Engineering Commons^™

A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian M. Lyons, James Finocchiaro, Misha Novitzky, Chris Korpela

Faculty Publications

Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …

A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela

Faculty Publications

Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …

Integrating Cost As A Decision Variable In Wargames, Joshua N. Reese, Jonathan D. Ritschel, Brent T. Langhals, Ryan D. Engle

Faculty Publications

The US military can no longer afford to be reactive, leaving critical cost analyses to the months and years following operations or full-scale conflicts. By leveraging cost in wargaming as part of the Joint planning process, DOD can provide Congress and the American taxpayers a range of potential costs associated with various military engagements that reflect fiscal and operational realities.

A Recommendation System For Meta-Modeling: A Meta-Learning Based Approach, Can Cui, Mengqi Hu, Jeffery D. Weir, Teresa Wu

Faculty Publications

Various meta-modeling techniques have been developed to replace computationally expensive simulation models. The performance of these meta-modeling techniques on different models is varied which makes existing model selection/recommendation approaches (e.g., trial-and-error, ensemble) problematic. To address these research gaps, we propose a general meta-modeling recommendation system using meta-learning which can automate the meta-modeling recommendation process by intelligently adapting the learning bias to problem characterizations. The proposed intelligent recommendation system includes four modules: (1) problem module, (2) meta-feature module which includes a comprehensive set of meta-features to characterize the geometrical properties of problems, (3) meta-learner module which compares the performance of instance-based …

A Relaxed Fusion Of Information From Real And Synthetic Images To Predict Complex Behavior, Damian M. Lyons, D. Paul Benjamin

Faculty Publications

An important component of cognitive robotics is the ability to mentally simulate physical processes and to compare the expected results with the information reported by a robot's sensors. In previous work, we have proposed an approach that integrates a 3D game-engine simulation into the robot control architecture. A key part of that architecture is the Match-Mediated Difference (MMD) operation, an approach to fusing sensory data and synthetic predictions at the image level. The MMD operation insists that simulated and predicted scenes are similar in terms of the appearance of the objects in the scene. This is an overly restrictive constraint …

Integrating Perception And Problem Solving To Predict Complex Object Behaviors, Damian M. Lyons, Sirhan Chaudhry, Marius Agica, John Vincent Monaco

Faculty Publications

One of the objectives of Cognitive Robotics is to construct robot systems that can be directed to achieve realworld goals by high-level directions rather than complex, low-level robot programming. Such a system must have the ability to represent, problem-solve and learn about its environment as well as communicate with other agents. In previous work, we have proposed ADAPT, a Cognitive Architecture that views perception as top-down and goaloriented and part of the problem solving process.

Our approach is linked to a SOAR-based problem-solving and learning framework. In this paper, we present an architecture for the perceptive and world modelling components …

The Use Of Two Mixture Fractions To Treat Coal Combustion Products In Turbulent Pulverized-Coal Flames, Daniel V. Flores, Thomas H. Fletcher

Faculty Publications

Previous coal combustion models using assumed-shape PDF's to treat turbulence-chemistry interactions have used only one progress variable to treat products from coal reactions. This assumes that the products of all coal reactions have the same composition. However. the composition of the combustion products of coal particles is known to vary with burnout, especially between devclatilization and char oxidation. In this work, two progress variables were implemented which distinguish between the products of devolatilization and those of char oxidation. This new approach requires as input the specified volatile content and elemental release during devolatilization. The values for these parameters were estimated …