Bat target tracking strategies for prey interception

ABSTRACT

Insectivorous bats capture their prey in flight with impressive success. They rely on the echoes of their own ultrasonic vocalization that yield acoustic snapshots, which enable target tracking on a rapid time scale. This task requires the use of intermittent information to navigate a dynamically changing environment. Bats may solve this challenging task by building internal models that estimate target velocity to anticipate the future location of a prey item. This has been recently tested empirically in perched bats tracking a target moving across their acoustic field. In this report, we build on past work to propose a new model that describes bat flight trajectories employing predictive strategies. Furthermore, we compare this model with a previous model of bat target interception that has also been employed by some visually guided animals: parallel navigation.

Abbreviations: HTTP, Hybrid Target Trajectory Prediction; CATD, Constant Absolute Target Direction; CB, Constant Bearing; PN, Parallel Navigation

KEYWORDS:

• Echolocation
• predictive tracking
• steering laws
• echolocation
• parallel navigation

Disclosure of Potential Conflicts of Interest

All code used in this work is made available through GitHub.

Additional information

Funding

Work was funded by a Human Frontiers Science Program fellowship awarded to AS [LT000220/2018], National Science Foundation fellowship awarded to CD [GRFP 2018261398]. National Science Foundation Brain Initiative [NCS-FO 1734744 (2017-2021)], AFOSR [FA9550-14-1-0398NIFTI] and ONR [N00014-17-1-2736] grants to CFM supported research that motivated the models presented here.