SBIR/STTR Research Award

Programmable Neuromorphic Microchip for Accelerating Dismount Identification in WFOV Video

Award identifier b7fc23b44835a1db66208a9f3ae95e931d24e9bc25f9990afba9ff5c1edd1cb0Awarding agency Department of Defense · Air Force

Award amount

$749,371

Program and phase

SBIR · Phase II

Award year

2014

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
Isocline Engineering LLC
Proposal award date
2014-08-27
Contract end date
2016-11-29
UEI
HAP1GG6Q56K8
Solicitation number
2013.3
Topic code
AF131-132

Research abstract

ABSTRACT: Wide field of view (WFOV) video capability on unmanned aerial systems (UAS) has outpaced data transmission capability. Identifying regions of interest (often performed through object recognition) enables selective video compression and maximizes the useful content in data transmission. Neuromorphic classifiers currently hold the records for greatest accuracy of object recognition and speech recognition, but are too computationally intensive for deployment in autonomous systems. This proposal describes a programmable microchip for energy-efficient acceleration of neuromorphic classifiers. Neuromorphic classifiers interpret sensor data much like the human brain does, allowing them to efficiently recognize dismounts, equipment, buildings, terrains, and other interesting features in video. The proposed platform will increase the capabilities of UAS while greatly reducing the form factor and power requirements of the control systems. In our Phase I effort we developed a mixed-signal circuitry that showed a 46-360x improvement in power efficiency, and a 700-9200x improvement in performance per volume, in comparison to a digital ASIC implementation or FPGA implementation, respectively. In this Phase II effort we will fabricate a prototype system that meets the target requirements of the solicitation. BENEFIT: The proposed system can function as a general purpose data classifier with little modification. Many commercial electronics are looking for new ways of interacting with the outside world that can benefit through this technology. In each of these applications the proposed system will be able to perform the task with much greater accuracy and performance with a lower power budget than other solutions. Military applications include object recognition for autonomous systems, navigation for autonomous systems through optical flow, and voice and gesture recognition for human interfaces. Potential consumer applications include medical devices that include data classifiers for detecting heart attacks or seizures, speech and object recognition for handheld devices like cellphones, and human interfaces for automobiles.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

5 SBIR/STTR records share this UEI (2012–2015). Reported award amounts total $2,022,859. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation

Agency intelligence

Department of Defense

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