基于UWB距离测量的碰撞预测
Collision Prediction from UWB Range Measurements
摘要：
能够预测，从而作出反应，迎面而来的碰撞之间的一组移动代理是安全的自主运动，人类和机器人的基本要求。本文讨论的系统，使用移动代理之间的距离测量的碰撞预测的目的，其中包括预测代理的未来路径，知道他们是否会在任何时候发生碰撞。一个简单的系统将使用已知位置的静态锚来估计代理随时间的坐标，并使用轨迹来预测碰撞。基本上，碰撞预测不需要固定的坐标系，因此仅使用两个代理之间的成对范围可以用于预测碰撞。我们提出了下限分析，这表明这种成对的方法的局限性。作为一种替代的无锚方法，我们提出了基于朋友的自主碰撞预测和跟踪（FACT）方法，使用附近（未知位置移动）代理之间的所有测量范围，在分布式算法中，估计它们的相对位置和速度，并预测未来的代理之间的碰撞。通过分析和仿真，我们表明了FACT与其他方法相比具有相同或更好的碰撞检测性能，同时避免了对锚的需求。然后，我们建立了一个网络的$N$超宽带（UWB）设备和一个有效的多节点协议，允许所有的${\cal O}(N^2)$成对的范围进行测量，在$N$时隙。我们运行实验，多达六个独立的机器人代理移动和碰撞在一个二维平面和多达四个锚节点的碰撞预测方法的性能进行比较。我们表明，FACT方法可以比其他任何一种方法，但不需要一个固定的基础设施的锚节点。
英文摘要：
The ability to predict, and thus react to, oncoming collisions among a set of mobile agents is a fundamental requirement for safe autonomous movement, both human and robotic. This paper addresses systems that use range measurements between mobile agents for the purpose of collision prediction, which involves prediction of the agents' future paths to know if they will collide at any time. One straightforward system would use known-location static anchors to estimate agent coordinates over time, and use the track to predict collision. Fundamentally, no fixed coordinate system is required for collision prediction, so using only the pairwise range between two agents can be used to predict collision. We present lower bound analysis which shows the limitations of this pairwise method. As an alternative anchor-free method, we propose the friend-based autonomous collision prediction and tracking (FACT) method that uses all measured ranges between nearby (unknown location mobile) agents, in a distributed algorithm, to estimate their relative locations and velocities and predict future collisions between agents. Using analysis and simulation, we show the potential for FACT to achieve equal or better collision detection performance compared to other methods, while avoiding the need for anchors. We then build a network of $N$ ultra wideband (UWB) devices and an efficient multi-node protocol which allows all ${\cal O}(N^2)$ pairwise ranges to be measured in $N$ slots. We run experiments with up to six independent robot agents moving and colliding in a 2D plane and up to four anchor nodes to compare the performance of the collision prediction methods. We show that the FACT method can perform better than either other method but without the need for a fixed infrastructure of anchor nodes.
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