Heavier-than-air flight at any scale is energetically expensive. This is greatly exacerbated at small scales and has so far presented an insurmountable obstacle for untethered flight in insect-sized (mass less than 500 milligrams and wingspan less than 5 centimetres) robots. These vehicles1–4 thus need to fly tethered to an offboard power supply and signal generator owing to the challenges associated with integrating onboard electronics within a limited payload capacity. Here we address these challenges to demonstrate sustained untethered flight of an insect-sized flapping-wing microscale aerial vehicle. The 90-milligram vehicle uses four wings driven by two alumina-reinforced piezoelectric actuators to increase aerodynamic efficiency (by up to 29 per cent relative to similar two-wing vehicles5) and achieve a peak lift-to-weight ratio of 4.1 to 1, demonstrating greater thrust per muscle mass than typical biological counterparts6. The integrated system of the vehicle together with the electronics required for untethered flight (a photovoltaic array and a signal generator) weighs 259 milligrams, with an additional payload capacity allowing for additional onboard devices. Consuming only 110–120 milliwatts of power, the system matches the thrust efficiency of similarly sized insects such as bees7. This insect-scale aerial vehicle is the lightest thus far to achieve sustained untethered flight (as opposed to impulsive jumping8 or liftoff9). Sustained flight of an insect-sized flapping-wing aerial vehicle weighing just 259 milligrams that does not need to fly tethered to an off-board power supply is demonstrated.

Untethered flight of an insect-sized flapping-wing microscale aerial vehicle

A boundary control approach is used to control a two-link rigid-flexible wing in this article. Its design is based on the principle of bionics to improve the mobility and the flexibility of aircraft. First, a series of partial differential equations (PDEs) and ordinary differential equations (ODEs) are derived through the Hamilton's principle. These PDEs and ODEs describe the governing equations and the boundary conditions of the system, respectively. Then, a control strategy is developed to achieve the objectives including restraining the vibrations in bending and twisting deflections of the flexible link of the wing and achieving the desired angular position of the wing. By using Lyapunov's direct method, the wing system is proven to be stable. The numerical simulations are carried out with the finite difference method to prove the effectiveness of designed boundary controllers.

Dynamical Modeling and Boundary Vibration Control of a Rigid-Flexible Wing System

The combination of spiking neural networks and event-based vision sensors holds the potential of highly efficient and high-bandwidth optical flow estimation This paper presents the first hierarchical spiking architecture in which motion (direction and speed) selectivity emerges in an unsupervised fashion from the raw stimuli generated with an event-based camera A novel adaptive neuron model and stable spike-timing-dependent plasticity formulation are at the core of this neural network governing its spike-based processing and learning, respectively After convergence, the neural architecture exhibits the main properties of biological visual motion systems, namely feature extraction and local and global motion perception Convolutional layers with input synapses characterized by single and multiple transmission delays are employed for feature and local motion perception, respectively; while global motion selectivity emerges in a final fully-connected layer The proposed solution is validated using synthetic and real event sequences Along with this paper, we provide the cuSNN library, a framework that enables GPU-accelerated simulations of large-scale spiking neural networks Source code and samples are available at https://githubcom/tudelft/cuSNN 

/pdf/unsupervised-learning-of-a-hierarchical-spiking-neural-59bgdx4vvv.pdf

Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception

This paper describes the results of a six-year project aiming at designing and constructing a flapping twin-wing robot of the size of hummingbird (Colibri in French) capable of hovering. Our prototype has a total mass of 22 g, a wing span of 21 cm and a flapping frequency of 22 Hz; it is actively stabilized in pitch and roll by changing the wing camber with a mechanism known as wing twist modulation. The proposed design of wing twist modulation effectively alters the mean lift vector with respect to the center of gravity by reorganization of the airflow. This mechanism is modulated by an onboard control board which calculates the corrective feedback control signals through a closed-loop PD controller in order to stabilize the robot. Currently, there is no control on the yaw axis which is passively stable, and the vertical position is controlled manually by tuning the flapping frequency. The paper describes the recent evolution of the various sub-systems: the wings, the flapping mechanism, the generation of control torques, the avionics and the PD control. The robot has demonstrated successful hovering flights with an on-board battery for the flight autonomy of 15–20 s.

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COLIBRI: A hovering flapping twin-wing robot

This work presents a review and discussion of the challenges that must be solved in order to successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From the discussion, we extract constraints and links that relate the local level MAV capabilities to the global operations of the swarm. These should be taken into account when designing swarm behaviors in order to maximize the utility of the group. At the lowest level, each MAV should operate safely. Robustness is often hailed as a pillar of swarm robotics, and a minimum level of local reliability is needed for it to propagate to the global level. An MAV must be capable of autonomous navigation within an environment with sufficient trustworthiness before the system can be scaled up. Once the operations of the single MAV are sufficiently secured for a task, the subsequent challenge is to allow the MAVs to sense one another within a neighborhood of interest. Relative localization of neighbors is a fundamental part of self-organizing robotic systems, enabling behaviors ranging from basic relative collision avoidance to higher level coordination. This ability, at times taken for granted, also must be sufficiently reliable. Moreover, herein lies a constraint: the design choice of the relative localization sensor has a direct link to the behaviors that the swarm can (and should) perform. Vision-based systems, for instance, force MAVs to fly within the field of view of their camera. Range or communication-based solutions, alternatively, provide omni-directional relative localization, yet can be victim to unobservable conditions under certain flight behaviors, such as parallel flight, and require constant relative excitation. At the swarm level, the final outcome is thus intrinsically influenced by the on-board abilities and sensors of the individual. The real-world behavior and operations of an MAV swarm intrinsically follow in a bottom-up fashion as a result of the local level limitations in cognition, relative knowledge, communication, power, and safety. Taking these local limitations into account when designing a global swarm behavior is key in order to take full advantage of the system, enabling local limitations to become true strengths of the swarm.

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A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

Insects are among the most agile natural flyers. Hypotheses on their flight control cannot always be validated by experiments with animals or tethered robots. To this end, we developed a programmable and agile autonomous free-flying robot controlled through bio-inspired motion changes of its flapping wings. Despite being 55 times the size of a fruit fly, the robot can accurately mimic the rapid escape maneuvers of flies, including a correcting yaw rotation toward the escape heading. Because the robot's yaw control was turned off, we showed that these yaw rotations result from passive, translation-induced aerodynamic coupling between the yaw torque and the roll and pitch torques produced throughout the maneuver. The robot enables new methods for studying animal flight, and its flight characteristics allow for real-world flight missions.

A tailless aerial robotic flapper reveals that flies use torque coupling in rapid banked turns

Flapping wing micro air vehicles (MAVs) take inspiration from natural fliers, such as insects and hummingbirds. Existing designs manage to mimic the wing motion of natural fliers to a certain extent; nevertheless, differences will always exist due to completely different building blocks of biological and man-made systems. The same holds true for the design of the wings themselves, as biological and engineering materials differ significantly. This paper presents results of experimental optimization of wing shape of a flexible wing for a hummingbird-sized flapping wing MAV. During the experiments we varied the wing 'slackness' (defined by a camber angle), the wing shape (determined by the aspect and taper ratios) and the surface area. Apart from the generated lift, we also evaluated the overall power efficiency of the flapping wing MAV achieved with the various wing design. The results indicate that especially the camber angle and aspect ratio have a critical impact on the force production and efficiency. The best performance was obtained with a wing of trapezoidal shape with a straight leading edge and an aspect ratio of 9.3, both parameters being very similar to a typical hummingbird wing. Finally, the wing performance was demonstrated by a lift-off of a 17.2 g flapping wing robot.

https://iopscience.iop.org/article/10.1088/1748-3190/aa5c9e/pdf

Experimental optimization of wing shape for a hummingbird-like flapping wing micro air vehicle

The interest in flapping wing MAVs has been rising progressively in the past years The complex aerodynamic mechanisms responsible for high manoeuvrability and energy efficient lift production have been modelled by multiple techniques Here we present a comparison of several models from the perspective of flight stability in hover We estimated the stability derivatives by aerodynamic models of various levels of complexity, ranging from analytical expressions derived from a quasi steady model to CFD results that were taken as a reference The stability of the complete 6DOF linearized system, split into longitudinal and lateral part, was evaluated in terms of eigenvalues and eigenvectors While the pole locations and modes of longitudinal system were consistent for all the models (two stable subsidence modes, one unstable oscillatory mode), the lateral dynamics showed that quasi steady models with only translational force are insufficient and revealed the necessity of including the rotational lift to obtain pole locations that are in accordance with the CFD study (one slow divergence mode, one fast subsidence mode and one stable oscillatory mode)

Flapping Flight Stability in Hover: A Comparison of Various Aerodynamic Models

Micro Air Vehicles (MAVs) with flapping wings try to mimic their biological counterparts, insects and hummingbirds, as they can combine high agility manoeuvres with precision hovering flight. Near-hovering flapping flight is naturally unstable and needs to be stabilized actively. We present a novel mechanism for pitch moment generation in a robotic hummingbird that uses wing twist modulation via flexible wing root bars. A custom build force balance, sensitive enough to measure the cycle averaged pitch moment as well as lift force, is also presented. The introduced prototype mechanism generates pitch moment of up to ± 0.5 mNm. Finally we integrate a Shape Memory Alloy (SMA) wire to actuate the wing root bar ends. We present achievable displacement versus bandwidth as well as generated pitch moment.

https://journals.sagepub.com/doi/pdf/10.1260/1756-8293.5.4.299

Pitch Moment Generation and Measurement in a Robotic Hummingbird

We present a novel design of a tailless flapping wing micro air vehicle, which uses four independently driven pairs of flapping wings in order to fly and perform agile maneuvers. The wing pairs are...

https://journals.sagepub.com/doi/pdf/10.1177/1756829318794972

Matěj Karásek

Papers

A tailless aerial robotic flapper reveals that flies use torque coupling in rapid banked turns

Experimental optimization of wing shape for a hummingbird-like flapping wing micro air vehicle

Flapping Flight Stability in Hover: A Comparison of Various Aerodynamic Models

Pitch Moment Generation and Measurement in a Robotic Hummingbird

Quad-thopter: Tailless flapping wing robot with four pairs of wings: