Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial Robots @autonomousrobotslab
Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial Robots  @autonomousrobotslab
Uploaded March 2025 | Updated September 2026, 3 weeks ago
We are happy to release an update for the Aerial Gym Simulator.

Code: github.com/ntnu-arl/aerial_gym_simulator

The new update includes support for multi-linked embodiments, with fixed, reconfigurable (active), and soft (passive) joints for simulated multirotors. A faithful simulation model of a compliant robot Morphy(youtube.com/watch?v=C6l7Vklbc9k) and models for active reconfigurable multirotor platforms are added!

We provide scripts for training:
- State-based RL policies for position setpoint tracking including end-to-end methods
- Vision (depth) based RL-policies for navigation of cluttered environments
- Joint-aware policies for soft drones that minimize oscillations of compliant joints
- Joint and motor control policies for reconfigurable systems for robot-shape and position control

Newer capabilities to query face and vertex indices and surface normal information are added to the rendering framework alongside the capability to query user-defined vertex-level annotations from the environment.
Scripts to deploy trained policies on real robots are provided alongside network model files for easy reproducibility.
Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial RobotsThermal-Inertial Localization for Autonomous Navigation of Aerial Robots through ObscurantsCollaborative Exploration with a Marsupial Ground-Aerial Robot Team thru Task-Driven Map CompressionGraph-based Path Planning for Autonomous Subterranean ExplorationHistory-Aware Free Space Detection for Efficient Autonomous Exploration using Aerial RobotsUNR Skywalker X8 Maiden FlightSemantics-aware Predictive Inspection Path Planning: Field Deployment 1Unsupervised Anomaly Detection for Autonomous SurveillanceUNR: Robotics Seminar: Mark Mueller: Multicopter Dynamics and ControlMotion Primitives-based Path Planning for Fast and Agile Exploration using Aerial RobotsGraph-based Path Planning for Autonomous Inspection of Underground MinesICRA2020 Pitch Video: Motion Primitives-based Path Planning for Fast and Agile Exploration
Kostas Alexis |

Aerial Gym Simulator: A Framework for Highly Parallelized Simulation of Aerial Robots

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