DSCC 2013 Paper Abstract


Paper MoCT2.6

Samanta, Biswanath (Georgia Southern University), prince, Islam (Georgia Southern University)

Control of Autonomous Robots Using the Principles of Neuromodulation

Scheduled for presentation during the Invited session "Human Assistive Systems and Wearable Robots: Design and Control" (MoCT2), Monday, October 21, 2013, 17:40−18:00, Room 123

6th Annual Dynamic Systems and Control Conference, October 21-23, 2020, Stanford University, Munger Center, Palo Alto, CA

This information is tentative and subject to change. Compiled on October 30, 2020

Keywords Autonomous systems


The paper presents a control approach based on vertebrate neuromodulation and its implementation on an autonomous robot platform. A simple neural network is used to model the neuromodulatory function for generating context based behavioral responses to sensory signals. The neural network incorporates three types of neurons- cholinergic and noradrenergic (ACh/NE) neurons for attention focusing and action selection, dopaminergic (DA) neurons for curiosity-seeking, and serotonergic (5-HT) neurons for risk aversion behavior. The implementation of the neuronal model on a relatively simple autonomous robot illustrates its interesting behavior adapting to changes in the environment. The integration of neuromodulation based robots in the study of human-robot interaction would be worth considering in future.


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