论文标题
用于分布的多个设备本地化的机器人网络
A Robot Web for Distributed Many-Device Localisation
论文作者
论文摘要
我们表明，彼此测量的机器人或其他设备的分布式网络可以通过有效的临时同行与同伴通信进行协作以在全球范围内进行协作。我们的机器人Web解决方案基于高斯信念传播对基本的非线性因子图的传播，该图描述了所有观测机器人内部或彼此之间形成的所有观测值的概率结构，并且对于任何类型的机器人，运动或传感器都是灵活的。我们定义了一个简单有效的通信协议，可以通过发布和阅读网页或其他异步通信技术来实现。我们在模拟中显示了最多1000个机器人以任意模式相互作用的机器人，我们的解决方案可以在具有高度分布式计算和通信的分布式效率的同时，在运行高的集中式非线性因子图形求解器中，可以互动地达到全球精度。通过在GBP中使用强大因素，我们的方法可以耐受传感器测量或丢弃的通信数据包中的故障比例。
We show that a distributed network of robots or other devices which make measurements of each other can collaborate to globally localise via efficient ad-hoc peer to peer communication. Our Robot Web solution is based on Gaussian Belief Propagation on the fundamental non-linear factor graph describing the probabilistic structure of all of the observations robots make internally or of each other, and is flexible for any type of robot, motion or sensor. We define a simple and efficient communication protocol which can be implemented by the publishing and reading of web pages or other asynchronous communication technologies. We show in simulations with up to 1000 robots interacting in arbitrary patterns that our solution convergently achieves global accuracy as accurate as a centralised non-linear factor graph solver while operating with high distributed efficiency of computation and communication. Via the use of robust factors in GBP, our method is tolerant to a high percentage of faults in sensor measurements or dropped communication packets.
