SBIR/STTR Research Award

SBIR Phase I:Precision Docking for Automated Charging of Unmanned Platforms and Electric Vehicles

Award identifier 68053a727c3e25e8a92c8f5c94dd2a82eb76fe679cf2983816c91f24cbee76c8Awarding agency National Science Foundation

Award amount

$274,048

Program and phase

SBIR · Phase I

Award year

2023

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
INNOTECH SYSTEMS LLC
Proposal award date
2023-06-01
Contract end date
2024-05-31
UEI
RN2CQUMKETL7
Solicitation number
NSF 22-551
Topic code
R

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable automated and autonomous charging of a wide array of electric vehicles (e.g., electrified robots, cars and trucks, and drones) in adverse weather conditions.Examples include autonomous systems used in farming and logistics, electric vehicles in ports, and electric trucks. Despite tremendous progress and the proliferation of electric vehicles, an adequate, cost-effective, autonomous, and available charging infrastructure is currently lacking. This gap between need and availability is far worse in high power applications such as trucking. The proposed technology increases the deployment of autonomous mobile robots and drones in industries like agriculture and logistics which are currently suffering from labor issues.The technology may increase the deployment rate of commercial electric vehicle fleets that can contribute to reducing greenhouse gasses._x000D_ _x000D_ This SBIR Phase I project proposes to solve a key problem in the automation of the charging process for electric vehicles, namely precision localization and docking in adverse weather conditions. The conventional methods of localization for docking (e.g., infrared or vision-based) have limitations such as insufficient precision and limited performance in less-than-optimal environmental conditions. This team presents a high precision automated docking solution in the presence of clutter and removes objects that are potentially harming the Line of Sight (LOS). The goals of the proposed research and development are: 1) establishing that time averaged, multi-path signal characteristics in multiple spectral bands can identify locations within a known map or during a close proximity approach of the electric vehicle to the charger; 2) developing models suitable for Monte-Carlo modeling and simulation of an indoor environment or region in proximity of a charger benchmarked by some measurements and using such simulations for verification success; and 3) developing a high precision transponder based on wideband signaling._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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.

Research funding history

3 SBIR/STTR records share this UEI (2023–2025). Reported award amounts total $1,964,606. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Transportation, National Science Foundation

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

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