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Embodied neuromorphic intelligence

Author

Listed:
  • Chiara Bartolozzi

    (Istituto Italiano di Tecnologia)

  • Giacomo Indiveri

    (Institute of Neuroinformatics, University of Zurich and ETH Zurich)

  • Elisa Donati

    (Institute of Neuroinformatics, University of Zurich and ETH Zurich)

Abstract

The design of robots that interact autonomously with the environment and exhibit complex behaviours is an open challenge that can benefit from understanding what makes living beings fit to act in the world. Neuromorphic engineering studies neural computational principles to develop technologies that can provide a computing substrate for building compact and low-power processing systems. We discuss why endowing robots with neuromorphic technologies – from perception to motor control – represents a promising approach for the creation of robots which can seamlessly integrate in society. We present initial attempts in this direction, highlight open challenges, and propose actions required to overcome current limitations.

Suggested Citation

  • Chiara Bartolozzi & Giacomo Indiveri & Elisa Donati, 2022. "Embodied neuromorphic intelligence," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28487-2
    DOI: 10.1038/s41467-022-28487-2
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    References listed on IDEAS

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    Cited by:

    1. Ningning Bai & Yiheng Xue & Shuiqing Chen & Lin Shi & Junli Shi & Yuan Zhang & Xingyu Hou & Yu Cheng & Kaixi Huang & Weidong Wang & Jin Zhang & Yuan Liu & Chuan Fei Guo, 2023. "A robotic sensory system with high spatiotemporal resolution for texture recognition," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    2. Yue Yang & Fangduo Zhu & Xumeng Zhang & Pei Chen & Yongzhou Wang & Jiaxue Zhu & Yanting Ding & Lingli Cheng & Chao Li & Hao Jiang & Zhongrui Wang & Peng Lin & Tuo Shi & Ming Wang & Qi Liu & Ningsheng , 2024. "Firing feature-driven neural circuits with scalable memristive neurons for robotic obstacle avoidance," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    3. Imke Krauhausen & Sophie Griggs & Iain McCulloch & Jaap M. J. Toonder & Paschalis Gkoupidenis & Yoeri Burgt, 2024. "Bio-inspired multimodal learning with organic neuromorphic electronics for behavioral conditioning in robotics," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    4. Man Yao & Ole Richter & Guangshe Zhao & Ning Qiao & Yannan Xing & Dingheng Wang & Tianxiang Hu & Wei Fang & Tugba Demirci & Michele Marchi & Lei Deng & Tianyi Yan & Carsten Nielsen & Sadique Sheik & C, 2024. "Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    5. Shengbo Wang & Shuo Gao & Chenyu Tang & Edoardo Occhipinti & Cong Li & Shurui Wang & Jiaqi Wang & Hubin Zhao & Guohua Hu & Arokia Nathan & Ravinder Dahiya & Luigi Giuseppe Occhipinti, 2024. "Memristor-based adaptive neuromorphic perception in unstructured environments," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    6. Elisa Donati & Giacomo Valle, 2024. "Neuromorphic hardware for somatosensory neuroprostheses," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    7. Qian Li & Ting Tan & Benlong Wang & Zhimiao Yan, 2024. "Avian-inspired embodied perception in biohybrid flapping-wing robotics," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    8. Romain Beaubois & Jérémy Cheslet & Tomoya Duenki & Giuseppe De Venuto & Marta Carè & Farad Khoyratee & Michela Chiappalone & Pascal Branchereau & Yoshiho Ikeuchi & Timothée Levi, 2024. "BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    9. Simone D’Agostino & Filippo Moro & Tristan Torchet & Yiğit Demirağ & Laurent Grenouillet & Niccolò Castellani & Giacomo Indiveri & Elisa Vianello & Melika Payvand, 2024. "DenRAM: neuromorphic dendritic architecture with RRAM for efficient temporal processing with delays," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    10. Matteo Cartiglia & Filippo Costa & Shyam Narayanan & Cat-Vu H. Bui & Hasan Ulusan & Nicoletta Risi & Germain Haessig & Andreas Hierlemann & Fernando Cardes & Giacomo Indiveri, 2024. "A 4096 channel event-based multielectrode array with asynchronous outputs compatible with neuromorphic processors," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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