VLSI implementation of rehabituation

Goru, V.K.; Akers, L.A.

doi:10.1109/icnn.1996.549018

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…The phenomena of habituation, rehabituation and recovery have been implemented in hardware (Goru & Akers, 1996). However, the usefulness of habituation for adaptive robots has not been been fully explored yet.…”

Section: Discussionmentioning

confidence: 99%

Improving hallway navigation in mobile robots with sensor habituation

Chang

2000

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challeng

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Habituation is a form of non-associative learning observed in a variety of species of animals. Arguably, it is the simplest form of learning. Nonetheless, the ability to habituate to certain stimuli implies plastic neural systems and adaptive behaviors. This article describes how computational models of habituation can be applied to real robots. In particular, we discuss the problem of the oscillatory movements observed when a Khepera robot navigates through narrow hallways. Results show that habituation to the proximity of the walls can lead to smoother navigation. Habituation to sensory stimulation to the sides of the robot does not interfere with the robot's ability to turn at dead ends and to avoid obstacles outside the hallway. This work shows that simple biological mechanisms of learning can be adapted to achieve better performance in real mobile robots.

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Section: Discussionmentioning

confidence: 99%

Improving hallway navigation in mobile robots with sensor habituation

Chang

2000

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challeng

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Using Sensor Habituation in Mobile Robots to Reduce Oscillatory Movements in Narrow Corridors

Chang

2005

IEEE Trans. Neural Netw.

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Habituation is a form of nonassociative learning observed in a variety of species of animals. Arguably, it is the simplest form of learning. Nonetheless, the ability to habituate to certain stimuli implies plastic neural systems and adaptive behaviors. This paper describes how computational models of habituation can be applied to real robots. In particular, we discuss the problem of the oscillatory movements observed when a Khepera robot navigates through narrow hallways using a biologically inspired neurocontroller. Results show that habituation to the proximity of the walls can lead to smoother navigation. Habituation to sensory stimulation to the sides of the robot does not interfere with the robot's ability to turn at dead ends and to avoid obstacles outside the hallway. This paper shows that simple biological mechanisms of learning can be adapted to achieve better performance in real mobile robots.

show abstract

VLSI implementation of rehabituation

Cited by 2 publications

References 6 publications

Improving hallway navigation in mobile robots with sensor habituation

Improving hallway navigation in mobile robots with sensor habituation

Using Sensor Habituation in Mobile Robots to Reduce Oscillatory Movements in Narrow Corridors

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