilot systems with FPGA-based hardware-in-the-loop simulations

Dai, X., Ke, C., Quan, Q., & Cai, K. (2021) · Aerospace Science and Technology · doi:10.1016/j.ast.2021.106727 · Cited by 145 · see citing works

Agilicious: Open-source and open-hardware agile quadrotor for vision-based flight

Foehn, P., Kaufmann, E., Romero, Á., Pěnička, R., Sun, S., Bauersfeld, L., Laengle, T., Cioffi, G., Song, Y., Loquercio, A., et al. (2022) · Science Robotics · doi:10.1126/scirobotics.abl6259 · Cited by 150 · see citing works

FlightGoggles: Photorealistic Sensor Simulation for Perception-driven Robotics using Photogrammetry and Virtual Reality

Guerra, W., Tal, E. A., Murali, V., Ryou, G., & Karaman, S. (2019) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros40897.2019.8968116 · Cited by 139 · see citing works

How Simulation Helps Autonomous Driving: A Survey of Sim2real, Digital Twins, and Parallel Intelligence

Hu, X.-M., Li, S., Huang, T., Tang, B., Huai, R., & Chen, L. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3312777 · Cited by 173 · see citing works

Autonomous Drone Racing: A Survey

Hanover, D., Loquercio, A., Bauersfeld, L., Romero, Á., Pěnička, R., Song, Y., Cioffi, G., Kaufmann, E., & Scaramuzza, D. (2024) · IEEE Transactions on Robotics · doi:10.1109/tro.2024.3400838 · Cited by 148 · see citing works

Adversarial examples: A survey of attacks and defenses in deep learning-enabled cybersecurity systems

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A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes

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