Model Based Control of Commercial-Off-TheShelf (COTS) Unmanned Rotorcraft for BrickWall Construction
Nithya Sridhar, Sai Abhinay.N, Chaithanya Krishna.B and, Shubhankar Shobhit, Kaushik Das, Debasish Ghose

TL;DR
This paper develops a systematic modeling and control framework for COTS unmanned rotorcraft used in brick wall construction, demonstrating high accuracy and robustness through simulation and field tests.
Contribution
It introduces a novel framework for modeling and controlling COTS UAVs with sliding mode control, improving robustness and accuracy over linear controllers.
Findings
Model achieved only 9% deviation in validation.
Field tests showed control accuracy up to 8 cm.
Sliding mode control outperformed linear control in robustness.
Abstract
This work proposes a systematic framework for modelling and controller design of a Commercial-Off-The Shelf (COTS) unmanned rotorcraft using control theory and principles, for brick wall construction. With point to point navigation as the primary application, command velocities in the three axes of the Unmanned Aerial Vehicle (UAV) are considered as inputs of the system while its actual velocities are system outputs. Using the sine and step response data acquired from a Hardware-in-Loop (HiL) test simulator, the considered system was modelled in individual axes with the help of the proposed framework. This model was employed for controller design where a sliding mode controller was chosen to satisfy certain requirements of the application like robustness, flexibility and accuracy. The model was validated using step response data and produced a deviation of only 9%. Finally, the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Manufacturing and Logistics Optimization · Aerospace Engineering and Control Systems · Robotic Path Planning Algorithms
