To Land or Not to Land? Digital Twin Approach for Safe Landing of Multirotors on Complex Terrain

Simulation has become a powerful tool in robotics, enabling safe and rapid testing of robots prior to deployment. It also holds great potential to aid in real-time decision-making by emulating the surroundings on-the-fly using onboard perception modules. In this work, we introduce a simulation-based decision-making framework for the safe autonomous landing of a multirotor unmanned aerial vehicle (UAV) over difficult terrains. Our framework consists of first obtaining a terrain model using onboard sensors. It then assesses a range of possible landing configurations using a digital twin of the UAV in a high-fidelity physics-based simulation with PX4 firmware running in-the-loop. Finally, it identifies the safest simulated landing configuration and uses this to perform the landing in the real world. We validate our framework over complex, previously unseen terrains with a real multirotor. Our framework matches human-level judgment on how best to land on multiple instances of complex terrain and perform safe landings in real-world tests. This can be seen at https://youtu.be/G3nzaBFDHBY. These results show the potential of our approach for aerial robotics applications involving physical interaction.