Sbir phase i: precision docking for automated charging of unmanned platforms and electric vehicles

The National Science Foundation (NSF) awarded a $274,048 Project Grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to Innotech Systems LLC to develop a high-precision, automated docking solution for charging electric vehicles, robots, and drones in adverse weather conditions. The goals of the 1-year project are to: 1) establish that multi-path signal characteristics can identify vehicle locations for docking, 2) develop models for simulating and verifying the system's performance in indoor environments, and 3) create a wideband transponder-based system for high-precision docking. This research aims to enable broader deployment of autonomous mobile platforms in industries like agriculture and logistics by addressing a key challenge in electric vehicle charging infrastructure.

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. 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. 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.