论文标题
用于分布式多机器人本地化的最小能量过滤器
A Minimum Energy Filter for Distributed Multirobot Localisation
论文作者
论文摘要
我们通过应用最小能量过滤理论提出了一种解决合作定位问题的新方法。我们考虑在机器人可以感知固定地标和附近的机器人以及通过通信渠道与其他人共享信息的环境中估算一组移动机器人姿势的问题。尽管绝大多数现有文献都应用了卡尔曼过滤器的某种变体，但我们根据最小能量过滤的原理得出了一组全球状态估算的滤波器方程。我们展示了如何将过滤器方程解耦，并且计算分布在网络中的机器人中，而无需中央处理节点。最后，我们在模拟中提供了过滤器性能的演示。
We present a new approach to the cooperative localisation problem by applying the theory of minimum energy filtering. We consider the problem of estimating the pose of a group of mobile robots in an environment where robots can perceive fixed landmarks and neighbouring robots as well as share information with others over a communication channel. Whereas the vast majority of the existing literature applies some variant of a Kalman Filter, we derive a set of filter equations for the global state estimate based on the principle of minimum energy filtering. We show how the filter equations can be decoupled and the calculations distributed among the robots in the network without requiring a central processing node. Finally, we provide a demonstration of the filter's performance in simulation.
