Ant visual route navigation: How the fine details of behaviour promote successful route performance and convergence

Abstract

Individually foraging ants use egocentric views as a dominant navigation strategy for learning and retracing routes. Evidence suggests that route retracing can be achieved by algorithms which use views as visual compasses, where individuals choose the heading that leads to the most familiar visual scene when compared to route memories. However, such a mechanism does not naturally lead to route approach, and alternative strategies are required to enable convergence when off-route and for correcting on-route divergence. In this work we investigate how behavior incorporated into visual compass like route learning and recapitulation strategies might enable convergence to a learned route and its destination. The most successful recapitulation method comes from a cast and surge approach, a mechanism seen across arthropods for olfactory navigation. In this strategy casts form a zig-zagged or oscillatory search in space for familiar views, and surges exploit visual familiarity gradients. We also find that performance improves if the learned route consists of an oscillatory motor mechanism with learning gated to occur when the agent approaches the central axis of the oscillation. Furthermore, such oscillations combined with the cast and surge method additively enhance performance, showing that it benefits to incorporate oscillatory behavior in both learning and recapitulation. As destination reaching is the primary goal of navigation, we show that a suitably sized goal-orientated learning walk might suffice, but that the scale of this is dependent on route length and the route learning and recapitulation strategies enabled. Finally we show that view familiarity can modulate on-the-spot scans performed by an agent, providing a better reflection of ant behavior. Overall, our results show that the visual compass can provide a basis for robust visual navigation, so long as it is considered holistically with the details of basic motor and sensory-motor patterns of ants undertaking route learning and recapitulation. Author summaryAnts are capable of learning long visually guided routes. Given their small brains, it is assumed that they must have a computationally efficient strategy. The current dominant explanation for visual route guidance is that ants choose a direction to move in by comparing the current view (at different orientations) with views stored during learning, a so-called visual compass. These algorithms result in routes which typically run parallel to the training route, and do not explain how insects converge back onto a route when displaced. Using extensive simulations of ant route learning, we explore how innate behaviours and sensory motor strategies during learning and recapitulation can improve performance. We find that a mechanism which integrates a search strategy to sample a wider space by casting, interrupted by surging if the visual conditions are favourable, enhances convergence and goal reaching. We also show that altering the basic structure of learning routes to be oscillatory can significantly improve recapitulation. As well as emphasizing the importance of considering behaviour across both learning and recapitulation, this work gives a plausible account of robust route performance that maintains the elegant efficiency expected of insect navigation strategies.