Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Michael O. Shneier"'
Publikováno v:
Journal of Intelligent & Robotic Systems. 83:85-103
Detecting and tracking people is becoming more important in robotic applications because of the increasing demand for collaborative work in which people interact closely with and in the same workspace as robots. New safety standards allow people to w
Autor:
James S. Albus, Tsai Hong, Michael O. Shneier, Tommy Chang, William P. Shackleford, Roger V. Bostelman
Publikováno v:
Autonomous Robots. 24:69-86
Autonomous mobile robots need to adapt their behavior to the terrain over which they drive, and to predict the traversability of the terrain so that they can effectively plan their paths. Such robots usually make use of a set of sensors to investigat
Autor:
Roger V. Bostelman, William P. Shackleford, Tommy Chang, Michael O. Shneier, James S. Albus, Tsai Hong
Publikováno v:
Integrated Computer-Aided Engineering. 14:121-139
The National Institute of Standards and Technology's (NIST) Intelligent Systems Division (ISD) is a participant in the Defense Advanced Research Projects Agency (DARPA) LAGR (Learning Applied to Ground Robots) Program. The NIST team's objective for t
Publikováno v:
Journal of Field Robotics. 24:671-698
Soldiers are often asked to perform missions that last many hours and are extremely stressful. After a mission is complete, the soldiers are typically asked to provide a report describing the most important things that happened during the mission. Du
Autor:
Roger V. Bostelman, James S. Albus, Tsai Hong Hong, William P. Shackleford, Tommy Chang, Michael O. Shneier
Publikováno v:
Journal of Field Robotics. 23:975-1003
The Defense Applied Research Projects Agency (DARPA) Learning Applied to Ground Vehicles (LAGR) program aims to develop algorithms for autonomous vehicle navigation that learn how to operate in complex terrain. Over many years, the National Institute
Autor:
Geraldine S. Cheok, Michael O. Shneier, Roger V. Bostelman, Afzal Godil, Kamel S. Saidi, William P. Shackleford, Tsai Hong
Publikováno v:
CVPR Workshops
We have been researching three dimensional (3D) ground-truth systems for performance evaluation of vision and perception systems in the fields of smart manufacturing and robot safety. In this paper we first present an overview of different systems th