This paper presents a novel control approach to perform collaborative transportation by using multiple quadcopter Unmanned Aerial Vehicles (UAVs). In this paper, a leader-follower approach is implemented. The leader UAV uses a Proportional, Integral and Derivative (PID) controller to reach the desired goal point or follow a predefined trajectory. Traditionally, a Position Feedback Controller (PFC) has been used in literature to control the follower UAV. PFC takes the feedback of leader UAVs position to control the follower UAV. Such control schemes work effectively in indoor environments using accurate motion tracking cameras. However, the paper focuses on outdoor applications that requires usage of Global Positioning System (GPS) to receive the positional information of the leader UAV. GPS has inherent errors of order of magnitude that can destabilize the system. The control scheme proposed in this research addresses this major limitation. In this paper, a Force Feedback Controller (FFC) is used to control the follower UAV. An admittance controller is employed to implement this FFC. This controller simulates a virtual spring mass damper system, to generate a desired trajectory for the follower UAV, which complies with the contact forces acting on it. This desired trajectory is then tracked by a traditional PID controller. With the proposed control scheme, the follower UAV can be controlled without using leaders positional feedback and the system can be implemented for real-world applications. The paper presents results of numerical simulations showing the effectiveness of the proposed controller for way-point navigation and complex trajectory tracking.

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This paper presents a novel approach to perform the task of cooperative transportation (CT) by using multiple quadcopter drones. A leader-follower approach is utilized. Considering that the leader drone can be controlled using different means, such as Proportional, Integral, and Derivative (PID) control or remote control by an operator, this paper focuses on designing the control scheme for the follower drone. This paper specifically considers outdoor application of such systems that requires usage of Global Positioning System (GPS) to receive the positional information of the drones. However, GPS has inherent errors of order of magnitude that can destabilize the system. In order to address this major limitation, a Force-Torque Feedback Controller (FT-FC) is proposed to control the follower drone. The FT-FC provides control based on the interaction forces and torques acting at the point of contact between the follower drone and the payload. Using such passive control schemes, drones are thus not required to communicate with each other. Fuzzy Logic (FL) is used to implement the FT-FC. Fuzzy Logic provides effective force-torque coordination between drones, emulates human behavior during CT, and allows use of noisy inexpensive force-torque sensors. This paper presents results from numerical simulations showing the effectiveness of the proposed controller for way-point navigation and complex trajectory tracking. Additionally, the effectiveness of the fuzzy-based FT-FC in terms of handling disturbances is also demonstrated. The proposed FL FT-FC is also experimentally validated for two applications viz. three-dimensional physical Human Drone Interaction (HDI) and CT.

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Tethered drone systems can be used to perform long-endurance tasks such as area surveillance and relay stations for wireless communication. However, all the existing systems use tethers only for data and power transmission from a stationary point on the ground. This work presents a control strategy that enables a quadcopter to follow a moving tether anchor. A force feedback controller is implemented using Fuzzy Logic. Using force-based strategy provides effective compliance between the tether’s anchor and the drone. The drone can thus be controlled by mere physical movement/manipulation of tether. This enhances the safety of current tethered drone systems and simplifies the flying of drones. Fuzzy Logic provides an intuitive edge to the control of such systems and allows handling noise in force sensors. Extensive simulation results are presented in this paper showing the effectiveness of the proposed control scheme.