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1. Neurorobotics Models and Applications: – Neurorobots are categorized by purpose into classes like motor control, memory, action selection, and perception. – Common types of […]

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1. Neurorobotics Models and Applications:
– Neurorobots are categorized by purpose into classes like motor control, memory, action selection, and perception.
– Common types of neurorobots focus on motor control, memory, and perception.
– These robots are designed for specific mechanism studies in areas such as locomotion, memory testing, action selection, and sensory perception.
– Studies involve synaptic plasticity, neuromodulation, and active sensing theories to replicate animal behaviors.
– Neurorobots mimic locomotion using neurologically inspired theories and hierarchically organized control systems for complex movements.

2. Motor Control and Locomotion:
– Neurorobots are used to study motor feedback and control systems.
– Control systems in neurorobots are organized hierarchically for complex movements.
– Motor control methods include learned error correction and predictive controls.
– Robots are designed to produce adaptive arm movements and avoid obstacles.
– Models in this category mimic locomotion and focus on motor control theories.

3. Learning and Memory Systems:
– Neurorobots test animal memory theories, focusing on areas like the rat hippocampus.
– Studies involve learning mental maps of the environment through synaptic plasticity and neuromodulation.
– Robots match behavior of animals like barn owls.
– Active sensing theories support learning models in neurorobots.
– Neurorobots learn and replicate memory systems of animals for various experiments.

4. Action Selection and Value Systems:
– Neurorobots are used to study negative or positive weighting of actions and simulate ethical interactions.
– Studies focus on reinforcing neural signals with positive outcomes.
– Robots learn action selection behaviors based on inputs.
– Herds of small robots are used for feeding and communication experiments.
– This category explores how robots make decisions based on inputs and simulate ethical interactions.

5. Sensory Perception Studies:
– Neurorobots study sensory perception, especially vision.
– Neural models of sensory pathways are embedded in automatas.
– Researchers use depth information from human head and eye movements for visual scene representations.
– Changes in sensory signals from motor activity provide perceptual cues.
– Neurorobots are exposed to sensory signals during behavior to understand sensory perception mechanisms.

Neurorobotics (Wikipedia)

Neurorobotics is the combined study of neuroscience, robotics, and artificial intelligence. It is the science and technology of embodied autonomous neural systems. Neural systems include brain-inspired algorithms (e.g. connectionist networks), computational models of biological neural networks (e.g. artificial spiking neural networks, large-scale simulations of neural microcircuits) and actual biological systems (e.g. in vivo and in vitro neural nets). Such neural systems can be embodied in machines with mechanic or any other forms of physical actuation. This includes robots, prosthetic or wearable systems but also, at smaller scale, micro-machines and, at the larger scales, furniture and infrastructures.

Neurorobotics is that branch of neuroscience with robotics, which deals with the study and application of science and technology of embodied autonomous neural systems like brain-inspired algorithms. It is based on the idea that the brain is embodied and the body is embedded in the environment. Therefore, most neurorobots are required to function in the real world, as opposed to a simulated environment.

Beyond brain-inspired algorithms for robots neurorobotics may also involve the design of brain-controlled robot systems.

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