We propose a simulation-based model of flower finding in echolocating nectarivorous bats. In particular, we propose a behavior-based model that uses two sensorimotor loops to dock with flowers. The EchoVr, as we have termed our echo simulator, uses a bank of echoes collected by ensonifying real objects with a physical (bat-like) sonar device. Using the EchoVr, we built a 2D environment consisting of simulated objects. We trained a neural network to activate the correct sensorimotor loop based on the echoes received by the simulated bat. The model guides the simulated bat to dock successfully with the flower opening ( \(95\%\) success rate) by computing control commands solely from echoic inputs.