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Summary:The National Institute of Standards and Technology (NIST) Intelligent Systems Division (ISD) participated in the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) Program for a three year periods. During the first 18-month project phase, NIST developed learning algorithms and became familiar with the LAGR vehicles and DARPA test methods as a standard participant in the program, albeit outside the competition. During the second 18-month project phase, DARPA suggested that all LAGR teams participate in a “best-of” effort by supplying NIST with their best performing, most complete, and most promising perception and/or control algorithms. Description:The National Institute of Standards and Technology (NIST) Intelligent Systems Division (ISD) participated in the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) Program for a three year periods. During the first 18-month project phase, NIST developed learning algorithms and became familiar with the LAGR vehicles and DARPA test methods as a standard participant in the program, albeit outside the competition. During the second 18-month project phase, DARPA suggested that all LAGR teams participate in a “best-of” effort by supplying NIST with their best performing, most complete, and most promising perception and/or control algorithms. NIST developed an application programming interface (API) and a control framework to support “plug-and-play” of all algorithms into a vehicle controller for rapid integration and testing to support DARPA LAGR evaluations. In total, there were 27 tests, some with two parts. NIST participated in 21 tests. These included: Phase 1 tests 1-13 and Phase 2 test 14 which ran a pure Phase 1 system. NIST did not participate in tests 15 – 18 and 23. NIST provided “best of” vehicle controllers for tests 19-22 and 24-27. During the time in which the tests in which NIST did not participate were run, ISD developed a DARPA-requested standard color scheme for operator control units so that all teams’ controller output provided identically mapped costs to simplify team-to-team comparison. More importantly, during the non-participatory period, NIST developed the “plug-and-play” framework known as the Best-of LAGR (BLAGR) controller. The outcome of this effort allowed teams to integrate algorithms that abided by the NIST-developed API to be integrated into the BLAGR with relative ease. NIST then participated in several tests with versions of the BLAGR controller, comparing results to other teams’ controllers. |
Operator Control Unit Displays showing right and left: original color images (top), results of obstacle detection (middle), and cost maps (bottom). Cost values are converted to colors for visualization purpose. Lead Organizational Unit:elContact
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