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This paper investigates the aeroacoustic interactions of small hovering rotors, using both experiments and computations. The experiments were conducted in an anechoic chamber with arrays of microphones setup to evaluate the azimuthal and polar directivity. The computational methodology consists of high fidelity detached eddy simulations coupled to the Ffowcs-Williams and Hawkings equation, supplemented by a trailing edge broadband noise code. The aerodynamics and aeroacoustics of a single rotor are investigated first. The simulations capture a Reynolds number effect seen in the performance parameters that results in the coefficient of thrust changing with the RPM. The acoustic analysis enables the identification of self-induced noise sources. Next, dual side-by-side rotors are studied in both counter-rotating and co-rotating configurations to quantify the impact of their interactions. Higher harmonics appear due to the interactions and it is verified that the counter-rotating case leads to more noise and a less uniform azimuthal directivity. Difficulties that arise when trying to validate small rotor calculations against experiments are discussed. Comparisons of computational and experimental results yield further insight into the noise mechanisms that are captured by each methodology. 

We present a novel haptic teleoperation approach that considers not only the safety but also the stability of a teleoperation system. Specifically, we build upon previous work on haptic shared control, which generates a reference haptic feedback that helps the human operator to safely navigate the robot but without taking away their control authority. Crucially, in this approach the force rendered to the user is not directly reflected in the motion of the robot (which is still directly controlled by the user); however, previous work in the area neglected to consider the possible instabilities in feedback loop generated by a user that over-responds to the haptic force. In this paper we introduce a differential constraint on the rendered force that makes the system finite-gain L2 stable; the constraint results in a Quadratically Constrained Quadratic Program (QCQP), for which we provide a closed-form solution. Our constraint is related to, but less restrictive than, the typical passivity constraint used in previous literature. We conducted an experimental simulation in which a human operator flies a UAV near an obstacle to evaluate the proposed method. 

Applications of micro unmanned aerial vehicles (UAVs) are gradually expanding into complex urban and natural environments. Despite noticeable progress, flying robots in obstacle-rich environments is still challenging. On-board processing for detecting and avoiding obstacles is possible, but at a significant computational expense, and with significant limitations (e.g., for obstacles with small cross sections, such as wires). A low-cost alternative is to mitigate physical contacts through a cage or other similar protective devices. In this paper, we propose to transform these passive protective devices into functional sensors: we introduce a suspended rim combined with a central base measuring the relative displacement of the rim; we provide a full mechanical design, and derive solutions to the inverse kinematics for recovering the collision direction in real time. As a proof of concept, we show the benefits of this novel form of sensing by embedding it in a traditional particle filter for self-localization in a known environment; our experiments show that localization is possible with a minimal sacrifice in payload capacity. 

In this paper, we present a simple geometric attitude controller that is globally, exponentially stable. To overcome the topological restriction, the controller is designed to follow a reference trajectory that in turn converges to the desired equilibrium (making it discontinuous in the initial conditions, but continuous in time). The system and reference dynamics are studied as a single augmented system that can be analyzed and tuned simultaneously. The controller's stability is proved using contraction analysis (on the manifold), and the bounds on the convergence rate can be found via a semi-definite program with linear matrix inequalities. Additionally, our approach allows the use of the Nelder-Mead algorithm to automatically select controller gains and reference trajectory parameters by optimizing the aforementioned bounds. The resulting controller is verified through simulations. 

A multirotor trim module is developed for the HPCMP CREATETM-AV Helios rotorcraft simulation code. Trimmed free-flight simulation results are presented for two multirotor configurations, using rotor frequencies and aircraft attitudes as the control variables. The loose-coupling procedure is used to achieve trim, where aerodynamic loading on the rotor blades and fuselage are computed using a simplified aerodynamic model, and modified at each coupling iteration using the airloads computed by the higher fidelity CFD based aerodynamics. Two different optimization methods are tested: a least-square regression algorithm, with the norm of the loads at the center of gravity as the objective function, and a nonlinear constrained optimization code, with the total power as the objective function, and with constraints applied to satisfy trim. First, a commercial small-scale UAV is simulated in forward flight. A reference model for midscale UAM applications is then trimmed in hover to demonstrate the module’s ability to model and trim a complex configuration. 

In this paper we propose a new analysis of a simple geometric attitude controller, showing that it is locally exponentially stable and almost globally asymptotically stable; the exponential convergence region is much larger than existing non-hybrid geometric controllers (and covers almost the entire rotation space). The controller's stability is proved using contraction analysis combined with optimization. The key in this combination is that the contraction metric is a linear matrix inequality with a special structure stemming from the configuration manifold SO(3). As an additional contribution, we propose a general framework to automatically select controller gains by optimizing bounds on the system's convergence rate; while this principle is quite general, its application is particularly straightforward with our contraction-based analysis. We demonstrate our results through simulations. 

Computational fluid dynamics (CFD) simulations of a small quadrotor were conducted using CREATETM-AV Helios. Two near-body CFD solvers and multiple turbulence models including transition models available in Helios were tested. The DJI Phantom 3 was chosen as a representative configuration because it has been studied extensively and is typical of commercial unmanned aerial vehicles. The airfoil at three-quarters span of the rotor geometry was extracted to perform both two-dimensional (2D) airfoil and three-dimensional (3D) wing studies in order to determine appropriate grid spacings for use with the various models. Isolated rotor simulations for DJI Phantom 3 rotor in hover utilizing appropriate grids were completed for fully turbulent and turbulence transition models. The predicted thrust from all of the methods lie within experimental uncertainty. The Spalart Allmaras model gave consistent results across the two CFD solvers and was most computationally efficient. As such it was chosen for the simulations of the full quadrotor performance in hover. The results indicate that a transition model is not required in order to obtain satisfactory thrust predictions as compared to experiment for a small quadrotor in hover using the Helios package. However, the figure of merit is underpredicted by both fully turbulent and transition models. Therefore, the effect of transition modeling on torque prediction needs further investigation.