Conference proceeding
Hardware-in-the-loop test rig to capture aerial robot and sensor suite performance metrics
2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-12, pp 3521-3526
01 Jan 2006
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Fully autonomous aerial robots are needed to accomplish near-Earth missions such as search and rescue, and bio-chemical sensing. Recent advances in sensor technologies ([6], [8], [3], [7]) urge the aerial robotics community towards full autonomy. Only then, the sensors that are needed to detect obstacles will become more accurate, reliable, and smaller. The lack of flight test data in near-Earth environments poses a gap in the modeling and integration of obstacle detection sensors. To help advance the aerial robotics field we designed a hardware-in-the-loop system for near-Earth flying robots. The hardware-in-the-loop system generates the motion of the actual robotic aircraft in near-Earth environment by implementing model reference adaptive control (MRAC). The high-fidelity math model of the robotic aircraft is the reference model of the MRAC. The controller structure of the system is explained in this paper.
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Details
- Title
- Hardware-in-the-loop test rig to capture aerial robot and sensor suite performance metrics
- Creators
- Vefa Narli - Institute of Robotics and Intelligent SystemsPaul Y. Oh - Institute of Robotics and Intelligent SystemsIEEE
- Publication Details
- 2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-12, pp 3521-3526
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- IIS 0347430 / National Science Foundation CAREER; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Web of Science ID
- WOS:000245452403109
- Scopus ID
- 2-s2.0-34250690231
- Other Identifier
- 991019350679304721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Robotics