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Recent advances in aerial robotics have enabled the use of multirotor vehicles for autonomous payload transportation. Resorting only to classical methods to reliably model a quadrotor carrying a cable-slung load poses significant challenges. On the other hand, purely data-driven learning methods do not comply by design with the problem's physical constraints, especially in states that are not densely represented in training data. In this work, we explore the use of physics informed neural networks to learn an end-to-end model of the multirotor-slung-load system and, at a given time, estimate a sequence of the future system states. An LSTM encoder decoder with an attention mechanism is used to capture the dynamics of the system. To guarantee the cohesiveness between the multiple predicted states of the system, we propose the use of a physics-based term in the loss function, which includes a discretized physical model derived from first principles together with slack variables that allow for a small mismatch between expected and predicted values. To train the model, a dataset using a real-world quadrotor carrying a slung load was curated and is made available. Prediction results are presented and corroborate the feasibility of the approach. The proposed method outperforms both the first principles physical model and a comparable neural network model trained without the physics regularization proposed.

This paper proposes a novel constructive barrier feedback for reactive collision avoidance between two agents. It incorporates this feature in a formation tracking control strategy for a group of 2nd-order dynamic robots defined in three-dimensional space. Using only relative measurements between neighboring agents, we propose an elegant decentralized controller as the sum of a nominal tracking controller and the constructive barrier feedback for leader-follower formations under a directed single-spanning tree graph topology. The key ingredient is the use of divergent flow as a dissipative term, which slows down the relative velocity in the direction of the neighboring robots without compromising the nominal controller's performance. Compared to traditional barrier function-based optimization controllers, the proposed constructive barrier feedback avoids feasibility issues and results in more computationally efficient control algorithms with systematic equilibrium analysis.

Developing and testing novel control and motion planning algorithms for aerial vehicles can be a challenging task, with the robotics community relying more than ever on 3D simulation technologies to evaluate the performance of new algorithms in a variety of conditions and environments. In this work, we introduce the Pegasus Simulator, a modular framework implemented as an NVIDIA Isaac Sim extension that enables real-time simulation of multiple multirotor vehicles in photo-realistic environments, while providing out-of-the-box integration with the widely adopted PX4-Autopilot and ROS2 through its modular implementation and intuitive graphical user interface. To demonstrate some of its capabilities, a nonlinear controller was implemented and simulation results for two drones performing aggressive flight maneuvers are presented. Code and documentation for this framework are also provided as supplementary material., Comment: This paper has been accepted for publication in the 2024 International Conference on Unmanned Aircraft Systems (ICUAS), IEEE

This paper addresses the problem of bearing leader-follower formation control in three-dimensional space by exploring the persistence of excitation (PE) of the desired formation. Using only bearing and relative velocity measurements, distributed control laws are derived for a group of agents with double-integrator dynamics. The key contribution is that the exponential stabilization of the actual formation to the desired one in terms of both shape and scale is guaranteed as long as the PE conditions on the desired formation are satisfied. The approach generalizes stability results provided in prior work for leader-first follower (LFF) structures which are based on bearing rigidity and constraint consistency to ensure the exponential stabilization of the actual formation to a desired static geometric pattern up to a scale factor. Simulations results are provided to illustrate the performance of the proposed control method., Comment: arXiv admin note: text overlap with arXiv:2103.06024, arXiv:2009.00209

This paper considers the problem of controlling a quadrotor to go through a window and land on a planar target, the landing pad, using an Image-Based Visual Servo (IBVS) controller that relies on sensing information from two on-board cameras and an IMU. The maneuver is divided into two stages: crossing the window and landing on the pad. For the first stage, a control law is proposed that guarantees that the vehicle will not collide with the wall containing the window and will go through the window with non-zero velocity along the direction orthogonal to the window, keeping at all times a safety distance with respect to the window edges. For the landing stage, the proposed control law ensures that the vehicle achieves a smooth touchdown, keeping at all time a positive height above the plane containing the landing pad. For control purposes, the centroid vectors provided by the combination of the spherical image measurements of a collection of landmarks (corners) for both the window and the landing pad are used as position measurement. The translational optical flow relative to the wall, window edges, and landing plane is used as velocity cue. To achieve the proposed objective, no direct measurements nor explicit estimate of position or velocity are required. Simulation and experimental results are provided to illustrate the performance of the presented controller.

This paper addresses the problem of time-varying bearing formation control in $d$ $(d\ge 2)$-dimensional Euclidean space by exploring Persistence of Excitation (PE) of the desired bearing reference. A general concept of Bearing Persistently Exciting (BPE) formation defined in $d$-dimensional space is here fully developed. By providing a desired formation that is BPE, distributed control laws for multi-agent systems under both single- and double-integrator dynamics are proposed using bearing measurements (along with velocity measurements when the agents are described by double-integrator dynamics), which guarantee uniform exponential stabilization of the desired formation in terms of shape and scale. A key contribution of this work is to show that the classical bearing rigidity condition on the graph topology, required for achieving the stabilization of a formation up to a scaling factor, is relaxed and extended in a natural manner by exploring PE conditions imposed either on a specific set of desired bearing vectors or on the whole desired formation. Simulation results are provided to illustrate the performance of the proposed control method., Comment: arXiv admin note: text overlap with arXiv:2009.00209

This paper presents a method for planning optimal trajectories with a team of Unmanned Aerial Vehicles (UAVs) performing autonomous cinematography. The method is able to plan trajectories online and in a distributed manner, providing coordination between the UAVs. We propose a novel non-linear formulation for this challenging problem of computing multi-UAV optimal trajectories for cinematography; integrating UAVs dynamics and collision avoidance constraints, together with cinematographic aspects like smoothness, gimbal mechanical limits and mutual camera visibility. We integrate our method within a hardware and software architecture for UAV cinematography that was previously developed within the framework of the MultiDrone project; and demonstrate its use with different types of shots filming a moving target outdoors. We provide extensive experimental results both in simulation and field experiments. We analyze the performance of the method and prove that it is able to compute online smooth trajectories, reducing jerky movements and complying with cinematography constraints., Comment: This paper has been published as: Optimal trajectory planning for cinematography with multiple Unmanned Aerial Vehicles. Alfonso Alcantara and Jesus Capitan and Rita Cunha and Anibal Ollero. Robotics and Autonomous Systems. 103778 (2021) 10.1016/j.robot.2021.103778

This paper addresses the problem of bearing-only formation control in $d~(d\geq 2)$-dimensional space by exploring persistence of excitation (PE) of the desired bearing reference. By defining a desired formation that is bearing PE, distributed bearing-only control laws are proposed, which guarantee exponential stabilization of the desired formation only up to a translation vector. The key outcome of this approach relies in exploiting the bearing PE to significantly relax the conditions imposed on the graph topology to ensure exponential stabilization, when compared to the bearing rigidity conditions, and to remove the scale ambiguity introduced by bearing vectors. Simulation results are provided to illustrate the performance of the proposed control method.

This paper presents a system for the execution of autonomous cinematography missions with a team of drones. The system allows media directors to design missions involving different types of shots with one or multiple cameras, running sequentially or concurrently. We introduce the complete architecture, which includes components for mission design, planning and execution. Then, we focus on the components related to autonomous mission execution. First, we propose a novel parametric description for shots, considering different types of camera motion and tracked targets; and we use it to implement a set of canonical shots. Second, for multi-drone shot execution, we propose distributed schedulers that activate different shot controllers on board the drones. Moreover, an event-based mechanism is used to synchronize shot execution among the drones and to account for inaccuracies during shot planning. Finally, we showcase the system with field experiments filming sport activities, including a real regatta event. We report on system integration and lessons learnt during our experimental campaigns.

This is a complementary document to the paper presented in [1], to provide more detailed proofs for some results. The main paper addresses the problem of trajectory tracking control of autonomous rotorcraft in operation scenarios where only relative position measurements obtained from LiDAR sensors are possible. The proposed approach defines an alternative kinematic model, directly based on LiDAR measurements, and uses a trajectory-dependent error space to express the dynamic model of the vehicle. An LPV representation with piecewise affine dependence on the parameters is adopted to describe the error dynamics over a set of predefined operating regions, and a continuous-time $H_2$ control problem is solved using LMIs and implemented within the scope of gain-scheduling control theory., Comment: [1] B. J. Guerreiro, C. Silvestre, R. Cunha, and D. Cabecinhas, Lidar-based control of autonomous rotorcraft for the inspection of pier-like structures, IEEE Transactions in Control Systems Technology, 2017. (to appear)