LANDRONE: DEVELOPING ROBOTIC TOOLS FOR ADDING NON-PLANAR SURFACE LANDING CAPABILITY TO UAVS
Abstract
Unmanned Aerial Vehicles (UAVs) have been taking an important place in daily life with several different usage purposes, e.g., mapping, surveillance, inspection, and many others. One of the widely used areas of UAVs is visual inspection since they can gather information from areas beyond human-reach or from environments hostile to humans. Their usage for the inspection purpose is mostly limited to non-contact type sensors such as optical cameras and/or laser sensors. Lately, wall-climbing UAVs have been proposed to gather data using contact-type sensors. However, the major drawback is that they can solely be used for planar surfaces. For the inspection of more generic surfaces, more robotic platforms are needed. Having more robotic platforms bring the necessity of cooperation and communication among them. In this project, we propose an autonomous distributed cooperative control framework based on machine learning and deep learning and a new interaction algorithm. We will develop a new method for accurately estimating surface information and characteristics of an environment through the control of multiple robot probes that dynamically interact with an unknown environment. Also, complete development of a compact robotic mechanism with a robotic arm to allow UAVs to land on any shape of surfaces and to collect data from surfaces using not only non-contact type but also contact-type sensors is aimed at this project. This mechanism is intended to be light-weight, modular, expandable, selfbalanced, attachable to most of the existing UAVs. Such system will make UAVs to be more powerful and useful for different applications such as Search and Rescue (of buried survivors due to natural disasters or accidents at work), mine search and clean, detailed inspection of any type of surfaces such as solar panel, aircraft, and similar others.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 11, 2021
- Source ID
- FA23862014019
Entities
People
- Armağan Elibol
Organizations
- Air Force Office of Scientific Research
- Japan Advanced Institute of Science and Technology
- United States Air Force