|Intelligent Electrocardiogram |
An intelligent portable electrocardiogram (ECG) will automatically diagnose arrhythmias that could lead to sudden cardiac death (SCD).
|3D Visualization for EOD Robots |
NREC developed a plug-and-play camera and range finder module that gives range information and assists operators of EOD (explosive ordnance disposal) robots during manipulation.
|Enhanced Teleoperation (Mini SACR) |
NREC developed a real-time 3D video system to improve situation awareness in teleoperation and indirect driving.
|Enhanced Teleoperation (SACR) |
NREC’s miniaturized SACR (Situational Awareness Through Colorized Ranging) system fuses video and range data from a small panoramic camera ring and scanning LADAR sensor to provide photo-realistic 3D video and panoramic video images of an EOD (explosive ordnance disposal) robot’s surroundings.
|Sensabot Inspection Robot |
NREC is developing an inspection robot for use in oil and gas production plants.
|A Multi-Layered Display with Water Drops |
With a single projector-camera system and a set of linear drop generator manifolds, we have created a multi-layered water drop display that can be used for text, videos, and interactive games.
|Cargo UGV |
NREC is teaming with Oshkosh Defense to develop autonomous unmanned ground vehicle technologies for logistics tactical wheeled vehicles used by the US Marine Corps.
|Cargo UGV OCU |
The Cargo UGV operator control unit (OCU) seamlessly controls one or more Cargo UGVs traveling in convoy formation.
|Autonomous Robotics Manipulation |
Carnegie Mellon’s Autonomous Robotic Manipulation (ARM-S) team develops software that autonomously performs complex manipulation tasks.
|Computer Vistion Clinical Monitoring |
NREC and Columbia University researchers investigated whether computer vision could be used to monitor patients in clinical trials for spinal muscular atrophy (SMA) therapies.
|DRC Tartan Rescue Team |
During the Fukushima-Daiichi nuclear accident, robots weren’t able to inspect the facility, assess damage, and fix problems. DARPA wants to change this.
|Drug Discovery System |
An advanced computer vision system identifies and classifies the behavioral effects of new drug compounds, speeding the work of drug discovery.
|Negative Obstacle Detection |
NREC is developing a perception system to accurately detect negative obstacles in the path of an unmanned vehicle (UGV).
|Perception for LS3 |
NREC’s sensor system for DARPA’s Legged Squad Support System (LS3) enables LS3 to perceive its surroundings and autonomously track and follow a human leader.
|Stress Testing Autonomous Systems |
Stress Tests for Autonomy Architectures (STAA) finds autonomy system safety problems that are unlikely to be discovered by other types of tests.
|Tree Inventory |
A tree inventory system uses vehicle-mounted sensors to automatically count and map the locations of trees in an orchard.
|Tunnel Mapping |
NREC is pioneering research and development of a low power, small, lightweight system for producing accurate 3D maps of tunnels through its Precision Tunnel Mapping program.
|Urban Challenge |
Carnegie Mellon University and General Motors built an autonomous SUV that won first place in the 2007 DARPA Urban Challenge.
|Project LISTEN\'s Reading Tutor |
Project LISTEN's Reading Tutor listens to children read aloud.
|Visual Yield Mapping with Optimal and Generative Sampling Strategies |
This research project aims to develop methods to automatically collect visual image data to infer, estimate and forecast crop yields -- producing yield maps with high-resolution, across large scales and with accuracy. To achieve efficiency and accuracy, statistical sampling strategies are designed for human-robot teams that are optimal in the number of samples, location of samples, cost of sampling and accuracy of crop estimates.