Fast, Autonomous Flight in GPS-Denied and Cluttered Environments
This addresses the challenge of reliable drone navigation in complex, unknown indoor spaces like warehouses, though it appears incremental in system integration.
The paper tackled the problem of enabling fast, autonomous flight for aerial robots in GPS-denied and cluttered environments, achieving robust navigation in real-world warehouse settings.
One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment. This challenge is addressed in the present paper. We describe the system design and software architecture of our proposed solution, and showcase how all the distinct components can be integrated to enable smooth robot operation. We provide critical insight on hardware and software component selection and development, and present results from extensive experimental testing in real-world warehouse environments. Experimental testing reveals that our proposed solution can deliver fast and robust aerial robot autonomous navigation in cluttered, GPS-denied environments.