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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
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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 …
Motion Planning And Control Of Differential Drive Robot, Kaamesh Kothandaraman
Motion Planning And Control Of Differential Drive Robot, Kaamesh Kothandaraman
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Motion planning and control of a differential drive robot in a supervised environment is presented in this thesis. Differential drive robot is a mobile robot with two driving wheels in which the overall velocity is split between left and right wheels. Kinematic equations are derived and implemented in Simulink to observe the theoretical working principle of the robot. A proportional controller is designed to control the motion of the robot, which is later implemented on a physical robot. Combination of linear velocity and orientation generates individual wheel velocities which are sent to the robot by wireless communication for its motion. …