Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

10-2024

Abstract

We address the challenge of multi-LiDAR interference, an issue of growing importance as LiDAR sensors are embedded in a growing set of pervasive devices. We introduce a novel approach named D2SR, enabling decentralized interference detection, mitigation, and recovery without explicit coordination among nearby LiDAR devices. D2SR comprises three stages: (a) Detection, which identifies interfered frames, (b) Mitigation, which performs time-shifting of a LiDAR’s active period to reduce interference, and (c) Recovery, which corrects or reconstructs the depth values in interfered regions of a depth frame. Key contributions include a lightweight interference detection algorithm achieving an F1-score of 92%, a simple yet effective decentralized de-synchronization mechanism, and a lightweight depth recovery pipeline that preserves high throughput processing on edge devices. Evaluation on Nvidia Jetson devices demonstrates D2SR’s efficacy: under static settings, D2SR accurately detects interference in 93% of cases (recall=82%) and reduces the depth estimation error by 27% (RMSE= 38.7 cm, compared to RMSE= 60.6 cm for a baseline without D2SR). Furthermore, D2SR is able to reduce the fraction of interfered frames by 75.1% and reduce the depth estimation error (for interfered frames) by 24.9% even for a moving robot scenario.

Keywords

LiDAR Interference, Multi-Robot Systems

Discipline

Artificial Intelligence and Robotics | Databases and Information Systems

Research Areas

Data Science and Engineering

Areas of Excellence

Digital transformation

Publication

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024): Abu Dhabi, October 14-18: Proceedings,

First Page

1

Last Page

8

Publisher

IEEE

City or Country

Piscataway, NJ

Embargo Period

8-26-2024

Copyright Owner and License

Authors

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