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Autonomous Landing of a UAV on a Moving UGV Platform using Cooperative MPC

Time: Wed 2021-09-29 10.00 - 11.00

Location: Zoom Meeting https://kth-se.zoom.us/j/63850255829 (Links to an external site.)

Respondent: Luca Garegnani , Reglerteknik/DCS

Supervisor: Dženan Lapandić

Examiner: Bo Wahlgren

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Abstract

Cooperative control of autonomous multi-agent systems is a research area which is getting significant attention in recent years. Multi-agent systems allow for a broad spectrum of applications and cooperation can increase their flexibility, efficiency and robustness to changes in external constraints and disturbances. Focusing on autonomous vehicles, examples of possible applications of cooperative multi-agent systems include search and rescue missions, autonomous delivery and performing of emergency landings. The purpose of the thesis is to develop and implement a cooperative rendezvous algorithm based on model predictive control and apply it to the problem of autonomous landing in an indoor setting. The agents involved in the maneuver are a quadcopter and a ground carrier. The two agents cooperatively negotiate on the optimal location for the touchdown taking also into account relevant spatial constraints and, if necessary, update that location, also referred to as rendezvous point, in real-time throughout the maneuver. The algorithm is first tested and validated in a simulated environment and finally on the physical system during real-time operations. Additional scenarios are tested in the simulated environment in order to further inspect the potential capabilities of the developed algorithm. Those additional simulations analyse how the algorithm behaves when a constant lateral wind influences the quadcopter; when the controllers operate at a reduced frequency; and when the quadcopter is affected by an external Gaussian disturbance. The developed algorithm proved to be suitable for the purpose, allowing the agents to perform the desired maneuver in a relatively short time and with a high degree of precision.

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Belongs to: Decision and Control Systems
Last changed: Sep 28, 2021