A Novel Real-Time LiDAR Data Streaming Framework

Anand, Bhaskar and Kambhampaty, Harish Rohan and Rajalakshmi, P (2022) A Novel Real-Time LiDAR Data Streaming Framework. IEEE Sensors Journal. pp. 1-10. ISSN 1530-437X

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Data transmission of familiar sensor data sources like video and audio is well explored. However, data acquired from the sensor emitting voluminous data can not easily be transmitted due to a lack of bandwidth, which causes bottlenecks in the transmission. One valuable sensor in autonomous vehicles is Light Detection and Ranging (LiDAR). In this paper, a novel framework has been proposed which is capable of efficiently streaming LiDAR data over the internet. The proposed framework consists of various subsystems that handle data in multiple stages. On the sender-side, the stages include data acquisition from the sensor, compression, encryption, and encoding of data, followed by transmission of encoded data over the internet. On the receiver-side, decoding, decryption, decompression, and data visualization are performed. The end-to-end framework runs over Robot Operating System (ROS) platform. The data is acquired via ROS topics on the sender side and again published on ROS topics from the browser on the receiver side. This allows the users to apply any processing algorithm online with tolerable latency. The challenge of Clock Synchronization was addressed during the testing process. A detailed analysis to validate the quality of decompressed data has also been performed for which cloud distance was used as a metric. The implemented model was able to perform data transmission with an average latency of 160.62 ms for low-resolution compression mode. IEEE

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IITH Creators:
IITH CreatorsORCiD
Rajalakshmi, Phttps://orcid.org/0000-0002-7252-6728
Item Type: Article
Uncontrolled Keywords: Data communication; Data visualization; Laser radar; LiDAR; Octree; Point cloud; Point cloud library (PCL); Receivers; Security; Sensors; Servers; WebRTC
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 23 Nov 2022 11:05
Last Modified: 23 Nov 2022 11:05
URI: http://raiith.iith.ac.in/id/eprint/11369
Publisher URL: https://doi.org/10.1109/JSEN.2022.3215189
OA policy: https://v2.sherpa.ac.uk/id/publication/3570
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