Improvement of Hexacopter UAVs Attitude Parameters Employing Control and Decision Support Systems

Stamate, Mihai-Alin; Pupăză, Cristina; Nicolescu, Florin-Adrian; Moldoveanu, Cristian-Emil

doi:10.3390/s23031446

Cited by 11 publications

(8 citation statements)

References 86 publications

(86 reference statements)

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“…However, this is a one-time process. Recently, auto PID tuning approaches were proposed 60 . Hence, it is required to investigate these aspects to improve the parameter tuning of the proposed approach.…”

Section: Discussionmentioning

confidence: 99%

Residual dynamics learning for trajectory tracking for multi-rotor aerial vehicles

Kulathunga,

Hamed,

Klimchik

2024

Sci Rep

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This paper presents a technique to model the residual dynamics between a high-level planner and a low-level controller by considering reference trajectory tracking in a cluttered environment as an example scenario. We focus on minimising residual dynamics that arise due to only the kinematical modelling of high-level planning. The kinematical modelling is sufficient for such scenarios due to safety constraints and aggressive manoeuvres that are difficult to perform when the environment is cluttered and dynamic. We used a simplified motion model to represent the motion of the quadrotor when formulating the high-level planner. The Sparse Gaussian Process Regression-based technique is proposed to model the residual dynamics. Recently proposed Data-Driven MPC is targeting aggressive manoeuvres without considering obstacle constraints. The proposed technique is compared with Data-Driven MPC to estimate the residual dynamics error without considering obstacle constraints. The comparison results yield that the proposed technique helps to reduce the nominal model error by a factor of 2 on average. Further, the proposed complete framework was compared with four other trajectory-tracking approaches in terms of tracking the reference trajectory without colliding with obstacles. The proposed approach outperformed the others with less flight time without losing computational efficiency.

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Section: Discussionmentioning

confidence: 99%

Residual dynamics learning for trajectory tracking for multi-rotor aerial vehicles

Kulathunga,

Hamed,

Klimchik

2024

Sci Rep

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“…However, this is a one-time process. Recently, auto PID tuning approaches were proposed (Stamate et al, 2023). Hence, it is required to investigate these aspects to improve the parameter tuning of the proposed approach.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Optimization-Based Trajectory Tracking Approach for Multi-Rotor Aerial Vehicles in Unknown Environments

Kulathunga

Hamed

Devitt

et al. 2022

IEEE Robot. Autom. Lett.

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This paper presents a technique to cope with the gap between high-level planning, e.g., reference trajectory tracking, and low-level controlling using a learning-based method in the plan-based control paradigm. The technique improves the smoothness of maneuvering through cluttered environments, especially targeting low-speed velocity profiles. In such a profile, external aerodynamic effects that are applied on the quadrotor can be neglected. Hence, we used a simplified motion model to represent the motion of the quadrotor when formulating the Nonlinear Model Predictive Control (NMPC)-based local planner. However, the simplified motion model causes residual dynamics between the high-level planner and the low-level controller. The Sparse Gaussian Process Regression-based technique is proposed to reduce these residual dynamics. The proposed technique is compared with Data-Driven MPC. The comparison results yield that an augmented residual dynamics model-based planner helps to reduce the nominal model error by a factor of 2 on average. Further, we compared the proposed complete framework with four other approaches. The proposed approach outperformed the others in terms of tracking the reference trajectory without colliding with obstacles with less flight time without losing computational efficiency.

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“…Customization and Flexibility. The modular nature of hexacopter and octocopter designs allows for greater customization [65,66]. Users can adapt these drones for specific applications by adding or modifying payload options, making them versatile tools for various industries.…”

Section: Hexacopters and Octocoptersmentioning

confidence: 99%

A Review on the State of the Art in Copter Drones and Flight Control Systems

Peksa,

Mamchur

2024

Sensors

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This paper presents an overview on the state of the art in copter drones and their components. It starts by providing an introduction to unmanned aerial vehicles in general, describing their main types, and then shifts its focus mostly to multirotor drones as the most attractive for individual and research use. This paper analyzes various multirotor drone types, their construction, typical areas of implementation, and technology used underneath their construction. Finally, it looks at current challenges and future directions in drone system development, emerging technologies, and future research topics in the area. This paper concludes by highlighting some key challenges that need to be addressed before widespread adoption of drone technologies in everyday life can occur. By summarizing an up-to-date survey on the state of the art in copter drone technology, this paper will provide valuable insights into where this field is heading in terms of progress and innovation.

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Improvement of Hexacopter UAVs Attitude Parameters Employing Control and Decision Support Systems

Cited by 11 publications

References 86 publications

Residual dynamics learning for trajectory tracking for multi-rotor aerial vehicles

Residual dynamics learning for trajectory tracking for multi-rotor aerial vehicles

Optimization-Based Trajectory Tracking Approach for Multi-Rotor Aerial Vehicles in Unknown Environments

A Review on the State of the Art in Copter Drones and Flight Control Systems

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