Testbed Design for Robot Navigation through Differential Ray Tracing

被引:1
作者
Amatare, Sunday [1 ]
Samson, Michelle [1 ]
Roy, Debashri [1 ]
机构
[1] Univ Texas Arlington, Dept Comp Sci & Engn, Arlington, TX 76019 USA
来源
2024 IEEE INTERNATIONAL SYMPOSIUM ON DYNAMIC SPECTRUM ACCESS NETWORKS, DYSPAN 2024 | 2024年
关键词
D O I
10.1109/DySPAN60163.2024.10632751
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In recent years, there has been a surge in interest towards the refinement of autonomous systems, with a specific focus on advancing robot navigation through the effective utilization of sensing data. However, this heightened focus has brought forth significant privacy concerns. To address these issues and concurrently harness the advantages of sensing-based robot navigation, this paper introduces a testbed, designed to facilitate robot navigation via the application of a Differential Ray Tracing (DRT) approach. We delineate a systematic pipeline for constructing such a testbed, employing Lidar sensors from commercially available handheld devices. The acquired data is integrated into NVIDIA's Sionna tool. This integration process serves to enable the formulation of Radio Frequency (RF) propagation models tailored for mobile robots operating within indoor environments. This paper represents a significant stride toward the practical implementation of robot navigation by employing the RT-generated RF propagation of the environment. Through our proposed testbed, we contribute to the development of a robust and privacy-preserving approach for robot navigation in autonomous environment.
引用
收藏
页码:173 / 174
页数:2
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