Energy efficiency and neural control of continuous versus intermittent swimming in a fishlike robot.

Many aquatic animals, including larval zebrafish, exhibit intermittent locomotion, moving via discrete swimming bouts followed by passive glides rather than continuous movement. However, fundamental questions remain unresolved: What neural mechanisms drive this behavior, and what functional benefits does this behavior offer? Specifically, is intermittent swimming more energy efficient than continuous swimming, and, if so, by what mechanism? Live-animal experiments pose technical challenges, because observing or manipulating internal physiological states in freely swimming animals is difficult. Hence, we developed ZBot, a bioinspired robot that replicates the morphological features of larval zebrafish. Embedding a network model inspired by neural circuits and kinematic recordings of larval zebrafish, ZBot reproduces diverse swimming gaits of larval zebrafish bout-and-glide locomotion. By testing ZBot swimming in both turbulent and viscous flow regimes, we confirm that viscous flow markedly reduces traveled distance but minimally affects turning angles. We further tested ZBot in these regimes to analyze how key parameters (tail-beating frequency and amplitude) influence velocity and power use. Our results show that intermittent swimming lowers the energetic cost of transport across most achievable velocities in both flow regimes. Although prior work linked this efficiency to fluid dynamics, like reduced glide drag, we identify an extra mechanism: better actuator efficiency. Mechanistically, this benefit arises because intermittent locomotion shifts the robot's actuators to higher inherent efficiency. This work introduces a fishlike robot capable of biomimetic intermittent swimming-with demonstrated energy advantages at relevant speeds-and provides general insights into the factors shaping locomotor behavior and efficiency in aquatic animals.