Autonomous Flying With Neuromorphic Sensing
Autonomous flight for large aircraft appears to be within our reach. However, launching autonomous systems for everyday missions still requires an immense interdisciplinary research effort supported by pointed policies and funding. We believe that concerted endeavors in the fields of neuroscience, m...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-05-01
|
| Series: | Frontiers in Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2021.672161/full |
| _version_ | 1818599744504594432 |
|---|---|
| author | Patricia P. Parlevliet Andrey Kanaev Chou P. Hung Andreas Schweiger Frederick D. Gregory Frederick D. Gregory Ryad Benosman Ryad Benosman Ryad Benosman Guido C. H. E. de Croon Yoram Gutfreund Chung-Chuan Lo Cynthia F. Moss |
| author_facet | Patricia P. Parlevliet Andrey Kanaev Chou P. Hung Andreas Schweiger Frederick D. Gregory Frederick D. Gregory Ryad Benosman Ryad Benosman Ryad Benosman Guido C. H. E. de Croon Yoram Gutfreund Chung-Chuan Lo Cynthia F. Moss |
| author_sort | Patricia P. Parlevliet |
| collection | DOAJ |
| description | Autonomous flight for large aircraft appears to be within our reach. However, launching autonomous systems for everyday missions still requires an immense interdisciplinary research effort supported by pointed policies and funding. We believe that concerted endeavors in the fields of neuroscience, mathematics, sensor physics, robotics, and computer science are needed to address remaining crucial scientific challenges. In this paper, we argue for a bio-inspired approach to solve autonomous flying challenges, outline the frontier of sensing, data processing, and flight control within a neuromorphic paradigm, and chart directions of research needed to achieve operational capabilities comparable to those we observe in nature. One central problem of neuromorphic computing is learning. In biological systems, learning is achieved by adaptive and relativistic information acquisition characterized by near-continuous information retrieval with variable rates and sparsity. This results in both energy and computational resource savings being an inspiration for autonomous systems. We consider pertinent features of insect, bat and bird flight behavior as examples to address various vital aspects of autonomous flight. Insects exhibit sophisticated flight dynamics with comparatively reduced complexity of the brain. They represent excellent objects for the study of navigation and flight control. Bats and birds enable more complex models of attention and point to the importance of active sensing for conducting more complex missions. The implementation of neuromorphic paradigms for autonomous flight will require fundamental changes in both traditional hardware and software. We provide recommendations for sensor hardware and processing algorithm development to enable energy efficient and computationally effective flight control. |
| first_indexed | 2024-12-16T12:24:28Z |
| format | Article |
| id | doaj.art-f6205c825fa04b738b56828600494608 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-16T12:24:28Z |
| publishDate | 2021-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-f6205c825fa04b738b568286004946082022-12-21T22:31:53ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2021-05-011510.3389/fnins.2021.672161672161Autonomous Flying With Neuromorphic SensingPatricia P. Parlevliet0Andrey Kanaev1Chou P. Hung2Andreas Schweiger3Frederick D. Gregory4Frederick D. Gregory5Ryad Benosman6Ryad Benosman7Ryad Benosman8Guido C. H. E. de Croon9Yoram Gutfreund10Chung-Chuan Lo11Cynthia F. Moss12Central Research and Technology, Airbus, Munich, GermanyU.S. Office of Naval Research Global, London, United KingdomUnited States Army Research Laboratory, Aberdeen Proving Ground, Maryland, MD, United StatesAirbus Defence and Space GmbH, Manching, GermanyU.S. Army Research Laboratory, London, United KingdomDepartment of Bioengineering, Imperial College London, London, United KingdomInstitut de la Vision, INSERM UMRI S 968, Paris, FranceBiomedical Science Tower, University of Pittsburgh, Pittsburgh, PA, United StatesRobotics Institute, Carnegie Mellon University, Pittsburgh, PA, United States0Micro Air Vehicle Laboratory, Department of Control and Operations, Faculty of Aerospace Engineering, Delft University of Technology, Delft, Netherlands1The Neuroethological lab, Department of Neurobiology, The Rappaport Institute for Biomedical Research, Technion – Israel Institute of Technology, Haifa, Israel2Brain Research Center/Institute of Systems Neuroscience, National Tsing Hua University, Hsinchu, Taiwan3Laboratory of Comparative Neural Systems and Behavior, Department of Psychological and Brain Sciences, Neuroscience and Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United StatesAutonomous flight for large aircraft appears to be within our reach. However, launching autonomous systems for everyday missions still requires an immense interdisciplinary research effort supported by pointed policies and funding. We believe that concerted endeavors in the fields of neuroscience, mathematics, sensor physics, robotics, and computer science are needed to address remaining crucial scientific challenges. In this paper, we argue for a bio-inspired approach to solve autonomous flying challenges, outline the frontier of sensing, data processing, and flight control within a neuromorphic paradigm, and chart directions of research needed to achieve operational capabilities comparable to those we observe in nature. One central problem of neuromorphic computing is learning. In biological systems, learning is achieved by adaptive and relativistic information acquisition characterized by near-continuous information retrieval with variable rates and sparsity. This results in both energy and computational resource savings being an inspiration for autonomous systems. We consider pertinent features of insect, bat and bird flight behavior as examples to address various vital aspects of autonomous flight. Insects exhibit sophisticated flight dynamics with comparatively reduced complexity of the brain. They represent excellent objects for the study of navigation and flight control. Bats and birds enable more complex models of attention and point to the importance of active sensing for conducting more complex missions. The implementation of neuromorphic paradigms for autonomous flight will require fundamental changes in both traditional hardware and software. We provide recommendations for sensor hardware and processing algorithm development to enable energy efficient and computationally effective flight control.https://www.frontiersin.org/articles/10.3389/fnins.2021.672161/fullneuromorphic sensingautonomous flightbio-inspirationflying animalslearningflight control |
| spellingShingle | Patricia P. Parlevliet Andrey Kanaev Chou P. Hung Andreas Schweiger Frederick D. Gregory Frederick D. Gregory Ryad Benosman Ryad Benosman Ryad Benosman Guido C. H. E. de Croon Yoram Gutfreund Chung-Chuan Lo Cynthia F. Moss Autonomous Flying With Neuromorphic Sensing Frontiers in Neuroscience neuromorphic sensing autonomous flight bio-inspiration flying animals learning flight control |
| title | Autonomous Flying With Neuromorphic Sensing |
| title_full | Autonomous Flying With Neuromorphic Sensing |
| title_fullStr | Autonomous Flying With Neuromorphic Sensing |
| title_full_unstemmed | Autonomous Flying With Neuromorphic Sensing |
| title_short | Autonomous Flying With Neuromorphic Sensing |
| title_sort | autonomous flying with neuromorphic sensing |
| topic | neuromorphic sensing autonomous flight bio-inspiration flying animals learning flight control |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2021.672161/full |
| work_keys_str_mv | AT patriciapparlevliet autonomousflyingwithneuromorphicsensing AT andreykanaev autonomousflyingwithneuromorphicsensing AT chouphung autonomousflyingwithneuromorphicsensing AT andreasschweiger autonomousflyingwithneuromorphicsensing AT frederickdgregory autonomousflyingwithneuromorphicsensing AT frederickdgregory autonomousflyingwithneuromorphicsensing AT ryadbenosman autonomousflyingwithneuromorphicsensing AT ryadbenosman autonomousflyingwithneuromorphicsensing AT ryadbenosman autonomousflyingwithneuromorphicsensing AT guidochedecroon autonomousflyingwithneuromorphicsensing AT yoramgutfreund autonomousflyingwithneuromorphicsensing AT chungchuanlo autonomousflyingwithneuromorphicsensing AT cynthiafmoss autonomousflyingwithneuromorphicsensing |