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Full-Text Articles in Computer Engineering
Response To Changes In Key Stimuli Through The Co-Evolution Of Sensor Morphology And Control, Gary Parker, Pramod J. Nathan
Response To Changes In Key Stimuli Through The Co-Evolution Of Sensor Morphology And Control, Gary Parker, Pramod J. Nathan
Computer Science Faculty Publications
Co-evolving a robot’s sensor morphology and control program increases the potential that it can effectively complete its tasks and provides a means for adapting to changes in the environment. In previous work, we presented a learning system where the angle, range, and type of sensors on a hexapod robot, along with the control program, were evolved. Although three sensor stimuli were detectable by the system, it used only two due to the relative importance of these two stimuli in completing the task. In the research presented in this paper, we used the same system, but reduced the availability of a …
Basic Control For Four Rotor Autonomous Aerial Agent, Jonathan Mclean, Gary Parker, Newell Seal
Basic Control For Four Rotor Autonomous Aerial Agent, Jonathan Mclean, Gary Parker, Newell Seal
Computer Science Faculty Publications
Aerial robotics provides many practical applications in fields such as search and rescue and surveying. In order to advance the research in aerial robotics, an inexpensive test platform is required. Our four-rotor platform provides researchers with a inexpensive, fully scalable test platform for future studies. Its completely on-board processing removes the need for a virtual tether in the form of a radio transmitter, allowing for completely autonomous operation.
Evolving Predator Control Programs For A Hexapod Robot Pursuing A Prey, Gary Parker, Basar Gulcu
Evolving Predator Control Programs For A Hexapod Robot Pursuing A Prey, Gary Parker, Basar Gulcu
Computer Science Faculty Publications
Control program learning systems for autonomous robots are important to assist in their development and to allow them to adapt to changes in their capabilities and/or the environment. A common method for learning in robotics is Evolutionary Computation (EC) and a good problem to demonstrate the effectiveness of a learning system is the predator/prey problem. In previous research, we used a Cyclic Genetic Algorithm (CGA), a form of EC, to evolve the control program for a predator robot with a simple sensor configuration of 4 binary sensors, which yielded 16 possible sensor states. In this paper, we present the use …