Reactive direction control for a mobile robot: A locust-like control of escape direction emerges when a bilateral pair of model locust visual neurons are integrated

Yue, Shigang and Santer, Roger D. and Yamawaki, Yoshifumi and Rind, F. Claire (2010) Reactive direction control for a mobile robot: A locust-like control of escape direction emerges when a bilateral pair of model locust visual neurons are integrated. Autonomous Robots, 28 (2). pp. 151-167. ISSN 0929-5593

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Full text URL: http://dx.doi.org/10.1007/s10514-009-9157-4

Abstract

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to
the image of an approaching object. These neurons are called the lobula giant movement
detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the
development of an LGMD model for use as an artificial collision detector in robotic applications.
To date, robots have been equipped with only a single, central artificial LGMD sensor, and this
triggers a non-directional stop or rotation when a potentially colliding object is detected. Clearly,
for a robot to behave autonomously, it must react differently to stimuli approaching from
different directions. In this study, we implement a bilateral pair of LGMD models in Khepera
robots equipped with normal and panoramic cameras. We integrate the responses of these LGMD
models using methodologies inspired by research on escape direction control in cockroaches.
Using ‘randomised winner-take-all’ or ‘steering wheel’ algorithms for LGMD model integration,
the khepera robots could escape an approaching threat in real time and with a similar
distribution of escape directions as real locusts. We also found that by optimising these
algorithms, we could use them to integrate the left and right DCMD responses of real jumping
locusts offline and reproduce the actual escape directions that the locusts took in a particular
trial. Our results significantly advance the development of an artificial collision detection and
evasion system based on the locust LGMD by allowing it reactive control over robot behaviour.
The success of this approach may also indicate some important areas to be pursued in future
biological research.

Item Type:Article
Keywords:robots, escape, emergent properties, behaviour, visual neural network, LGMD, DCMD, locusts, jumping, agents, hybrid, cybernetics, direction
Subjects:C Biological Sciences > C120 Behavioural Biology
G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:2669
Deposited By: Shigang Yue
Deposited On:11 Jun 2010 13:19
Last Modified:04 Dec 2013 15:54

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