Aerial manipulation for safe physical interaction with their environments is gaining significant momentum in robotics research. In this paper, we present a disturbance-observer-based safety-critical control for a fully actuated aerial manipulator interacting with both static and dynamic structures. Our approach centers on a safety filter that dynamically adjusts the desired trajectory of the vehicle's pose, accounting for the aerial manipulator's dynamics, the disturbance observer's structure, and motor thrust limits. We provide rigorous proof that the proposed safety filter ensures the forward invariance of the safety set—representing motor thrust limits—even in the presence of disturbance estimation errors. To demonstrate the superiority of our method over existing control strategies for aerial physical interaction, we perform comparative experiments involving complex tasks, such as pushing against a static structure and pulling a plug firmly attached to an electric socket. Furthermore, to highlight its repeatability in scenarios with sudden dynamic changes, we perform repeated tests of pushing a movable cart and extracting a plug from a socket. These experiments confirm that our method not only outperforms existing methods but also excels in handling tasks with rapid dynamic variations.

Aerial physical interaction (APhI) with a multirotor-based platform such as pushing a heavy object demands generation of a sufficiently large interaction force while maintaining the stability. Such requirement can cause rotor saturation, because the rotor thrust enlarged for interaction force may leave a reduced margin for attitude stabilization. We first design an H-shaped coaxial tiltrotor that can generate a sufficiently large interaction force than a conventional multirotor. We then propose an overall framework composed of high-level robust controller and low-level control allocation for the coaxial tiltrotor to ensure robustness against uncertain motion of the unknown interacting object and to overcome the saturation issue. To guarantee the robustness at all time, we design a controller based on a nonlinear disturbance observer (DOB). Then, we formulate a problem of computing low-level actuator inputs avoiding rotor saturation as a tractable nonlinear optimization problem, which can be solved real-time. The proposed framework is validated in extensive real-world experiments where the 3.3 kg tiltrotor successfully pushes a cart weighing up to 60 kg. An ablation study with the tiltrotor shows effectiveness of the proposed control allocation law in avoiding rotor saturation. Furthermore, a comparative experiment with a conventional multirotor shows failure in the same setting, which validates the use of the coaxial tiltrotor. An experimental video can be found athttps://youtu.be/Gdmcmoz_UjUNote to Practitioners—The motivation of this work is to enable heavy object manipulation, especially pushing operation, using a multirotor platform. To push a heavy object, which has not been treated in existing works, is challenging due to the presence of a large unknown interaction wrench and rotor saturation issue. To resolve this problem, we first build an H-shaped coaxial tiltrotor that can effectively utilize rotor thrusts to generate horizontal interaction force. Then, a robust controller is designed to address uncertainty in the interaction wrench for the tiltrotor. Finally, we propose an optimization-based control allocation to avoid rotor saturation. Real-world experiments including heavy object pushing and ablation study with respect to the control allocation law are conducted to show the effectiveness of the proposed framework. We validate the use of the coaxial tiltrotor in additional comparative experiments with a conventional multirotor which fails in pushing a 60 kg cart. The proposed framework can be utilized in various applications such as disaster relief operations, emergency rescue and aerial delivery.

Aerial unperching of multirotors has received little attention as opposed to perching that has been investigated to elongate operation time. This study presents a new aerial robot capable of both perching and unperching autonomously on/from a ferromagnetic surface during flight, and a switching controller to avoid rotor saturation and mitigate overshoot during transition between free-flight and perching. To enable stable perching and unperching maneuvers on/from a vertical surface, a lightweight (≈ 1 kg), fully actuated tiltrotor that can hover at 90◦pitch angle is first developed. We design a perching/unperching module composed of a single servomotor and a magnet, which is then mounted on the tiltrotor. A switching controller including exclusive control modes for transitions between free-flight and perching is proposed. Lastly, we propose a simple yet effective strategy to ensure robust perching in the presence of measurement and control errors and avoid collisions with the perching site immediately after unperching. We validate the proposed framework in experiments where the tiltrotor successfully performs perching and unperching on/from a vertical surface during flight. We further show effectiveness of the proposed transition mode in the switching controller by ablation studies where large overshoot and even collision with a perching site occur. To the best of the authors’ knowledge, this work presents the first autonomous aerial unperching framework using a fully actuated tiltrotor.

Autonomous aerial manipulation requires the capability to handle inevitable dynamic changes during physical interaction. Previously, very few studies have addressed the stability and transient performance of the scenarios involving abrupt changes in dynamics. This paper proposes a hybrid controller enhancing transient performance for an aerial manipulator extracting an object wedged in a static structure. This task incurs a significant jump in the interaction force on the end-effector so that the analysis using the concept of hybrid dynamical systems is required. To demonstrate the dynamic characteristics of the object-extracting aerial manipulator, we derive the dynamic equations for two flight modes, i.e., free-flight and object-extracting, and the rule of state jumps. Also, we design control strategies which enhance the transient performance during flight mode transition. Then, the stability of the proposed control law is proven, and the overshoot reduction after the object extraction is analyzed. To show the improved performance, we conduct plug-pulling experiments with a quadrotor-based aerial manipulator using the proposed controller and two different existing controllers. The comparative results confirm that our controller enables the aerial manipulator to maintain its stability after the flight mode transition and shows the best transient performance in overshoot minimization among three controllers.Note to Practitioners—The motivation for this article is the desire to prevent unexpected collisions between obstacles and an aerial manipulator after the vehicle extracts a wedged object from a static structure. To resolve this problem, we present a hybrid control method for such tasks while avoiding an excessive overshoot after the extraction. This method can be utilized in tasks involving abrupt changes in the dynamic model such as retrieving a device attached to a tall structure, reclaiming an object in disaster recovery, or pulling a plug out of a socket. Unlike existing methods, the proposed method simultaneously considers the stabilityandthe initial overshoot right after pulling the object out of the structure, by employing a disturbance observer (DOB) in a hybrid control structure. It can be utilized for the aerial manipulator to avoid collision in a narrow space or to keep it in a safe operation envelope even though the task requires producing a relatively large pulling force.

This study presents a globally defined dynamics for a conventional multirotor equipped with a single$n\mathbf{-DOF}$manipulator using modified Lagrangian dynamics. This enables the reformulation of entire dynamics directly on$\text{SO}(3)$without exploiting any local coordinates, and thus problems such as the singularity of Euler angles can be avoided. Since skew-symmetric property of Coriolis matrix$C$and inertia matrix facilitates stability analysis, we propose a method to compute$C$which guarantees the skew-symmetric property by considering$C$as a summation of two sub-matrices. Then, a geometric tracking controller is designed based on decoupled dynamics applying passive decomposition. The proposed controller guarantees almost global region of attraction. We validate our method via consecutive aerial flipping experiments.

This study presents a new hardware design and control of a minimally actuated 5 control degrees of freedom (CDoF) quadrotor-based tiltrotor. The proposed tiltrotor possesses several characteristics distinct from those found in existing works, including: 1) minimal number of actuators for 5 CDoF, 2) large margin to generate interaction force during aerial physical interaction (APhI), and 3) no mechanical obstruction in thrust direction rotation. Thanks to these properties, the proposed tiltrotor is suitable for perching-enabled APhI since it can hover parallel to an arbitrarily oriented surface and can freely adjust its thrust direction. To fully control the 5-CDoF of the designed tiltrotor, we construct an asymptotically stabilizing controller with stability analysis. The proposed tiltrotor design and controller are validated in experiments where the first two experiments of x, y position tracking and pitch tracking show controllability of the added CDoF compared to a conventional quadrotor. Finally, the last experiment of perching and cart pushing demonstrates the proposed tiltrotor's applicability to perching-enabled APhI.

In this paper, an autonomous aerial manipulation task of pulling a plug out of an electric socket is conducted, where maintaining the stability and robustness is challenging due to sudden disappearance of a large interaction force. The abrupt change in the dynamical model before and after the separation of the plug can cause destabilization or mission failure. To accomplish aerial plug-pulling, we employ the concept of hybrid automata to divide the task into three operative modes, i.e, wire-pulling, stabilizing, and free-flight. Also, a strategy for trajectory generation and a design of disturbance-observer-based controllers for each operative mode are presented. Furthermore, the theory of hybrid automata is used to prove the stability and robustness during the mode transition. We validate the proposed trajectory generation and control method by an actual wire-pulling experiment with a multirotor-based aerial manipulator.

Motion planners for mobile robots in unknown environments face the challenge of simultaneously maintaining both robustness against unmodeled uncertainties and persistent feasibility of the trajectory-finding problem. That is, while dealing with uncertainties, a motion planner must update its trajectory, adapting to the newly revealed environment in real-time; failing to do so may involve unsafe circumstances. Many existing planning algorithms guarantee these by maintaining the clearance needed to perform an emergency brake, which is itself a robust and persistently feasible maneuver. However, such maneuvers are not applicable for systems in which braking is impossible or risky, such as fixed-wing aircraft. To that end, we propose a real-time robust planner that recursively guarantees persistent feasibility without any need of braking. The planner ensures robustness against bounded uncertainties and persistent feasibility by constructing a loop of sequentially composed funnels, starting from the receding horizon local trajectory’s forward reachable set. We implement the proposed algorithm for a robotic car tracking a speed-fixed reference trajectory. The experiment results show that the proposed algorithm can be run at faster than 16 Hz, while successfully keeping the system away from entering any dead end, to maintain safety and feasibility.

Automation of excavation tasks requires real-time trajectory planning satisfying various constraints. To guarantee both constraint feasibility and real-time trajectory re-plannability, we present an integrated framework for real-time optimization-based trajectory planning of a hydraulic excavator. The proposed framework is composed of two main modules: a global planner and a real-time local planner. The global planner computes the entire global trajectory considering excavation volume and energy minimization while the local counterpart tracks the global trajectory in a receding horizon manner, satisfying dynamic feasibility, physical constraints, and disturbance-awareness. We validate the proposed planning algorithm in a simulation environment where two types of operations are conducted in the presence of emulated disturbance from hydraulic friction and soil-bucket interaction: shallow and deep excavation. The optimized global trajectories are obtained in an order of a second, which is tracked by the local planner at faster than 30 Hz. To the best of our knowledge, this work presents the first real-time motion planning framework that satisfies constraints of a hydraulic excavator, such as force/torque, power, cylinder displacement, and flow rate limits.

Existing studies for environment interaction with an aerial robot have been focused on interaction with static surroundings. However, to fully explore the concept of an aerial manipulation, interaction with moving structures should also be considered. In this paper, a multirotor-based aerial manipulator opening a daily-life moving structure, a hinged door, is presented. In order to address the constrained motion of the structure and to avoid collisions during operation, model predictive control (MPC) is applied to the derived coupled system dynamics between the aerial manipulator and the door involving state constraints. By implementing a constrained version of differential dynamic programming (DDP), MPC can generate position setpoints to the disturbance observer (DOB)-based robust controller in real-time, which is validated by our experimental results.

Planning a trajectory with guaranteed safety is a core part for a risk-free flight of a multirotor. If a trajectory planner only aims to ensure safety, it may generate trajectories which overly bypass risky regions and prevent the system from achieving specific missions. This work presents a robust trajectory planning algorithm which simultaneously guarantees the safety and reachability to the target state in the presence of unknown disturbances. We first characterize how the forward and backward reachable sets (FRSs and BRSs) are constructed by using Hamilton-Jacobi reachability analysis. Based on the analysis, we present analytic expressions for the reachable sets and then propose minimal ellipsoids which closely approximate the reachable sets. In the planning process, we optimize the reference trajectory to connect the FRSs and BRSs, while avoiding obstacles. By combining the FRSs and BRSs, we can guarantee that any state inside of the initial set reaches the target set. We validate the proposed algorithm through a simulation of traversing a narrow gap.

In this paper, we introduce a cargo transportation method with a new type of multi-rotor UAV platform known as T3-multirotor, to achieve stable and constant flight performance regardless of the type of cargo attached to the fuselage. The T3-multirotor, which consists of the `Thrust Generating Part' and the `Fuselage Part', can directly control the relative attitude between the two parts using the novel servomechanism. By utilizing the servomechanism with the proposed relative attitude control strategy, the T3-multirotor with cargo attached to the fuselage part can behave as a multi-rotor with only the moment of inertia of the thrust generating part during entire transportation. This allows the T3-multirotor to achieve the reliable performance in the event of any cargo being attached to the fuselage, achieving stable platform motion control. Detailed hardware description and dynamic analysis of T3-Multirotor is performed in this paper, and the validity of the proposed control strategy is also analyzed. The feasibility of the proposed control strategy is verified through experimental results with analysis.