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Abstract Neuromorphic computing, exemplified by breakthroughs in machine vision through concepts like address-event representation and send-on-delta sampling, has revolutionised sensor technology, enabling low-latency and high dynamic range perception with minimal bandwidth. While these advancements are prominent in vision and auditory perception, their potential in machine olfaction remains under-explored, particularly in the context of fast sensing. Here, we outline the perspectives for neuromorphic principles in machine olfaction. Considering the physical characteristics of turbulent odour environments, we argue that event-driven signal processing is optimally suited to the inherent properties of olfactory signals. We highlight the lack of bandwidth limitation due to turbulent dispersal processes, the characteristic temporal and chemical sparsity, as well as the high information density of the odour landscape. Further, we critically review and discuss the literature on neuromorphic olfaction; particularly focusing on neuromorphic principles such as event generation algorithms, information encoding mechanisms, event processing schemes (spiking neural networks), and learning. We discuss that the application of neuromorphic principles may significantly enhance response time and task performance in robotic olfaction, enabling autonomous systems to perform complex tasks in turbulent environments—such as environmental monitoring, odour guided search and rescue operations, and hazard detection.
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Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review
The nervous systems converts the physical quantities sensed by its primary receptors into trains of events that are then processed in the brain. The unmatched efficiency in information processing has long inspired engineers to seek brain-like approaches to sensing and signal processing. The key principle pursued in neuromorphic sensing is to shed the traditional approach of periodic sampling in favor of an event-driven scheme that mimicks sampling as it occurs in the nervous system, where events are preferably emitted upon the change of the sensed stimulus. In this paper we highlight the advantages and challenges of event-based sensing and signal processing in the visual, auditory and olfactory domains. We also provide a survey of the literature covering neuromorphic sensing and signal processing in all three modalities. Our aim is to facilitate research in event-based sensing and signal processing by providing a comprehensive overview of the research performed previously as well as highlighting conceptual advantages, current progress and future challenges in the field.
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- Award ID(s):
- 2014217
- PAR ID:
- 10523414
- Publisher / Repository:
- Frontiers in Neural Circuits
- Date Published:
- Journal Name:
- Frontiers in Neural Circuits
- Volume:
- 15
- ISSN:
- 1662-5110
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fncir.2021.610446
