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

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