Search Results - "De Croon, Guido C. H. E."

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  1. 1

    Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception by Paredes-Valles, Federico, Scheper, Kirk Yannick Willehm, de Croon, Guido C. H. E.

    “…The combination of spiking neural networks and event-based vision sensors holds the potential of highly efficient and high-bandwidth optical flow estimation…”
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    Journal Article
  2. 2

    A tailless aerial robotic flapper reveals that flies use torque coupling in rapid banked turns by Karásek, Matěj, Muijres, Florian T, De Wagter, Christophe, Remes, Bart D W, de Croon, Guido C H E

    “…Insects are among the most agile natural flyers. Hypotheses on their flight control cannot always be validated by experiments with animals or tethered robots…”
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    Journal Article
  3. 3

    A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints by Coppola, Mario, McGuire, Kimberly N, De Wagter, Christophe, de Croon, Guido C H E

    Published in Frontiers in robotics and AI (25-02-2020)
    “…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…”
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    Journal Article
  4. 4

    Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy by Paredes-Valles, Federico, de Croon, Guido C. H. E.

    “…Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The…”
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    Conference Proceeding
  5. 5

    On-board communication-based relative localization for collision avoidance in Micro Air Vehicle teams by Coppola, Mario, McGuire, Kimberly N., Scheper, Kirk Y. W., de Croon, Guido C. H. E.

    Published in Autonomous robots (2018)
    “…To avoid collisions, Micro Air Vehicles (MAVs) flying in teams require estimates of their relative locations, preferably with minimal mass and processing…”
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    Journal Article
  6. 6

    How Do Neural Networks Estimate Optical Flow? A Neuropsychology-Inspired Study by de Jong, David B., Paredes-Valles, Federico, de Croon, Guido C. H. E.

    “…End-to-end trained convolutional neural networks have led to a breakthrough in optical flow estimation. The most recent advances focus on improving the optical…”
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    Journal Article
  7. 7

    Visual model‐predictive localization for computationally efficient autonomous racing of a 72‐g drone by Li, Shuo, Horst, Erik, Duernay, Philipp, De Wagter, Christophe, Croon, Guido C. H. E.

    Published in Journal of field robotics (01-06-2020)
    “…Drone racing is becoming a popular e‐sport all over the world, and beating the best human drone race pilots has quickly become a new major challenge for…”
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    Journal Article
  8. 8

    Monocular distance estimation with optical flow maneuvers and efference copies: a stability-based strategy by de Croon, Guido C H E

    Published in Bioinspiration & biomimetics (07-01-2016)
    “…The visual cue of optical flow plays an important role in the navigation of flying insects, and is increasingly studied for use by small flying robots as well…”
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    Journal Article
  9. 9

    Real-Time Nonlinear Control Allocation Framework for Vehicles with Highly Nonlinear Effectors Subject to Saturation by Mancinelli, Alessandro, Remes, Bart D. W., De Croon, Guido C. H. E., Smeur, Ewoud J. J.

    Published in Journal of intelligent & robotic systems (01-08-2023)
    “…Hybrid Unmanned Aerial Vehicles UAV are vehicles capable of take-off and landing vertically like helicopters while maintaining the long-range efficiency of…”
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    Journal Article
  10. 10

    Autonomous Flying With Neuromorphic Sensing by Parlevliet, Patricia P, Kanaev, Andrey, Hung, Chou P, Schweiger, Andreas, Gregory, Frederick D, Benosman, Ryad, de Croon, Guido C H E, Gutfreund, Yoram, Lo, Chung-Chuan, Moss, Cynthia F

    Published in Frontiers in neuroscience (14-05-2021)
    “…Autonomous flight for large aircraft appears to be within our reach. However, launching autonomous systems for everyday missions still requires an immense…”
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    Journal Article
  11. 11

    Optical flow-based control for micro air vehicles: an efficient data-driven incremental nonlinear dynamic inversion approach by Ho, Hann Woei, Zhou, Ye, Feng, Yiting, de Croon, Guido C. H. E.

    Published in Autonomous robots (01-12-2024)
    “…This paper proposes an innovative approach for optical flow-based control of micro air vehicles (MAVs), addressing challenges inherent in the nonlinearity of…”
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    Journal Article
  12. 12

    Drone-racing champions outpaced by AI by de Croon, Guido C. H. E.

    Published in Nature (London) (31-08-2023)
    “…An autonomous drone has competed against human drone-racing champions — and won. The victory can be attributed to savvy engineering and a type of artificial…”
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    Journal Article
  13. 13

    Accommodating unobservability to control flight attitude with optic flow by de Croon, Guido C. H. E., Dupeyroux, Julien J. G., De Wagter, Christophe, Chatterjee, Abhishek, Olejnik, Diana A., Ruffier, Franck

    Published in Nature (London) (20-10-2022)
    “…Attitude control is an essential flight capability. Whereas flying robots commonly rely on accelerometers 1 for estimating attitude, flying insects lack an…”
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    Journal Article
  14. 14

    Online trajectory planning and control of a MAV payload system in dynamic environments by Potdar, Nikhil D., de Croon, Guido C. H. E., Alonso-Mora, Javier

    Published in Autonomous robots (01-07-2020)
    “…Micro Aerial Vehicles (MAVs) can be used for aerial transportation in remote and urban spaces where portability can be exploited to reach previously…”
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    Journal Article
  15. 15

    On-board range-based relative localization for micro air vehicles in indoor leader–follower flight by van der Helm, Steven, Coppola, Mario, McGuire, Kimberly N., de Croon, Guido C. H. E.

    Published in Autonomous robots (01-03-2020)
    “…We present a range-based solution for indoor relative localization by micro air vehicles (MAVs), achieving sufficient accuracy for leader–follower flight…”
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    Journal Article
  16. 16

    Obstacle Avoidance Strategy using Onboard Stereo Vision on a Flapping Wing MAV by Tijmons, Sjoerd, de Croon, Guido C. H. E., Remes, Bart D. W., De Wagter, Christophe, Mulder, Max

    Published in IEEE transactions on robotics (01-08-2017)
    “…The development of autonomous lightweight MAVs, capable of navigating in unknown indoor environments, is one of the major challenges in robotics. The…”
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    Journal Article
  17. 17

    Sniffy Bug: A Fully Autonomous Swarm of Gas-Seeking Nano Quadcopters in Cluttered Environments by Duisterhof, Bardienus P., Li, Shushuai, Burgues, Javier, Reddi, Vijay Janapa, de Croon, Guido C. H. E.

    “…Nano quadcopters are ideal for gas source localization (GSL) as they are safe, agile and inexpensive. However, their extremely restricted sensors and…”
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    Conference Proceeding
  18. 18

    Provable self-organizing pattern formation by a swarm of robots with limited knowledge by Coppola, Mario, Guo, Jian, Gill, Eberhard, de Croon, Guido C. H. E.

    Published in Swarm intelligence (15-03-2019)
    “…In this paper we present a procedure to automatically design and verify the local behavior of robots with highly limited cognition. All robots are: anonymous,…”
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    Journal Article
  19. 19

    Three-dimensional relative localization and synchronized movement with wireless ranging by Pfeiffer, Sven, Munaro, Veronica, Li, Shushuai, Rizzo, Alessandro, de Croon, Guido C. H. E.

    Published in Swarm intelligence (01-06-2023)
    “…Relative localization is a key capability for autonomous robot swarms, and it is a substantial challenge, especially for small flying robots, as they are…”
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    Journal Article
  20. 20

    AvoidBench: A high-fidelity vision-based obstacle avoidance benchmarking suite for multi-rotors by Yu, Hang, de Croon, Guido C. H. E, De Wagter, Christophe

    “…Obstacle avoidance is an essential topic in the field of autonomous drone research. When choosing an avoidance algorithm, many different options are available,…”
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    Conference Proceeding