论文标题
通过UWB和限制的通信多代理相对姿势估计
Multi-Agent Relative Pose Estimation with UWB and Constrained Communications
论文作者
论文摘要
对于在没有外部定位基础设施或先前的环境知识的情况下运行的任何多机器人系统，相对定位对于任何多机器人系统至关重要。我们提出了一个新型的质地间相对2D姿势估计系统，每个参与代理都配备了几个超宽带（UWB）范围标签。先前的工作通常会补充UWB范围的测量值，并具有其他连续传输的数据，例如探测器，使这些方法随着群体的增加或通信吞吐量的减少而缩小尺寸较差。这种方法通过仅使用本地收集的UWB测量值来解决这些问题，而没有其他传输数据。通过对我们提出的优化解决方案中观察到的范围偏差和系统的天线障碍物进行建模，我们的实验结果表明，在类似的最新方法中，改善了平均位置误差（同时在其他指标中保持竞争力），该方法还依赖于不断依赖于持续传播的遗传体。
Inter-agent relative localization is critical for any multi-robot system operating in the absence of external positioning infrastructure or prior environmental knowledge. We propose a novel inter-agent relative 2D pose estimation system where each participating agent is equipped with several ultra-wideband (UWB) ranging tags. Prior work typically supplements noisy UWB range measurements with additional continuously transmitted data, such as odometry, making these approaches scale poorly with increased swarm size or decreased communication throughput. This approach addresses these concerns by using only locally collected UWB measurements with no additionally transmitted data. By modeling observed ranging biases and systematic antenna obstructions in our proposed optimization solution, our experimental results demonstrate an improved mean position error (while remaining competitive in other metrics) over a similar state-of-the-art approach that additionally relies on continuously transmitted odometry.
