In the evolving landscape of high-speed agile quadrotor flight, achieving precise trajectory tracking at the platform’s operational limits is paramount. Controllers must handle actuator constraints, exhibit robustness to disturbances, and remain computationally efficient for safety-critical applications. In this work, we present a novel neural-augmented feedback controller for agile flight control. The controller addresses individual limitations of existing state-of-the-art control paradigms and unifies their strengths. We demonstrate the controller’s capabilities, including the accurate tracking of highly aggressive trajectories that surpass the feasibility of the actuators. Notably, the controller provides universal stability guarantees, enhancing its robustness and tracking performance even in exceedingly disturbance-prone settings. Its nonlinear feedback structure is highly efficient enabling fast computation at high update rates. Moreover, the learning process in simulation is both fast and stable, and the controller’s inherent robustness allows direct deployment to real-world platforms without the need for training augmentations or fine-tuning.

This work focuses on the agile transportation of liquids with robotic manipulators. In contrast to existing methods that are either computationally heavy, system/container specific or dependant on a singularity-prone pendulum model, we present a real-time slosh-free tracking technique. This method solely requires the reference trajectory and the robot’s kinematic constraints to output kinematically feasible joint space commands. The crucial element underlying this approach consists on mimicking the end-effector’s motion through a virtual quadrotor, which is inherently slosh-free and differentially flat, thereby allowing us to calculate a slosh-free reference orientation. Through the utilization of a cascaded proportional-derivative (PD) controller, this slosh-free reference is transformed into task space acceleration commands, which, following the resolution of a Quadratic Program (QP) based on Resolved Acceleration Control (RAC), are translated into a feasible joint configuration. The validity of the proposed approach is demonstrated by simulated and real-world experiments on a 7 DoF Franka Emika Panda robot.

Modeling the kinematics and dynamics of robotics systems with suspended loads using dual quaternions has not been explored so far. This paper introduces a new innovative control strategy using dual quaternions for UAVs with cable-suspended loads, focusing on the sling load lifting and tracking problems. By utilizing the mathematical efficiency and compactness of dual quaternions, a unified representation of the UAV and its suspended load’s dynamics and kinematics is achieved, facilitating the realization of load lifting and trajectory tracking. The simulation results have tested the proposed strategy’s accuracy, efficiency, and robustness. This study makes a substantial contribution to present this novel control strategy that harnesses the benefits of dual quaternions for cargo UAVs. Our work also holds promise for inspiring future innovations in under-actuated systems control using dual quaternions.

This paper presents a method to compute differentiable collision-free parametric corridors. In contrast to existing solutions that decompose the obstacle-free space into multiple convex sets, the continuous corridors computed by our method are smooth and differentiable, making them compatible with existing numerical techniques for learning and optimization. To achieve this, we represent the collision-free corridors as a path-parametric off-centered ellipse with a polynomial basis. We show that the problem of maximizing the volume of such corridors is convex, and can be efficiently solved. To assess the effectiveness of the proposed method, we examine its performance in a synthetic case study and subsequently evaluate its applicability in a real-world scenario from the KITTI dataset.

This work focuses on spatial time-optimal motion planning, a generalization of the exact time-optimal path following problem that allows a system to plan within a predefined space. In contrast to state-of-the-art methods, we drop the assumption of a given collision-free geometric reference. Instead, we present a three-stage motion planning method that solely relies on start and goal locations and a geometric representation of the environment to compute a time-optimal trajectory that is compliant with system dynamics and constraints. The proposed scheme first finds collision-free navigation corridors, second computes an obstacle-free Pythagorean Hodograph parametric spline along each corridor, and third, solves a spatially reformulated minimum-time optimization problem at each of these corridors. The spline obtained in the second stage is not a geometric reference, but an extension of the free space associated with its corridor, and thus, time-optimality of the solution is guaranteed. The validity of the proposed approach is demonstrated by a well-established planar example and benchmarked in a spatial system against state-of-the-art methodologies across a wide range of scenarios in highly congested environments. Video: https://youtu.be/zGExvnUEfOY

Autonomous systems and humans are increasingly sharing the same space. Robots work side by side or even hand in hand with humans to balance each other's limitations. Such cooperative interactions are ever more sophisticated. Thus, the ability to reason not just about a human's center of gravity position, but also its granular motion is an important prerequisite for human-robot interaction. Though, many algorithms ignore the multimodal nature of humans or neglect uncertainty in their motion forecasts. We present Motron, a multimodal, probabilistic, graph-structured model, that captures human's multimodality using probabilistic methods while being able to output deterministic maximum-likelihood motions and corresponding confidence values for each mode. Our model aims to be tightly integrated with the robotic planning-control-interaction loop; outputting physically feasible human motions and being computationally efficient. We demonstrate the performance of our model on several challenging real-world motion forecasting datasets, outperforming a wide array of generative/variational methods while providing state-of-the-art single-output motions if required. Both using significantly less computational power than state-of-the art algorithms.

Minimum-time navigation within constrained and dynamic environments is of special relevance in robotics. Seeking time-optimality, while guaranteeing the integrity of time-varying spatial bounds, is an appealing trade-off for agile vehicles, such as quadrotors. State-of-the-art approaches, either assume bounds to be static and generate time-optimal trajectories offline, or compromise time-optimality for constraint satisfaction. Leveraging nonlinear model predictive control and a path parametric reformulation of the quadrotor model, we present a real-time control that approximates time-optimal behavior and remains within dynamic corridors. The efficacy of the approach is evaluated by simulated results, showing itself capable of performing extremely aggressive maneuvers as well as stop-and-go and backward motions. Video: https://youtu.be/Apc8MCu7Yvo

We present SMORS, the first Soft fully actuated MultirOtoR System for multimodal locomotion. Unlike conventional hexarotors, SMORS is equipped with three rigid and three continuously soft arms, with each arm hosting a propeller. We create a bridge between the fields of soft and aerial robotics by mechanically coupling the actuation of a fully actuated flying platform with the actuation of a soft robotic manipulator. Each rotor is slightly tilted, allowing for full actuation of the platform. The soft components combined with the platform's full actuation allow for a robust interaction, in the form of efficient multimodal locomotion. In this work, we present the dynamical model of the platform, derive a closed-loop control, and present simulation results fortifying the robustness of the platform under a jumping-flying maneuver. We demonstrate in simulations that our multimodal locomotion approach can be more energy-efficient than the flight with a hexarotor.

There has been a considerable amount of recent work on high-speed micro-aerial vehicle flight in unknown and unstructured environments. Generally these approaches either use active sensing or fly slowly enough to ensure a safe braking distance with the relatively short sensing range of passive sensors. The former generally requires carrying large and heavy LIDARs and the latter only allows flight far away from the dynamic limits of the vehicle. One of the significant challenges for high-speed flight is the computational demand of trajectory planning at sufficiently high rates and length scales required in outdoor environments. We tackle both problems in this work by leveraging semantic information derived from an RGB camera on-board the vehicle. We first describe how to use semantic information to increase the effective range of perception on certain environment classes. Second, we present a sparse representation of the environment that is sufficiently lightweight for long distance path planning. We show how our approach outperforms more traditional metric planners which seek the shortest path, demonstrate the semantic planner's capabilities in a set of simulated and excessive real-world autonomous quadrotor flights in an urban environment.

There has been considerable recent work in motion planning for UAVs to enable aggressive, highly dynamic flight in known environments with motion capture systems. However, these existing planners have not been shown to enable the same kind of flight in unknown, outdoor environments. In this paper we present a receding horizon planning architecture that enables the fast replanning necessary for reactive obstacle avoidance by combining three techniques. First, we show how previous work in computationally efficient, closed-form trajectory generation method can be coupled with spatial partitioning data structures to reason about the geometry of the environment in real-time. Second, we show how to maintain safety margins during fast flight in unknown environments by planning velocities according to obstacle density. Third, our receding-horizon, sampling-based motion planner uses minimum-jerk trajectories and closed-loop tracking to enable smooth, robust, high-speed flight with the low angular rates necessary for accurate visual-inertial navigation. We compare against two state-of-the-art, reactive motion planners in simulation and benchmark solution quality against an offline global planner. Finally, we demonstrate our planner over 80 flights with a combined distance of 22km of autonomous quadrotor flights in an urban environment at speeds up to 9.4ms $^{-1}$.

In this paper, we consider a non-conventional hexarotor whose propellers can be simultaneously tilted about two orthogonal axes: in this way, its underactuation degree can be easily adapted to the task at hand. For a given tilt profile, the minimum-energy trajectory between two prescribed boundary states is explicitly determined by solving an optimal control problem with respect to the angular accelerations of the six brushless motors. We also perform, for the first time, a systematic study of the singularities of the control allocation matrix of the hexarotor, showing the presence of subtle singular configurations that should be carefully avoided in the design phase. Numerical experiments conducted with the FAST-Hex platform illustrate the theory and delineate the pros and cons of dual-tilting paradigm in terms of maneuverability and energy efficiency.

A class of abstract aerial robotic systems is introduced, the laterally bounded force vehicles. in which most of the control authority is expressed along a principal thrust direction, while along the lateral directions a t smaller and possibly null) force may be exploited to achieve full-pose tracking. This class approximates platforms endowed with noncollinear rotors that can modify the orientation of the total thrust in a body frame. If made possible by the force constraints, the proposed SE(3)-based control strategy achieves the independent tracking of position-plus-orientation trajectories. The method, which is proven using a Lyapunov technique, deals seamlessly with both underactuated and fully actuated platforms, and guarantees at least the position tracking in the case of an unfeasible full-pose reference trajectory. Several experimental tests are presented that dearly show the approach practicability and the sharp improvement with respect to state of the art.

In this paper, we shed light on two fundamental actuation capabilities of multirotors. The first is the degree of coupling between the total force and total moment generated by the propellers. The second is the ability to robustly fly completely still in place after the loss of one or more propellers, in the case of mono-directional propellers. These are formalized through the definition of some algebraic conditions on the control allocation matrices. The theory is valid for any multirotor, with arbitrary number, position, and orientation of the propellers. As a show case for the general theory, we demonstrate that standard star-shaped hexarotors with collinear propellers are not able to robustly fly completely still at a constant spot using only five of their six propellers. To deeply understand this counterintuitive result, it is enough to apply our theory, which clarifies the role of the tilt angles and locations of the propellers. The theory is also able to explain why, on the contrary, both the tilted star-shaped and the Y-shaped hexarotors can fly with only five out of six propellers. The analysis is validated with both simulations and extensive experimental results showing recovery control after rotor losses.

Standard hexarotors are often mistakenly considered `by definition' fail-safe multi-rotor platforms because of the two additional propellers when compared to quadrotors. However this is not true, in fact, a standard hexarotor cannot statically hover with `only' five propellers. In this paper we provide a set of new general algebraic conditions to ensure static hover for any multi-rotor platform with any number of generically oriented rotors. These are elegantly formulated as the full-rankness of the control moment input matrix, and the non-orthogonality between its null-space and the row space of the control force input matrix. Input saturations and safety margins are also taken into account with an additional condition on the null-space of control moment input matrix. A deep analysis on the hoverability properties is then carried out focusing on the propeller loss in a hexarotor platform. Leveraging our general results we explain why a standard hexarotor is not robust and how it can be made robust thanks to a particular tilt of the rotors. We finally propose a novel cascaded controller based on a preferential direction in the null-space of the control moment input matrix for the large class of statically hoverable multi-rotors, which goes far beyond standard platforms, and we apply this controller to the case of failed tilted hexarotor.

This paper presents the design, control, and experimental validation of a novel fully-actuated aerial robot for physically interactive tasks, named Tilt-Hex. We show how the Tilt-Hex, a tilted-propeller hexarotor is able to control the full pose (position and orientation independently) using a geometric control, and to exert a full-wrench (force and torque independently) with a rigidly attached end-effector using an admittance control paradigm. An outer loop control governs the desired admittance behavior and an inner loop based on geometric control ensures pose tracking. The interaction forces are estimated by a momentum based observer. Control and observation are made possible by a precise control and measurement of the speed of each propeller. An extensive experimental campaign shows that the Tilt-Hex is able to outperform the classical underactuated multi-rotors in terms of stability, accuracy and dexterity and represent one of the best choice at date for tasks requiring aerial physical interaction.

We present FAST-Hex, a novel UAV concept which is able to smoothly change its configuration from underactuated to fully actuated by using only one additional motor that tilts all propellers at the same time. FAST-Hex can adapt to the task at hand by finely tuning its configuration from the efficient (but underactuated) flight (typical of coplanar multi-rotor platforms) to the full-pose-tracking (but less efficient) flight, which is attainable by non-coplanar multi-rotors. We also introduce a novel full-pose geometric controller for generic multi-rotors (not only the FAST-Hex) that outperforms classical inverse dynamics approaches. The controller receives as input any reference pose in ℝ3×SO(3) (3D position + 3D orientation). Exact tracking is achieved if the reference pose is feasible with respect to the propeller spinning rate saturations. In case of unfeasibility a new feasible desired trajectory is generated online giving priority to the positional part. The new controller is tested with the FAST-Hex but can be used for many other multi-rotor platforms: underactuated, slightly fully-actuated and completely fully-actuated.

Mobility of a hexarotor UAV in its standard configuration is limited, since all the propeller force vectors are parallel and they achieve only 4-DoF actuation, similar, e.g., to quadrotors. As a consequence, the hexarotor pose cannot track an arbitrary trajectory while the center of mass is tracking a position trajectory. In this paper, we consider a different hexarotor architecture where propellers are tilted, without the need of any additional hardware. In this way, the hexarotor gains a 6-DoF actuation which allows to independently reach positions and orientations in free space and to be able to exert forces on the environment to resist any wrench for aerial manipulation tasks. After deriving the dynamical model of the proposed hexarotor, we discuss the controllability and the tilt angle optimization to reduce the control effort for the specific task. An exact feedback linearization and decoupling control law is proposed based on the input-output mapping, considering the Jacobian and task acceleration, for non-linear trajectory tracking. The capabilities of our approach are shown by simulation results.

In this paper the problem of a quadrotor that physically interacts with the surrounding environment through a rigid tool is considered. We present a theoretical design that allows to exert an arbitrary 3D force by using a standard near-hovering controller that was originally developed for contact-free flight control. This is achieved by analytically solving the nonlinear system that relates the quadrotor state, the force exerted by the rigid tool on the environment, and the near-hovering controller action at the equilibrium points, during any generic contact. Stability of the equilibria for the most relevant actions (pushing, releasing, lifting, dropping, and left-right shifting) are proven by means of numerical analysis using the indirect Lyapunov method. An experimental platform, including a suitable tool design, has been developed and used to validate the theory with preliminary experiments.

In this work we present a novel concept of a quadrotor UAV with tilting propellers. Standard quadrotors are limited in their mobility because of their intrinsic underactuation (only 4 independent control inputs vs. their 6-dof pose in space). The quadrotor prototype discussed in this paper, on the other hand, has the ability to also control the orientation of its 4 propellers, thus making it possible to overcome the aforementioned underactuation and behave as a fully-actuated flying vehicle. We first illustrate the hardware/software specifications of our recently developed prototype, and then report the experimental results of some preliminary, but promising, flight tests which show the capabilities of this new UAV concept.

Standard quadrotor UAVs possess a limited mobility because of their inherent underactuation, i.e., availability of 4 independent control inputs (the 4 propeller spinning velocities) vs. the 6 dofs parameterizing the quadrotor position/ orientation in space. As a consequence, the quadrotor pose cannot track an arbitrary trajectory over time (e.g., it can hover on the spot only when horizontal). In this paper, we propose a novel actuation concept in which the quadrotor propellers are allowed to tilt about their axes w.r.t. the main quadrotor body. This introduces an additional set of 4 control inputs which provides full actuation to the quadrotor position/orientation. After deriving the dynamical model of the proposed quadrotor, we formally discuss its controllability properties and propose a nonlinear trajectory tracking controller based on dynamic feedback linearization techniques. The soundness of our approach is validated by means of simulation results.