Microsoft and IAMAI collaborated to advance high-fidelity autonomy simulations through Project AirSim—the evolution of AirSim— released under the MIT license as part of a DARPA-supported initiative.
Abstract: This paper presents a novel approach for landing an autonomous quadcopter using reinforcement learning (RL) in the AirSim simulation environment running on Unreal Engine. The complicated ...
Abstract: As a typical application of the low-altitude economy, UAV collaborative monitoring contributes to urban management and data collection. The dense distribution of urban buildings leads to ...
This repository provides a code base to evaluate and train models from the paper "Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations". This project is licensed under ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results