Optimal navigation of microswimmers in complex and noisy environments

TL;DR

This paper introduces semi-autonomous navigation strategies for microswimmers that optimize travel time in complex, noisy environments without external feedback, showing robustness and performance comparable to optimal control methods.

Contribution

The authors develop simple, semi-autonomous navigation protocols for microswimmers that achieve near-optimal travel times without external control, unlike traditional control-based strategies.

Findings

Strategies show arrival time statistics similar to stochastic optimal control.

Protocols are robust to environmental changes and fluctuations.

Applicable to broader optimization problems.

Abstract

We design new navigation strategies for travel time optimization of microscopic self-propelled particles in complex and noisy environments. In contrast to strategies relying on the results of optimal control theory, these protocols allow for semi-autonomous navigation as they do not require control over the microswimmer motion via external feedback loops. Although the strategies we propose rely on simple principles, they show arrival time statistics strikingly similar to those obtained from stochastic optimal control theory, as well as performances that are robust to environmental changes and strong fluctuations. These features, as well as their applicability to more general optimization problems, make these strategies promising candidates for the realization of optimized semi-autonomous navigation.