Zhaopeng Zhang

The unmanned aerial manipulator (UAM) system, with its ability to actively interact with the environment, has significant potential for applications in infrastructure inspection and disaster relief. However, the majority of current research focuses on interactive scenarios near the system’s equilibrium point or at low speeds, limiting the utilization of the aerial vehicle’s maneuverability advantages. In addition, the unique physical characteristics of hammering tasks present challenges to both the safety and effectiveness of aerial operations. To address the aforementioned problem, this article proposes an impact mitigation strategy for aerial manipulator hammering tasks, aiming to ensure the safety of the UAM system while achieving effective hammering operation. Specifically, this strategy divides the UAM hammering task into hover, dive, and hammer phases. During the dive phase, the aerial vehicle’s maneuverability is exploited for accelerated descent, while the manipulator adjusts the end effector’s attitude to suit the hammering scenario requirements. The planning method within the strategy considers the desired velocity and attitude of the end effector at the moment of hammering, generating smooth trajectories for the aerial vehicle and manipulator. Furthermore, a manipulator controller with active/passive work modes is designed to mitigate collision impulses without the need for any specialized devices. During the hammering phase, external and internal impulse modeling and analysis are conducted, resulting in a theoretical assurance of the maximum pre-hammering end effector velocity for system safety. Multiple sets of experimental data demonstrate that the proposed strategy performs well in hammering tasks on surfaces with inclinations and materials of different hardness, effectively achieving hammering with the UAM.

The aerial manipulator, composed of a multirotor and a robotic arm, could provide extra active operation capability and has the potential for applications in both military and civilian fields. Due to the complex working scenarios, planning a safe and reliable motion trajectory for aerial manipulators is of great importance. To achieve target grasping with aerial manipulators in complex environments, a coupled motion planning method for the aerial manipulator is proposed in this article, which conducts the motion planning for the multirotor and the robotic arm simultaneously. Specifically, the aerial manipulator is considered as enclosed by a convex polyhedron other than a big sphere so as to reduce the conservatism of the trajectory. Furthermore, the trajectory of the aerial manipulator could be represented by a set of polynomial functions of the flat outputs, including the position and the yaw angle of the multirotor and the joint angles of the robotic arm. Utilizing polynomial-based trajectory representation for both the multirotor's and the robotic arm's states simplifies the optimization problem and ensures dynamic feasibility. The simulation and experimental results show the effectiveness of the proposed method. Unlike the other works that only consider the position of the end-effector, the proposed method also takes into account the orientation of the end-effector as well, resulting in improved performance in grasping tasks.

By utilizing a suspension cable to connect the payload with the quadrotor, transport tasks can be accomplished while preserving the unmanned aerial vehicle’s agility and maneuverability, particularly in environments that are impassable for ground vehicles. Equipping onboard visual sensors and utilizing image-based visual servoing techniques, the application range of aerial transportation systems is poised to be significantly expanded in scenarios like autonomous landing and goods release. Unfortunately, within the system, there exist multiple layers of dynamic couplings between image features, quadrotor rotation, translation, and payload motion. These intricacies give rise to numerous difficulties in achieving smooth anti-swing transportation. To overcome the aforementioned difficulties, this paper presents the first image-based visual servoing control scheme for the aerial transportation system with variable-length cable. Specifically, the image moments defined on the rotated virtual image plane are taken as the image features, whose dynamics is independent of the quadrotor rotational motion. Subsequently, a generalized virtual image feature signal is introduced by organically combining the cable length and payload swing angles with the image feature, which is further exploited in the anti-swing control scheme design. The equilibrium point of the overall closed-loop system is proved to be asymptotically stable through Lyapunov techniques and LaSalle’s Invariance Theorem. Hardware experiments are conducted on a self-built aerial transportation platform to verify the proposed controller’s basic and functional performance in terms of rapid anti-swing and accurate target position and cable length tracking. Note to Practitioners —This paper is motivated by the requirement to improve the autonomy level and payload swing suppression ability of the aerial transportation system through visual servoing techniques. By installing onboard monocular camera and the cable length adjustment mechanism, the application scope of the aerial transportation system can be significantly expanded. However, due to the “double” underactuated characteristic, the visual features couple with both the quadrotor motion and the payload motion, hence, it is quite challenging to realize visual servoing control for cable-suspended aerial transportation systems with simultaneous payload swing suppression and quadrotor positioning. Accounting for the foregoing problems, this paper proposes an image-based visual servoing anti-swing control scheme. With the elaborately constructed generalized virtual image feature signal, the designed controller could improve the anti-swing ability with a completed theoretical analysis. Furthermore, two groups of hardware experiments are conducted to validate the effectiveness of the suggested control method. In future studies, we intend to design more effective control scheme for payload delivery issue with consideration of the visibility of the mobile platform.

The unmanned aerial manipulator system has shown great application potential in rotor blade repairing, bridge inspection, and goods delivery. Allowing additional alternatives in tasks, dual-arm always provides more flexibility, versatility, and manipulability compared to a single arm. Unfortunately, the inherent defects of unignorable nonlinearities and complex dynamic coupling between the multirotor and the manipulator have limited the practical application of dual-arm aerial manipulator systems. It is noteworthy that the dynamic coupling between the multirotor UAV (unmanned aerial vehicle) and the dual-arm manipulator is much more complicated than the case of the single-arm, and may degrade the control performance significantly as the CoM (center of mass) of the system changes with the movement of the manipulator. To this end, this paper presents a novel control method based on dual-arm movement compensation. Specifically, the kinematic and dynamic model of the system is first established, based on which the force effect of the manipulator exerting on the multirotor UAV is estimated by the disturbance observer and then compensated. By using Lyapunov techniques, it is proven that the error signal can converge asymptotically. As far as we know, this paper presents the first controller design for dual-arm aerial manipulator systems with rigorous stability analysis. Finally, the effectiveness and robustness of the proposed method are verified through a significant number of comparison experiments, and the results of these experiments demonstrate that the proposed method can reduce the positioning error obviously compared to the comparison methods. Taking the PID method as the benchmark for comparison, it is obvious that the proposed method exhibits the greatest reduction in both maximum and average errors compared to the baseline method, indicating superior control precision than the other comparison methods. For the result of the proposed method in $\bm x$ -direction, one can find a substantial reduction ranging from 16.69% to 38.57% for the maximum error, and 22.24% to 45.66% for the mean error. Shifting focus to the $\bm y$ -direction, the error reduction for the proposed method is even more remarkable, ranging from 68.10% to 81.80% at maximum, and 66.31% to 86.33% for the mean error. As for the $\bm z$ -direction, the error reduction by the proposed method remained significant, ranging from 50.67% to 86.38% at maximum, and with a mean error reduction of 33.11% to 80.39%. Note to Practitioners —This paper is motivated by the problem of executing such tasks as load transportation and coordinate manipulation for aerial robots in flight. By integrating the dual-arm manipulator, the flexibility, versatility, and manipulability of the unmanned aerial manipulator system is further extended. However, the uncertain center of mass of the system during operation may badly increase the control difficulty of the dual-arm aerial manipulator system. Moreover, the strong nonlinearity and complex coupling existing between the multirotor and the manipulator also induce urgently solved problems in practical aerial manipulation tasks. To this end, this paper proposes a novel dual-arm movement compensation based control scheme by utilizing an elaborately designed disturbance observer to deal with the unestimated part of disturbance exerting on the multirotor by arm operation. With rigorous theoretical analysis, the convergence of the error signal is proven. Additionally, groups of hardware experiments further verify the effectiveness and robustness of the suggested control method. In future studies, we will improve the autonomy level of the system by integrating onboard sensors.