High Fidelity Sensor Simulations for the Virtual Autonomous Navigation Environment. - Christopher Goodin; Phillip J. Durst; Burhman Q. Gates; Christopher L. Cummins; Jody D. Priddy (SIMPAR, 2010)

The Need for High-Fidelity Robotics Sensor Models. - Phillip J. Durst; Christopher Goodin; Burhman Q. Gates; Christopher L. Cummins; Burney McKinley; Jody D. Priddy; Peter Rander; Brett Browning (J. Robotics, 2011)

Towards an Ontology for Autonomous Robots. - Liam Paull; Gaëtan Séverac; Guilherme V. Raffo; Julian Mauricio Angel; Harold Boley; Phillip J. Durst; Wendell Gray; Maki K. Habib; Bao Nguyen; S. Veera Ragavan; Sajad Saeedi G.; Ricardo Sanz; et al. (IROS, 2012)

A framework for predicting the mission-specific performance of autonomous unmanned systems. - Phillip J. Durst; Wendell Gray; Agris Nikitenko; João Caetano; Michael Trentini; Roger King (IROS, 2014)

A reference autonomous mobility model. - Phillip J. Durst; Christopher T. Goodin; Derek T. Anderson; Cindy L. Bethel (WSC, 2017)

A historical review of the development of verification and validation theories for simulation models. - Phillip J. Durst; Derek T. Anderson; Cindy L. Bethel (Int. J. Model. Simul. Sci. Comput., 2017)

Using Physics-Based M&S for Training and Testing Machine Learning Algorithms. - Justin Carrillo; Burhman Q. Gates; Gabe Monroe; Brent Newell; Phillip J. Durst (MESAS, 2018)

Quantifying the Effects of Environmental Conditions on Autonomy Algorithms for Unmanned Ground Vehicles. - Phillip J. Durst; Justin Carrillo (MESAS, 2018)

A Perception-Based Fuzzy Route Planing Algorithm for Autonomous Unmanned Ground Vehicles. - Phillip J. Durst; Christopher T. Goodin; Cindy L. Bethel; Derek T. Anderson; Daniel W. Carruth; Hyeona Lim (Unmanned Syst., 2018)

A novel framework for verification and validation of simulations of autonomous robots. - Phillip J. Durst; David P. McInnis; Jeremy Davis; Christopher T. Goodin (Simul. Model. Pract. Theory, 2022)