N141-077 TITLE: Low-Light, Low Cost Passive Terrain Sensing

TECHNOLOGY AREAS: Air Platform, Sensors

OBJECTIVE: Develop a stereo imaging passive terrain mapping system explicitly for use in low-light conditions using low-resolution, low cost, and low signal-to-noise sensors.

DESCRIPTION: Terrain sensing and mapping based on stereo imagery, whether from single or multiple cameras, generally relies on having good signal-to-noise characteristics. Military operations necessitate that terrain sensing systems operate primarily at night under low-light conditions where image intensifiers (I2) or infrared (IR) sensors are generally limited to low resolution, low signal-to-noise, or both. This has resulted in the majority of terrain sensing systems now being active (emitting), such as millimeter-wave radar, scanning Laser Detection and Ranging (LADAR), or flash LADAR, all of which pose a signature risk in threat environments. This effort would explore the limits of passive terrain sensing and mapping under low-light conditions using sensors such as I2, fused Electro-optical-infrared (EO-IR) or some alternative, preferably low cost solution. This effort will also stress the limits of machine vision ranging algorithms in low signal-to-noise environments. Terrain and obstacles likely to be encountered by a helicopter Unmanned Aerial Vehicle (UAV) in both rural and urban settings should be emphasized; e.g., hills, trees, water, buildings, towers, wires, etc.

PHASE I: Perform and document a tradeoff analysis of existing sensors for range, field-of-view, resolution, frame rate, weight, and power. Identify design points within the study appropriate to micro, small and full-scale helicopter UAVs, i.e., system weight equal to approximately 0.25 lb, 2.5 lb, and 25 lb, respectively. A horizontal and vertical field-of-view of 60 degrees is desirable. Identify and design a concept using the low-light sensors coupled with machine vision algorithms. Demonstrate a breadboard implementation of the resulting design that can produce accurate real-time terrain data.

PHASE II: Using results of the Phase I effort, build a prototype system and demonstrate it on a helicopter UAV provided as Government-furnished equipment. This prototype demonstration and validation will be achieved by working closely with Government researchers to integrate the sensor.

PHASE III: Upon successful results at the end of Phase II, the company will be expected to support the Navy in continuing the transition of the developed low-light terrain sensing technology. The business will produce a sensor system for evaluation to determine its effectiveness in an operationally relevant environment and will provide support for test and validation to certify and qualify the new technology in navy systems. Other potential applications include the ONR AACUS program and Army Autonomous Technologies for Unmanned Air Systems (ATUAS) program. These programs seek to expand the operations of future autonomous helicopters including operations in complex, cluttered environments.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: This system could be used in a broad range of helicopter UAV missions requiring autonomous operations in complex urban environments. In addition, manned helicopters operating in the same environment could benefit from such a sensor to prevent controlled flight into terrain (CFIT).

REFERENCES:
1. Whalley, M. et al, "Flight Test Results for Autonomous Obstacle Field Navigation and Landing Site Selection on the RASCAL JUH-60A," presented at the 69th Annual Forum of the American Helicopter Society, Phoenix, AZ, May 2013.

2. Goerzen, C. and Whalley M., "Sensor Requirements for Autonomous Flight," presented at the 2012 International Conference on Unmanned Aircraft Systems (ICUAS), Philadelphia, PA, June 2012.

3. Goerzen, C. and Whalley, M., "Minimal risk motion planning: a new planner for autonomous UAVs in uncertain environments," presented at The AHS International Specialists Meeting on Unmanned Rotorcraft, Tempe, AZ, Jan. 2011.

4. Theodore, "Comparison Between Passive and Active Terrain Sensing for Autonomous Landing Site Selection" presented at the 2007 AHS International Specialists' Meeting, Unmanned Rotorcraft: Design, Control and Testing, January 2007.

KEYWORDS: Terrain; mapping; low-light; sensor; electro-optic; helicopter

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