talk by Franck Ruffier, invited by the Bernstein Focus Neuronal Basis of Learning: Insect inspired robots: The role of memory in decision making
*Department of Biorobotics, Institut des Sciences du Mouvement at CNRS & Universite Aix en Prevence, Marseille
To better grasp the visuomotor control system underlying insects height and speed control (Srinivasan et al. 1996, Portelli et al. 2010a), we attempted to interfere with this system by producing a major perturbation on the free flying insect and observing the effect of this perturbation. Honeybees were trained to fly along a high-roofed tunnel, part of which was equipped with a moving floor. The bees followed the stationary part of the floor at a given height. On encountering the moving part of the floor, which moved in the same direction as their flight, honeybees descended and flew at a lower height. In so doing, bees gradually restored their ventral optic flow (OF) to a similar optic flow value to that they had perceived when flying over the stationary part of the floor. OF restoration therefore relied on lowering the groundheight rather than increasing the groundspeed (Portelli, Ruffier, Franceschini 2010b).
This result can be accounted for by a control system called an optic flow regulator, that is, a feedback control system based on an OF sensor, which strives to maintain the ventrally perceived OF at a constant set point by adjusting the vertical lift (Ruffier, Franceschini 2005; Franceschini, Ruffier, Serres 2007). This visuo-motor control scheme may not only explain how honeybees land at a constant descent angle (Srinivasan et al. 2000) but also how they navigate safely along surfaces on the sole basis of OF measurements, without any need to measure either their speed or their distance from the ground, the ceiling or the surrounding walls (Serres et al. 2008, Portelli et al. 2010a), that is, without relying on any of the conventional avionic sensors such as velocimeters or rangefinders.
Results obtained in neurophysiological, behavioural, and biorobotic studies on insect flight control were used to safely land a spacecraft on the Moon in a simulated environment. The optic flow regulator for automatic landing was tested in a realistic simulated Lunar environment (Valette et al. 2010). Visual information was provided using the ESA s PANGU software program and used to regulate the optic flow sensed during the descent of a 2-DOF spacecraft. The results of the simulation showed that a single 2-pixel optic flow sensor coupled to an optic flow regulator was able to robustly control the autonomous descent of the simulated lunar lander (See Fig. 2). Low gate located approximately 10 m above the ground was reached with reduced vertical and horizontal speeds of 4m/s and 5m/s, respectively. It was also established that optic flow sensing methods can be used successfully to cope with temporary sensor blinding and poor lighting conditions (Valette et al. 2010), as typically occurs at the Moon south pole that the 2018 Next ESA mission is planning to explore.
References : N. Franceschini, F. Ruffier, J. Serres (2007) A bio-inspired flying robot sheds light on insect piloting abilities Current Biology, 17(4) :329-335
Feb 25, 2011 | 11:30 AM - 12:30 PM
Seminarraum II, Zoology, Königin-Luise Strasse 1-3