PUB - Publikationen an der Universität Bielefeld

The need for robust and efficient obstacle avoidance algorithms for flying platforms increases at a fast pace. Strategies are required to maneuver around various obstacles. Since bumblebees are efficient fliers that need to navigate in cluttered environments, they are perfectly suitable test objects when seeking for avoidance strategies. In the present work, we study the maneuver of bumblebees confronted with a large rectangular obstacle lying on their direct path to the hive. The bumblebees could always evade the obstacle vertically or horizontally, e.g., fly over the obstacle or fly around the obstacle, respectively. The chosen evasion maneuver, i.e., the basic strategy employed by the bee, is considered the dependent variable. The influence of the distance to the obstacle, obstacle dimensions, acceleration, and flight speed were investigated and considered as independent variables. To evaluate the bumblebee behavior, linear regression, and the Horizontality Verticality Index (HV), an adaption of the Laterality Index, was used to estimate the preferred behavioral choice. Examination of the bumblebee behavior revealed a strong tendency towards vertical evasion at higher distances to the obstacle, while the bumblebees evaded close obstacles horizontally. This is reasonable because climbing in flapping-wing flight is aerodynamically more efficient in forward movement than in hover flight. A linear function based on the HV Index was defined to estimate a relationship between distance to obstacle and evasion maneuver. Depending on the dimensions of the obstacle, alternative slopes of the HV function could be identified, indicating an additional dependency on the height-to-width ratio. However, taking the obstacle shape into account does not improve the predictability of an L1 LASSO regression model. Finally, one possibility to include the HV index into a technical system as an element of an obstacle avoidance algorithm is discussed.