Cooperatively Localizing robots should seek optimal control strategies to maximize precision of position estimation and ensure safety in flight. Observability-Aware Trajectory Optimization has strong potential to address this issue, but no concrete link between observability and precision has been proven yet. In this paper, we prove that improvement in positioning precision inherently follows from optimizing observability. Based on this finding, we develop an Observability-Aware Control principle to generate observability-optimal control strategies. We implement this principle in a Model Predictive Control framework, and we verify it on a team of quadrotor Unmanned Aerial Vehicles comprising a follower vehicle localizing itself by tracking a leader vehicle in both simulations and real-world flight tests. Our results demonstrate that maximizing observability contributed to improving global positioning precision for the quadrotor team.

翻译：协同定位的机器人应寻求最优控制策略，以最大化位置估计精度并确保飞行安全。可观测性感知轨迹优化在解决此问题上具有巨大潜力，但可观测性与精度之间的具体关联尚未得到证明。本文证明了定位精度的提升本质上源于对可观测性的优化。基于这一发现，我们提出了一种可观测性感知控制原理，用于生成可观测性最优的控制策略。我们在模型预测控制框架中实现了该原理，并通过仿真和实际飞行测试，在一个由跟随无人机（通过追踪领航无人机实现自身定位）组成的四旋翼无人机编队中进行了验证。结果表明，最大化可观测性有助于提升四旋翼无人机编队的全局定位精度。