Warping (Franz et al., Biological Cybernetics 79(3), 191-202, 1998b) and 2D-warping (Möller, Robotics and Autonomous Systems 57(1), [87][88][89][90][91][92][93][94][95][96][97][98][99][100][101] 2009) are effective visual homing methods which can be applied for navigation in topological maps. This paper presents several improvements of 2D-warping and introduces two novel "free" warping methods in the same framework. The free warping methods partially lift the assumption of the original warping method that all landmarks have the same distance from the goal location. Experiments on image databases confirm the effect of the improvements of 2D-warping and show that the two free warping methods produce more precise home vectors and approximately the same proportion of erroneous home vectors. In addition, two novel and easier-to-interpret performance measures for the angular error are introduced.

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Abstract. In this study we present an empirical experiment investigating obstacle avoidance and path selection behavior in rats and a number of visually-guided models that could account for the empirical data. In the experiment, the animals were repeatedly released into an open arena containing several obstacles and a single feeder that was marked by a large visual landmark. We recorded and analyzed the animals' trajectories as they approached the feeder. We found that the animals adapted their paths according to the specific obstacle configurations not only to avoid the obstacles that were blocking the direct path, but also to select optimal or near-optimal trajectories. On basis of these results, we then develop and present a series of minimalistic models of obstacle avoidance and path selection behavior that are based purely on visual input. In contrast to standard approaches to obstacle avoidance and path planning, our models do not require a map-like representation of space.

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