Smart navigation of a gravity-driven glider with adjustable center of mass

Artificial gliders are designed to disperse as they settle through a fluid, requiring precise navigation to reach target locations. We show that a compact glider settling in a viscous fluid can navigate by dynamically adjusting its center of mass. Using fully resolved direct numerical simulations and reinforcement learning, we find two optimal navigation strategies that allow the glider to reach its target location accurately. These strategies depend sensitively on how the glider interacts with the surrounding fluid. The nature of this interaction changes as the particle Reynolds number <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"> <a:msub> <a:mi>Re</a:mi> <a:mi>p</a:mi> </a:msub> </a:math> changes. Our results explain how the optimal strategy depends on <b:math xmlns:b="http://www.w3.org/1998/Math/MathML"> <b:msub> <b:mi>Re</b:mi> <b:mi>p</b:mi> </b:msub> </b:math> . At large <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"> <c:msub> <c:mi>Re</c:mi> <c:mi>p</c:mi> </c:msub> </c:math> , the glider learns to tumble rapidly by moving its center of mass as its orientation changes. This generates a large horizontal inertial lift force, which allows the glider to travel far. At small <d:math xmlns:d="http://www.w3.org/1998/Math/MathML"> <d:msub> <d:mi>Re</d:mi> <d:mi>p</d:mi> </d:msub> </d:math> , by contrast, high viscosity hinders tumbling. In this case, the glider learns to adjust its center of mass so that it settles with a steady, inclined orientation that results in a horizontal viscous force. The horizontal range is much smaller than for large <e:math xmlns:e="http://www.w3.org/1998/Math/MathML"> <e:msub> <e:mi>Re</e:mi> <e:mi>p</e:mi> </e:msub> </e:math> , because this viscous force is much smaller than the inertial lift force at large <f:math xmlns:f="http://www.w3.org/1998/Math/MathML"> <f:msub> <f:mi>Re</f:mi> <f:mi>p</f:mi> </f:msub> </f:math> .