Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) provide a versatile platform well-suited to applications requiring the efficiency of fixed-wing flight with the maneuverability of a multicopter. Prior work has introduced the concept of using solar energy harvesting using photovoltaic cells embedded in the wings of the vehicle to perform self-recharge in the field when landed and at rest. This work demonstrates a further extension of this concept by optimizing the VTOL aircraft for maximum input-to-output power ratio, such that continuous flight is possible for the majority of a typical day with good sunlight. By also adding amphibious design elements, a transoceanic flight cycle is proposed. The candidate aircraft design is shown with estimated and actual behavioral and performance data for hovering and forward flight. Artwork for design elements such as the tiltrotor nacelle design and interchangeable avionics pod are shown.
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uavEE: A Modular, Power-Aware Emulation Environment for Rapid Prototyping and Testing of UAV
State of the art design and testing of avionics for
unmanned aircraft is an iterative process that involves many
test flights, interleaved with multiple revisions of the flight management
software and hardware. To significantly reduce flight
test time and software development costs, we have developed
a real-time UAV Emulation Environment (uavEE) using ROS
that interfaces with high fidelity simulators to simulate the
flight behavior of the aircraft. Our uavEE emulates the avionics
hardware by interfacing directly with the embedded hardware
used in real flight. The modularity of uavEE allows the integration
of countless test scenarios and applications. Furthermore,
we present an accurate data driven approach for modeling of
propulsion power of fixed-wing UAVs, which is integrated into
uavEE. Finally, uavEE and the proposed UAV Power Model have
been experimentally validated using a fixed-wing UAV testbed.
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- Award ID(s):
- 1646383
- NSF-PAR ID:
- 10082990
- Date Published:
- Journal Name:
- Proceedings of IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Dataset accompanying code and paper: AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs
We present AircraftVerse, a publicly available aerial vehicle design dataset. AircraftVerse contains 27,714 diverse battery powered aircraft designs that have been evaluated using state-of-the-art physics models that characterize performance metrics such as maximum flight distance and hover-time.
This repository contains:
- A zip file "AircraftVerse.zip", where each design_X contains:
- design_tree.json: The design tree describes the design topology, choice of propulsion and energy subsystems. The tree also contains continuous parameters such as wing span, wing chord and arm length.
- design_seq.json: A preorder traversal of the design tree and store this as design_seq.json.
- design_low_level.json: The most low level representation of the design. This low level representation includes significant repetition that is avoided in the tree representation through the use of symmetry.
- Geom.stp: CAD design for the Aircraft in composition STP format (ISO 10303 standard).
- cadfile.stl: CAD design for the Aircraft in stereolithographic STL file,
- output.json: Summary containing the UAV's performance metrics such as maximum flight distance, maximum hover time, fight distance at maximum speed, maximum current draw, and mass.
- trims.npy: Contains the [Distance, Flight Time, Pitch, Control Input, Thrust, Lift, Drag, Current, Power] at each evaluated trim state (velocity).
- pointCloud.npy: Numpy array containing the corresponding point clouds for each design.
- corpus_dic: The corpus of components (e.g. batteries, propellers) that make up all aircraft designs. It is structured as a dictionary of dictionaries, with the high level components: ['Servo', 'GPS', 'ESC', 'Wing', 'Sensor', 'Propeller', 'Receiver', 'Motor', 'Battery', 'Autopilot'], containing a list of dictionaries corresponding to the component type. E.g. corpus_dic['Battery']['TurnigyGraphene2200mAh3S75C'] contains the detail of this particular battery.
Corresponding code for this work is included at https://github.com/SRI-CSL/AircraftVerse.
Acknowledgements:
This material is based upon work supported by the United States Air Force and DARPA under Contract No. FA8750-20-C-0002. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force and DARPA.
- A zip file "AircraftVerse.zip", where each design_X contains:
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Abstract Some bird species exhibit a flight behavior known as whiffling, in which the bird flies upside-down during landing, predator evasion, or courtship displays. Flying inverted causes the flight feathers to twist, creating gaps in the wing’s trailing edge. It has been suggested that these gaps decrease lift at a potentially lower energy cost, enabling the bird to maneuver and rapidly descend. Thus, avian whiffling has parallels to an uncrewed aerial vehicle (UAV) using spoilers for rapid descent and ailerons for roll control. However, while whiffling has been previously described in the biological literature, it has yet to directly inspire aerodynamic design. In the current research, we investigated if gaps in a wing’s trailing edge, similar to those caused by feather rotation during whiffling, could provide an effective mechanism for UAV control, particularly rapid descent and banking. To address this question, we performed a wind tunnel test of 3D printed wings with a varying amount of trailing edge gaps and compared the lift and rolling moment coefficients generated by the gapped wings to a traditional spoiler and aileron. Next, we used an analytical analysis to estimate the force and work required to actuate gaps, spoiler, and aileron. Our results showed that gapped wings did not reduce lift as much as a spoiler and required more work. However, we found that at high angles of attack, the gapped wings produced rolling moment coefficients equivalent to upwards aileron deflections of up to 32.7° while requiring substantially less actuation force and work. Thus, while the gapped wings did not provide a noticeable benefit over spoilers for rapid descent, a whiffling-inspired control surface could provide an effective alternative to ailerons for roll control. These findings suggest a novel control mechanism that may be advantageous for small fixed-wing UAVs, particularly energy-constrained aircraft.more » « less
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Autonomous multicopters often feature federated architectures, which incur relatively high communication costs between separate hardware components. These costs limit the ability to react quickly to new mission objectives. Additionally, federated architectures are not easily upgraded without introducing new hardware that impacts size, weight, power and cost (SWaP-C) constraints. In turn, such constraints restrict the use of redundant hardware to handle faults. In response to these challenges, we propose FlyOS, an Integrated Modular Avionics (IMA) approach to consolidate mixed-criticality flight functions in software on heterogeneous multicore aerial platforms. FlyOS is based on a separation kernel that statically partitions resources among virtualized sandboxed OSes. We present a dual-sandbox prototype configuration, where timing-and safety-critical flight control tasks execute in a real-time OS alongside mission-critical vision-based navigation tasks in a Linux sandbox. Low latency shared memory communication allows flight commands and data to be relayed in real-time between sandboxes. A hypervisor-based fault-tolerance mechanism is also deployed to ensure failover flight control in case of critical function or timing failures. We validate FlyOS’s performance and showcase its benefits when compared against traditional architectures in terms of predictable, extensible and efficient flight control.more » « less
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Abstract The majority of bird and bat species are incapable of carrying tags that transmit their position to satellites. Given fundamental power requirements for such communication, burdened mass guidelines and battery technology, this constraint necessitates the continued use of very high frequency (VHF) radio beacons. As such, efforts should be made to mitigate their primary deficiencies: detection range, localization time and localization accuracy.
The integration of a radiotelemetry system with an unmanned aerial vehicle (UAV) could significantly improve the capacity for data collection from VHF tags. We present a UAV‐integrated radiotelemetry system that relies on open source hardware and software. Localization methods, including signal processing, bearing estimation based on principal component analysis, localization techniques and test results, are discussed.
Using a low‐power beacon applicable for bats and small birds, testing showed that the improved vantage of the UAV‐radiotelemetry system (UAV‐RT) provided significantly higher received signal power compared to the low‐level flights (maximum range beyond 1.4 km). Flight testing of localization methods showed median bearing errors between 2.3° and 6.8°, with localization errors of between 5% and 14% of the distance to the tag. In a direct comparison to an experienced radiotelemetry user, the UAV‐RT system provided bearing and localization estimates with 53% less error.
This paper introduces the core functionality and use methods of the UAV‐RT system, while presenting baseline localization performance metrics. An associated website hosts plans for assembly and software installation. The methods of UAV‐RT use for tag detection will be further developed in future works. For both the detection and localization problems, the mobility of a flying asset drastically reduces tracker time requirements. A 7‐min flight would be sufficient to collect five equally spaced bearing estimates over a 1‐km transect. The use of a software‐defined radio on the UAV‐RT system will allow for the simultaneous detection and localization of multiple tags.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
