Data Reduction And Error Analysis For The Physical Sciences

We are witnessing the advent of a new era of robots - drones - that can autonomously fly in natural and man-made environments. These robots, often associated with defence applications, could have a major impact on civilian tasks, including transportation, communication, agriculture, disaster mitigation and environment preservation. Autonomous flight in confined spaces presents great scientific and technical challenges owing to the energetic cost of staying airborne and to the perceptual intelligence required to negotiate complex environments. We identify scientific and technological advances that are expected to translate, within appropriate regulatory frameworks, into pervasive use of autonomous drones for civilian applications.

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Science, technology and the future of small autonomous drones

We present a novel, deeply embedded robotics middleware and programming environment. It uses a multithreaded, publish-subscribe design pattern and provides a Unix-like software interface for micro controller applications. We improve over the state of the art in deeply embedded open source systems by providing a modular and standards-oriented platform. Our system architecture is centered around a publish-subscribe object request broker on top of a POSIX application programming interface. This allows to reuse common Unix knowledge and experience, including a bash-like shell. We demonstrate with a vertical takeoff and landing (VTOL) use case that the system modularity is well suited for novel and experimental vehicle platforms. We also show how the system architecture allows a direct interface to ROS and to run individual processes either as native ROS nodes on Linux or nodes on the micro controller, maximizing interoperability. Our microcontroller-based execution environment has substantially lower latency and better hardware connectivity than a typical Robotics Linux system and is therefore well suited for fast, high rate control tasks.

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PX4: A node-based multithreaded open source robotics framework for deeply embedded platforms

Flying insects capable of navigating in highly cluttered natural environments can withstand in-flight collisions because of the combination of their low inertia1 and the resilience of their wings2, exoskeletons1 and muscles. Current insect-scale (less than ten centimetres long and weighing less than five grams) aerial robots3–6 use rigid microscale actuators, which are typically fragile under external impact. Biomimetic artificial muscles7–10 that are capable of large deformation offer a promising alternative for actuation because they can endure the stresses caused by such impacts. However, existing soft actuators11–13 have not yet demonstrated sufficient power density to achieve lift-off, and their actuation nonlinearity and limited bandwidth create further challenges for achieving closed-loop (driven by an input control signal that is adjusted based on sensory feedback) flight control. Here we develop heavier-than-air aerial robots powered by soft artificial muscles that demonstrate open-loop (driven by a predetermined signal without feedback), passively stable (upright during flight) ascending flight as well as closed-loop, hovering flight. The robots are driven by multi-layered dielectric elastomer actuators that weigh 100 milligrams each and have a resonance frequency of 500 hertz and power density of 600 watts per kilogram. To increase the mechanical power output of the actuator and to demonstrate flight control, we present ways to overcome challenges unique to soft actuators, such as nonlinear transduction and dynamic buckling. These robots can sense and withstand collisions with surrounding obstacles and can recover from in-flight collisions by exploiting material robustness and vehicle passive stability. We also fly two micro-aerial vehicles simultaneously in a cluttered environment. They collide with the wall and each other without suffering damage. These robots rely on offboard amplifiers and an external motion-capture system to provide power to the dielectric elastomer actuators and to control their flight. Our work demonstrates how soft actuators can achieve sufficient power density and bandwidth to enable controlled flight, illustrating the potential of developing next-generation agile soft robots. Heavier-than-air insect-scale aerial robots powered by soft artificial muscles can hover and also recover from in-flight collisions, illustrating the potential for developing next-generation agile soft robots.

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Controlled flight of a microrobot powered by soft artificial muscles

WE found, on experimental grounds in Article I, that the field of air‐flow past a short body of low resistance shape, such as an aerofoil, comprises two dissimilar parts: (a) a thin boundary layer enveloping the body and dominated by viscous effects, and (b) a motion outside the boundary layer in which viscosity is much less important. It will be remembered that in the external motion occur the large pressure changes, which, transmitted through the boundary layer, account for nearly all the lift and for part of the drag. These pressures we observed to be calculable from the velocities without appreciable error by Bernoulli's equation. In the present Article we confine attention to this external flow, assuming it to be steady, incompressible, and inviscid. Its dependence upon (a), already discussed to some extent, we ignore; the boundary layer is conceived to be everywhere very thin, so that the only role it plays is to allow of relative velocity at the surface of the body. The assumptions made, excepting that of incompressibility, will appear drastic, and it will not be surprising if some of our deductions prove discordant with experimental fact. Nevertheless, they lead to a theory which finds many applications and uses in real fluid motion, and, in particular, gives an intimate view of aerofoil flow that is very close to the truth. It is convenient to develop our reasoning in analytical terms and for simplicity to restrict the flow to two dimensions (Article 1, §5). But the engineer will find special scope in this part of aerodynamics for graphical methods in the solution of particular problems.

Aerodynamics for Engineers

Light-weight, autonomous ornithopters form a promise to observe places that are too small or too dangerous for humans to enter In this article, we discuss the DelFly project, in which we follow a top-down approach to ever smaller and more autonomous ornithopters Top-down signifies that the project always focuses on complete flying systems equipped with camera We give arguments for the approach by explaining which findings on the DelFly I and DelFly II recently led to the development of the DelFly Micro: a 307-gram ornithopter carrying a camera and transmitter onboard These findings concern the design, aerodynamics, and vision-based control of the DelFly In addition, we identify main obstacles on the road to fly-sized ornithopters

https://journals.sagepub.com/doi/pdf/10.1260/175682909789498288

Design, Aerodynamics, and Vision-Based Control of the DelFly:

One of the major challenges in robotics is to develop a fly-like robot that can autonomously fly around in unknown environments. In this paper, we discuss the current state of the DelFly project, in which we follow a top-down approach to ever smaller and more autonomous ornithopters. The presented findings concerning the design, aerodynamics and autonomy of the DelFly illustrate some of the properties of the top-down approach, which allows the identification and resolution of issues that also play a role at smaller scales. A parametric variation of the wing stiffener layout produced a 5% more power-efficient wing. An experimental aerodynamic investigation revealed that this could be associated with an improved stiffness of the wing, while further providing evidence of the vortex development during the flap cycle. The presented experiments resulted in an improvement in the generated lift, allowing the inclusion of a yaw rate gyro, pressure sensor and microcontroller onboard the DelFly. The autonomy of the DelFly is expanded by achieving (1) an improved turning logic to obtain better vision-based obstacle avoidance performance in environments with varying texture and (2) successful onboard height control based on the pressure sensor.

https://iopscience.iop.org/article/10.1088/1748-3182/7/2/025003/pdf

Design, aerodynamics and autonomy of the DelFly

Swarms of tiny flying robots hold great potential for exploring unknown, indoor environments. Their small size allows them to move in narrow spaces, and their light weight makes them safe for operating around humans. Until now, this task has been out of reach due to the lack of adequate navigation strategies. The absence of external infrastructure implies that any positioning attempts must be performed by the robots themselves. State-of-the-art solutions, such as simultaneous localization and mapping, are still too resource demanding. This article presents the swarm gradient bug algorithm (SGBA), a minimal navigation solution that allows a swarm of tiny flying robots to autonomously explore an unknown environment and subsequently come back to the departure point. SGBA maximizes coverage by having robots travel in different directions away from the departure point. The robots navigate the environment and deal with static obstacles on the fly by means of visual odometry and wall-following behaviors. Moreover, they communicate with each other to avoid collisions and maximize search efficiency. To come back to the departure point, the robots perform a gradient search toward a home beacon. We studied the collective aspects of SGBA, demonstrating that it allows a group of 33-g commercial off-the-shelf quadrotors to successfully explore a real-world environment. The application potential is illustrated by a proof-of-concept search-and-rescue mission in which the robots captured images to find "victims" in an office environment. The developed algorithms generalize to other robot types and lay the basis for tackling other similarly complex missions with robot swarms in the future.

Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment

Autonomous flight of Flapping Wing Micro Air Vehicles (FWMAVs) is a major challenge in the field of robotics, due to their light weight and the flapping-induced body motions. In this article, we present the first FWMAV with onboard vision processing for autonomous flight in generic environments. In particular, we introduce the DelFly ‘Explorer’, a 20-gram FWMAV equipped with a 0.98-gram autopilot and a 4.0-gram onboard stereo vision system. We explain the design choices that permit carrying the extended payload, while retaining the DelFly’s hover capabilities. In addition, we introduce a novel stereo vision algorithm, LongSeq, designed specifically to cope with the flapping motion and the desire to attain a computational effort tuned to the frame rate. The onboard stereo vision system is illustrated in the context of an obstacle avoidance task in an environment with sparse obstacles.

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Autonomous flight of a 20-gram Flapping Wing MAV with a 4-gram onboard stereo vision system

This paper presents an approach to the system identification of the Delfly II Flapping Wing Micro Air Vehicle (FWMAV) using flight test data. It aims at providing simple FWMAV aerodynamic models that can be used in simulations as well as in nonlinear flight control systems. The undertaken methodology builds on normal aircraft system identification methods and extends these with techniques that are specific to FWMAV model identification. The entire aircraft model identification cycle is discussed covering the set-up and automatic execution of the flight test experiments, the aircraft states, the aerodynamic forces and moments' reconstruction, the aerodynamic model structure selection, the parameter estimation and finally, the model validation. In particular, a motion capturing facility was used to record the flapper's position in time and from there compute the states and aerodynamic forces and moments that acted on it, assuming flap-averaged dynamics and linear aerodynamic model structures. It is shown th...

https://journals.sagepub.com/doi/pdf/10.1260/1756-8293.5.4.273

C. De Wagter

Papers

Design, Aerodynamics, and Vision-Based Control of the DelFly:

Design, aerodynamics and autonomy of the DelFly

Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment

Autonomous flight of a 20-gram Flapping Wing MAV with a 4-gram onboard stereo vision system

Linear Aerodynamic Model Identification of a Flapping Wing MAV Based on Flight Test Data