NIST Measurement Science and Engineering Research Grants
WORLD MODELING FOR AUTONOMOUS NAVIGATION IN UNSTRUCTURED AND DYNAMIC ENVIRONMENTS: PERFORMANCE EVALUATION AND BENCHMARKING
Create and experimentally validate a framework by which automated guided vehicles (AGVs), robotic devices that are widely used in factory floors to transport goods, can automatically generate a sufficiently accurate internal map (world model) of its surroundings, in order to make them more versatile and useful as they navigate factory spaces with dynamically changing environments.
RECIPIENT: Temple University, Philadelphia, PA
AGVs are an integral component of today's manufacturing processes; they are widely used on factory floors for intra-factory transport of goods. However, they require highly structured environments and reference markers installed throughout plants, which can carry prohibitively high maintenance and installation costs. AGVs could be much more widely used in manufacturing if they could cope with unstructured, dynamic environments and adapt to human-centered collaboration while still keeping humans out of harm's way. Having robots sense unstructured environments and automatically generate a sufficiently accurate world model is still an unsolved problem, and the solution requires a framework for generating accurate representations of the operational domain. This, in turn, requires scientifically sound and statistically significant metrics, measurement, and evaluation methodologies for quantifying intelligent systems' performance. To address these challenges, the researchers will create and experimentally validate a world modeling framework for unstructured manufacturing environments containing dynamic objects. The researchers also plan on creating reference data sets for end users, developers, and vendors, and to actively participate in standards efforts in this field.
Public contact (for project information):
Robert Gage, 215-204-7486
Project Partners: Oak Ridge National Laboratory
NIST Program Office Contact:
Jason Boehm, 301-975-8678