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Design and Implementation of an Over-Actuated Quadrotor with Rotatable Motors Axes

Kafili Gavgani, Ali | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58685 (08)
  4. University: Sharif University of Technology
  5. Department: Mechanical Engineering
  6. Advisor(s): Alasty, Aria; Nejat, Hossein; Talaeizadeh, Amin
  7. Abstract:
  8. Conventional multirotor UAVs are inherently underactuated, preventing independent control of all degrees of freedom and thereby limiting their ability to perform complex maneuvers and specialized missions. This thesis introduces and implements the Sharif AgRoCopter, a fully-actuated quadrotor equipped with additional actuators to tilt the rotor axes, enabling full independent control across all degrees of freedom. A comprehensive comparative analysis of various omniorientational configurations is presented, offering a roadmap for configuration selection and controller design aligned with different design objectives. A novel control strategy based on virtual control signal generation and both linear and nonlinear allocation is proposed to resolve input–non-affine dynamics, facilitating the implementation of a cascaded nonlinear PID controller without linearization. Extended variants of this controller are developed to ensure reliable flight under partial sensor unavailability, and a sliding-mode controller is further designed to validate the derived system dynamics. The research also establishes experimental infrastructures, including a three-degree-of-freedom testbed, a low-cost vision-based positioning and orientation system, and a programming and testing environment for conventional quadrotors. The fully-actuated UAV is then designed, fabricated, and tested in both autonomous and non-autonomous flight modes. Experimental results confirm stable flight performance and validate the proposed control strategies. This work contributes toward the development of UAVs capable of operating reliably in dense agricultural environments, providing a foundation for AI-assisted missions and precision pest monitoring. A video from experimental tests are provided in
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