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.
- Dynamic Systems and Control Division
Admittance Based Force Control for Collaborative Transportation of a Common Payload Using Two UAVs
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Barawkar, S, Radmanesh, M, Kumar, M, & Cohen, K. "Admittance Based Force Control for Collaborative Transportation of a Common Payload Using Two UAVs." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems. Tysons, Virginia, USA. October 11–13, 2017. V003T39A007. ASME. https://doi.org/10.1115/DSCC2017-5278
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