Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Engineering
Amygdala Modeling With Context And Motivation Using Spiking Neural Networks For Robotics Applications, Matthew Aaron Zeglen
Amygdala Modeling With Context And Motivation Using Spiking Neural Networks For Robotics Applications, Matthew Aaron Zeglen
Browse all Theses and Dissertations
Cognitive capabilities for robotic applications are furthered by developing an artificial amygdala that mimics biology. The amygdala portion of the brain is commonly understood to control mood and behavior based upon sensory inputs, motivation, and context. This research builds upon prior work in creating artificial intelligence for robotics which focused on mood-generated actions. However, recent amygdala research suggests a void in greater functionality. This work developed a computational model of an amygdala, integrated this model into a robot model, and developed a comprehensive integration of the robot for simulation, and live embodiment. The developed amygdala, instantiated in the Nengo Brain …
Stability Analysis Of Leg Configurations For Bipedal Running, Nitin Jaiswal
Stability Analysis Of Leg Configurations For Bipedal Running, Nitin Jaiswal
Browse all Theses and Dissertations
A legged robot with three-segmented limbs is used to study the effects of leg compliance originating from the joint level on the stability of hopping in place and running. The three-segments allow each leg to be kinematically configured an infinite number ways that satisfy the desired landing condition parameters, total leg length and angle. These two parameters along with the amount of energy thrust during stance determine the motion of the system during a single stride. The goal of this work is to explore the potential values for the leg parameters of three-segment leg, that provide additional stability when compared …
Design And Demonstration Of A Physical, Multi-Agent Autonomous Controller Testbed, Eric A. Nees
Design And Demonstration Of A Physical, Multi-Agent Autonomous Controller Testbed, Eric A. Nees
Browse all Theses and Dissertations
Navigation and control algorithms are often tested in a simulated environment before being deployed in physical systems. Although simulated environments provide a controlled setting to carefully evaluate performance, the designed scenarios are sometimes unrealistically ideal and may unintentionally omit circumstances or unmodeled interactions. This thesis presents the design, implementation, and practical demonstration of a physical testbed that enables the testing of multi-agent autonomous strategies in hardware on a small scale. Testing the algorithms at scale allows real-time exploration of the interaction and performance of both human and autonomous algorithms under non-ideal conditions while avoiding the costs and risks of full-scale, …