Collision-Free Path Generation for Teleoperation of Unmanned Vehicles

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Teleoperation, or remote driving, constitutes a crucial transitional phase toward the widespread adoption of fully autonomous vehicles. Nevertheless, to enable seamless real-time teleoperation, it is imperative to address the time delay between the driver and the vehicle. Collision-free path generation has emerged as a vital technique facilitating both teleoperation and autonomous driving, particularly in high-level path planning for vehicles. In the context of real-time teleoperation, a generated collision-free path serves as a valuable guide for the teleoperator, effectively mitigating the impact of time delay. In this research, we present a framework dubbed dual transformer network (DTNet), designed to cater to the needs of teleoperation by addressing road scene understanding. The proposed DTNet employs two transformer-based networks to effectively segment the road free space and detect road objects. Additionally, we introduce an innovative fusion mechanism that leverages the combined information from both networks to predict a collision-free path. The efficacy of the DTNet is extensively evaluated using a large-scale BDD100k dataset, substantiating its superior performance in road free space segmentation and road object detection tasks. Remarkably, DTNet achieves a mean intersection over union score of 83.89% for road free space segmentation and an impressive mean average precision score of 34.20% for road object detection. The experimental findings affirm the effectiveness of the DT-Net framework in addressing the challenges of road scene understanding, making it a promising solution to provide a robust and efficient approach for collision-free path generation, with broader implications for the advancement of autonomous driving technologies.

    Original languageBritish English
    Title of host publication2023 21st International Conference on Advanced Robotics, ICAR 2023
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages21-27
    Number of pages7
    ISBN (Electronic)9798350342291
    DOIs
    StatePublished - 2023
    Event21st International Conference on Advanced Robotics, ICAR 2023 - Abu Dhabi, United Arab Emirates
    Duration: 5 Dec 20238 Dec 2023

    Publication series

    Name2023 21st International Conference on Advanced Robotics, ICAR 2023

    Conference

    Conference21st International Conference on Advanced Robotics, ICAR 2023
    Country/TerritoryUnited Arab Emirates
    CityAbu Dhabi
    Period5/12/238/12/23

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