Dynamic interaction between robot and UAV in aerial manipulation

Cocuzza, Silvio; Rossetto, Edoardo; Doria, Alberto

doi:10.1109/me49197.2020.9286694

Cited by 3 publications

(5 citation statements)

References 13 publications

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“…In a real-world application, a low-level controller calculates the rotor speeds that result in these control forces and torques. The general dynamic equations relating rotor speeds and simplified thrust/attitude control inputs for a multicopter system in 3D are summarized in [12]. In our analysis, we only consider UAM translations in the 2D plane x I z I and rotation about the y I -axis orthogonal to that plane.…”

Section: Unmanned Aerial Manipulator Dynamics and Control Modelmentioning

confidence: 99%

“…Sci. 2022, 12, x FOR PEER REVIEW 4 of 28 relating rotor speeds and simplified thrust/attitude control inputs for a multicopter system in 3D are summarized in [12]. In our analysis, we only consider UAM translations in the 2D plane and rotation about the -axis orthogonal to that plane.…”

Section: Unmanned Aerial Manipulator Dynamics and Control Modelmentioning

confidence: 99%

“…On the other hand, global [19] and nearly-global [20] optimization approaches have been developed in the case of fixed-base and of space manipulators, and their applicability to the case of aerial manipulators will be part of future work. Indeed, as demonstrated in [12], a torque transferred to the UAV CoG causes an undesired large horizontal displacement of the UAV, which in turn jeopardizes the endeffector precision. On the other hand, global [19] and nearly-global [20] optimization approaches have been developed in the case of fixed-base and of space manipulators, and their applicability to the case of aerial manipulators will be part of future work.…”

Section: Unmanned Aerial Manipulator Dynamics and Control Modelmentioning

confidence: 99%

“…In general, static balancing through controlling the arm to be aligned with the aerial robot does not guarantee that zero reaction forces and torques are transferred from the manipulator to the robot. The dynamic interaction between the manipulator and UAV in aerial manipulation has also been discussed in [12].…”

Section: Introductionmentioning

confidence: 99%

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Zero Reaction Torque Trajectory Tracking of an Aerial Manipulator through Extended Generalized Jacobian

2022

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Aerial manipulators are used in industrial and service robotics tasks such as assembly, inspection, and maintenance. One of the main challenges in aerial manipulation is related to the motion of the UAV base caused by manipulator disturbance torques and forces, which jeopardize the precision of the robot manipulator. In this paper, we propose two novel inverse kinematic control methods used to track a trajectory with an aerial manipulator while also considering resultant UAV base motions. The first method is adapted from the generalized Jacobian formulation used in space robotics and includes the change in system momentum resulting from gravity and UAV control forces in the inverse kinematic control equation. This approach is simulated for a 2 and 3 degree-of-freedom aerial manipulator tracking trajectories with the end-effector. Although the end-effector position error is approximately zero throughout the simulated task, we see significant undesired UAV base motions of several centimeters in magnitude. To ameliorate this by exploiting the kinematic redundancy, we modify the generalized Jacobian by adding an additional task constraint which minimizes the reaction torques from the manipulator, to form the extended generalized Jacobian. While the second approach results in improved precision and reduced base motion by an order of magnitude as compared to the generalized Jacobian, a drawback is the reduction in the available workspace as the solution seeks to minimize the manipulator center of gravity translation. We also demonstrate and compare both approaches in a load picking task. All the algorithms are completed computationally faster than real time in the MATLAB simulations, illustrating their potential for application in real-world experiments.

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Section: Unmanned Aerial Manipulator Dynamics and Control Modelmentioning

confidence: 99%

Section: Unmanned Aerial Manipulator Dynamics and Control Modelmentioning

confidence: 99%

Section: Unmanned Aerial Manipulator Dynamics and Control Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Zero Reaction Torque Trajectory Tracking of an Aerial Manipulator through Extended Generalized Jacobian

2022

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“…To eradicate this limitation in our work, the shortest path found by the search algorithm is handed over to a trajectory generation algorithm, which generates a dynamically feasible and optimal trajectory with finite and smooth curvatures. The vibration of the UAV frame [36,37] and the motion of a robot manipulator mounted on the UAV [38] might affect the system dynamics and motion planning, and this will be investigated in future works. In particular, a reactionless motion of the manipulator [39][40][41][42] will be beneficial because it will not significantly affect the system dynamics.…”

Section: Introductionmentioning

confidence: 99%

Modified A-Star (A*) Approach to Plan the Motion of a Quadrotor UAV in Three-Dimensional Obstacle-Cluttered Environment

et al. 2022

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Motion-planning algorithms play a vital role in attaining various levels of autonomy for any ground or flying agent. Three-dimensional (3D) motion-planning is interesting, but rather complex, especially for flying agents such as autonomous unmanned aerial vehicles (UAVs), due to the increased dimensionality of space and consideration of dynamical constraints for a feasible trajectory. Usually, in 3D path search problems, it is hard to avoid extra expanded nodes due to increased dimensionality with various available search options. Therefore, this paper discusses and implements a modified heuristic-based A* formalism that uses a truncation mechanism in order to eradicate the mentioned problem. In this formalism, the complete motion planning is divided into shortest path search problem and smooth trajectory generation. The shortest path search problem is subdivided into an initial naïve guess of the path and the truncation of the extra nodes. To find a naïve shortest path, a conventional two-dimensional (2D) A* algorithm is augmented for 3D space with six-sided search. This approach led to the inclusion of extra expanded nodes and, therefore, it is not the shortest one. Hence, a truncation algorithm is developed to further process this path in order to truncate the extra expanded nodes and then to shorten the path length. This new approach significantly reduces the path length and renders only those nodes that are obstacle-free. The latter is ensured using a collision detection algorithm during the truncation process. Subsequently, the nodes of this shortened path are used to generate a dynamically feasible and optimal trajectory for the quadrotor UAV. Optimal trajectory generation requires that the plant dynamics must be differentially flat. Therefore, the corresponding proof is presented to ensure generation of the optimal trajectory. This optimal trajectory minimizes the control effort and ensures longer endurance. Moreover, quadrotor model and controllers are derived as preliminaries, which are subsequently used to track the desired trajectory generated by the trajectory planner. Finally, results of numerical simulations which ultimately validate the theoretical developments are presented.

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Trajectory Tracking Control of an Aerial Manipulator in the Presence of Disturbances and Model Uncertainties

Pedrocco,

Pasetto,

Fanti

et al. 2024

Applied Sciences

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The precise control of an aerial manipulator presents a formidable challenge due to the inherent mobility of its base, which is subject to both external disturbances and dynamic disturbances due to manipulator motions. In this paper, we introduce two Closed-Loop Inverse Kinematics (CLIK) control algorithms tailored to aerial manipulators. The first algorithm operates at the velocity level and uses the Generalized Jacobian for inverse kinematics, while the second one operates at the acceleration level. We evaluate their performance in a simulated environment, replicating real-world challenges such as the wind effect, sensors noise, uncertainty of the system inertial parameters, and impulsive forces at the end-effector. Trajectory tracking simulated experiments are carried out for a two- and three-degree-of-freedom (DOF) aerial manipulator tracking a circular trajectory with its end-effector. Both algorithms demonstrate promising results in coping with external disturbances and variations in the inertial parameters, enhancing the precision of the trajectory tracking control. The acceleration-level algorithm shows overall better performance compared to the velocity-level one in the face of greater implementation complexity and computational burden.

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Dynamic interaction between robot and UAV in aerial manipulation

Cited by 3 publications

References 13 publications

Zero Reaction Torque Trajectory Tracking of an Aerial Manipulator through Extended Generalized Jacobian

Zero Reaction Torque Trajectory Tracking of an Aerial Manipulator through Extended Generalized Jacobian

Modified A-Star (A*) Approach to Plan the Motion of a Quadrotor UAV in Three-Dimensional Obstacle-Cluttered Environment

Trajectory Tracking Control of an Aerial Manipulator in the Presence of Disturbances and Model Uncertainties

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