Evaluation of Event-Based Sensors for Satellite Material Characterization

Jolley, Andrew; Cohen, Gregory; Joubert, Damien; Lambert, Andrew

doi:10.2514/1.a35015

Cited by 4 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It has been used to create annotated datasets (Rebecq et al, 2019 ), or to simulate novel pixel designs with multi-spectral sensitivities (Scheerlinck et al, 2019 ). More recently, we have developed an even more realistic event based vision sensor simulator (Joubert et al, 2021 ), which has been used to simulate characterising the materials on resident space objects with event based sensors (Jolley et al, 2021 ).…”

Section: Existing Benchmarksmentioning

confidence: 99%

Neuromorphic Engineering Needs Closed-Loop Benchmarks

Milde

Afshar

et al. 2022

Front. Neurosci.

Self Cite

View full text Add to dashboard Cite

Neuromorphic engineering aims to build (autonomous) systems by mimicking biological systems. It is motivated by the observation that biological organisms—from algae to primates—excel in sensing their environment, reacting promptly to their perils and opportunities. Furthermore, they do so more resiliently than our most advanced machines, at a fraction of the power consumption. It follows that the performance of neuromorphic systems should be evaluated in terms of real-time operation, power consumption, and resiliency to real-world perturbations and noise using task-relevant evaluation metrics. Yet, following in the footsteps of conventional machine learning, most neuromorphic benchmarks rely on recorded datasets that foster sensing accuracy as the primary measure for performance. Sensing accuracy is but an arbitrary proxy for the actual system's goal—taking a good decision in a timely manner. Moreover, static datasets hinder our ability to study and compare closed-loop sensing and control strategies that are central to survival for biological organisms. This article makes the case for a renewed focus on closed-loop benchmarks involving real-world tasks. Such benchmarks will be crucial in developing and progressing neuromorphic Intelligence. The shift towards dynamic real-world benchmarking tasks should usher in richer, more resilient, and robust artificially intelligent systems in the future.

show abstract

Section: Existing Benchmarksmentioning

confidence: 99%

Neuromorphic Engineering Needs Closed-Loop Benchmarks

Milde

Afshar

et al. 2022

Front. Neurosci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The space-based operation of the EBC for spacecraft landing on the Moon was investigated using simulated data [15]. The use of the EBCs for satellite characterization has also been studied [16]. The viability of EBC operation in the high-Fig.…”

Section: Introductionmentioning

confidence: 99%

Astrometric calibration and source characterisation of the latest generation neuromorphic event-based cameras for space imaging

Ralph,

Marcireau,

Afshar

et al. 2023

Astrodyn

View full text Add to dashboard Cite

As an emerging approach to space situational awareness and space imaging, the practical use of an event-based camera (EBC) in space imaging for precise source analysis is still in its infancy. The nature of event-based space imaging and data collection needs to be further explored to develop more effective event-based space imaging systems and advance the capabilities of event-based tracking systems with improved target measurement models. Moreover, for event measurements to be meaningful, a framework must be investigated for EBC calibration to project events from pixel array coordinates in the image plane to coordinates in a target resident space object’s reference frame. In this paper, the traditional techniques of conventional astronomy are reconsidered to properly utilise the EBC for space imaging and space situational awareness. This paper presents the techniques and systems used for calibrating an EBC for reliable and accurate measurement acquisition. These techniques are vital in building event-based space imaging systems capable of real-world space situational awareness tasks. By calibrating sources detected using the EBC, the spatiotemporal characteristics of detected sources or “event sources” can be related to the photometric characteristics of the underlying astrophysical objects. Finally, these characteristics are analysed to establish a foundation for principled processing and observing techniques which appropriately exploit the capabilities of the EBC.

show abstract