Engineering Commons^™

Evolving Expert Agent Parameters For Capture The Flag Agent In Xpilot, Gary Parker, Sarah Penrose

Computer Science Faculty Publications

Xpilot is an open source, 2d space combat game. Xpilot-AI allows a programmer to write scripts that control an agent playing a game of Xpilot. It provides a reasonable environment for testing learning systems for autonomous agents, both video game agents and robots. In previous work, a wide range of techniques have been used to develop controllers that are focused on the combat skills for an Xpilot agent. In this research, a Genetic Algorithm (GA) was used to evolve the parameters for an expert agent solving the more challenging problem of capture the flag.

Evolving Predator Control Programs For An Actual Hexapod Robot Predator, Gary Parker, Basar Gulcu

Computer Science Faculty Publications

In the development of autonomous robots, control program learning systems are important since they allow the robots to adapt to changes in their surroundings. Evolutionary Computation (EC) is a method that is used widely in learning systems. In previous research, we used a Cyclic Genetic Algorithm (CGA), a form of EC, to evolve a simulated predator robot to test the effectiveness of a learning system in the predator/prey problem. The learned control program performed search, chase, and capture behavior using 64 sensor states relative to the nearest obstacle and the target, a simulated prey robot. In this paper, we present …

Designing Autonomous Robot Missions With Performance Guarantees, Damian M. Lyons, Ronald Arkin, Prem Nirmal, Shu Jiang

Faculty Publications

This paper describes the need and methods required to construct an integrated software verification and mission specification system for use in robotic missions intended for counter-weapons of mass destruction (c-WMD) operations, as part of a 3-year effort for the Defense Threat Reduction Agency. The overall system architecture is described. The principal tool for verification is a process algebra, PARS, based on port automata theory. PARS is introduced, emphasizing its ability to represent probabilistic programs and uncertain and dynamic environments, followed by the analysis of mission properties for an example robotic mission.

Getting It Right The First Time: Predicted Performance Guarantees From The Analysis Of Emergent Behavior In Autonomous And Semi-Autonomous Systems, Ronald C. Arkin, Damian M. Lyons, Shu Jiang, Prem Nirmal, Munzir Zafar

Faculty Publications

A crucially important aspect for mission-critical robotic operations is ensuring as best as possible that an autonomous system be able to complete its task. In a project for the Defense Threat Reduction Agency (DTRA) we are developing methods to provide such guidance, specifically for counter-Weapons of Mass Destruction (C-WMD) missions. In this paper, we describe the scenarios under consideration, the performance measures and metrics being developed, and an outline of the mechanisms for providing performance guarantees.

Navigation Of Uncertain Terrain By Fusion Of Information From Real And Synthetic Imagery, Damian M. Lyons, Prem Nirmal, D. Paul Benjamin

Faculty Publications

We consider the scenario where an autonomous platform that is searching or traversing a building may observe unstable masonry or may need to travel over unstable rubble. A purely behaviour-based system may handle these challenges but produce behaviour that works against long-terms goals such as reaching a victim as quickly as possible. We extend our work on ADAPT, a cognitive robotics architecture that incorporates 3D simulation and image fusion, to allow the robot to predict the behaviour of physical phenomena, such as falling masonry, and take actions consonant with long-term goals.

We experimentally evaluate a cognitive only and reactive only …

Using A Virtual World For Robot Planning, D. Paul Benjamin, John V. Monaco, Yixia Lin, Christopher Funk, Damian M. Lyons

Faculty Publications

We are building a robot cognitive architecture that constructs a real-time virtual copy of itself and its environment, including people, and uses the model to process perceptual information and to plan its movements. This paper describes the structure of this architecture. The software components of this architecture include PhysX for the virtual world, OpenCV and the Point Cloud Library for visual processing, and the Soar cognitive architecture that controls the perceptual processing and task planning. The RS (Robot Schemas) language is implemented in Soar, providing the ability to reason about concurrency and time. This Soar/RS component controls visual processing, deciding …

An Approach To Stereo-Point Cloud Registration Using Image Homographies, Damian M. Lyons, Stephen D. Fox

Faculty Publications

No abstract provided.

Characterizing Performance Guarantees For Real-Time Multiagent Systems Operating In Noisy And Uncertain Environments, Damian M. Lyons, Ronald Arkin, Stephen Fox, Shu Jiang, Prem Nirmal, Munzir Zafar

Faculty Publications

Autonomous robots offer the potential to conduct Counter-Weapons of Mass Destruction (C-WMD) missions in an efficient and robust manner. However, to leverage this potential, a mission designer needs to be able to determine how well a robot system will operate in the noisy and uncertain environments that a C-WMD mission may require. We are developing a software framework for verification of performance guarantees for C-WMD missions based on the MissionLab software system and a novel process algebra approach to representing robot programs and operating environments.

In this paper, we report on our initial research for the Defense Threat Reduction Agency …

Effects Of Visual Interaction Methods On Simulated Unmanned Aircraft Operator Situational Awareness, Brent A. Terwilliger

Publications

The limited field of view of static egocentric visual displays employed in unmanned aircraft controls introduces the soda straw effect on operators, which significantly affects their ability to capture and maintain situational awareness by not depicting peripheral visual data. The problem with insufficient operator situational awareness is the resulting increased potential for error and oversight during operation of unmanned aircraft, leading to accidents and mishaps costing United States taxpayers between $4 million to $54 million per year. The purpose of this quantitative experimental completely randomized design study was to examine and compare use of dynamic eyepoint to static visual interaction …