面向现实世界中的敏捷多机器人系统:用于相对定位的主动闪烁标记的快速机载跟踪

IF 5.2 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Tim Lakemann , Daniel Bonilla Licea , Viktor Walter , Tomáš Báča , Martin Saska
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引用次数: 0

摘要

本文介绍了一种新的机载跟踪方法,利用主动闪烁标记跟踪(AMT)实现基于视觉的相对定位和通信。多机器人团队成员的主动闪烁标记提高了紧密耦合多机器人系统中飞行器相对定位的鲁棒性,同时也作为一种弹性通信系统。传统的跟踪算法很难处理快速移动的闪烁标记,因为它们在相机帧中间歇性出现,并且在连续帧中关联多个这些标记的复杂性。AMT通过使用加权多项式回归来预测主动闪烁标记的未来外观,同时考虑到预测中的不确定性来解决这个问题。在室外实验中,AMT方法在跟踪密度、准确性和复杂性方面优于最先进的方法。实验验证了这种新型的相对定位和光通信跟踪方法,包括对敏捷多机器人部署研究所激发的运动模式进行测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards agile multi-robot systems in the real world: Fast onboard tracking of active blinking markers for relative localization
A novel onboard tracking approach enabling vision-based relative localization and communication using Active blinking Marker Tracking (AMT) is introduced in this article. Active blinking markers on multi-robot team members improve the robustness of relative localization for aerial vehicles in tightly coupled multi-robot systems during real-world deployments, while also serving as a resilient communication system. Traditional tracking algorithms struggle with fast-moving blinking markers due to their intermittent appearance in camera frames and the complexity of associating multiple of these markers across consecutive frames. AMT addresses this by using weighted polynomial regression to predict the future appearance of active blinking markers while accounting for uncertainty in the prediction. In outdoor experiments, the AMT approach outperformed state-of-the-art methods in tracking density, accuracy, and complexity. The experimental validation of this novel tracking approach for relative localization and optical communication involved testing motion patterns motivated by our research on agile multi-robot deployment.
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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