LiCS: Navigation using Learned-imitation on Cluttered Space

Fuente: arXiv
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Main Authors: Damanik, Joshua Julian, Jung, Jae-Won, Deresa, Chala Adane, Choi, Han-Lim
Format: Preprint
Published: 2024
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author Damanik, Joshua Julian
Jung, Jae-Won
Deresa, Chala Adane
Choi, Han-Lim
author_facet Damanik, Joshua Julian
Jung, Jae-Won
Deresa, Chala Adane
Choi, Han-Lim
contents In this letter, we propose a robust and fast navigation system in a narrow indoor environment for UGV (Unmanned Ground Vehicle) using 2D LiDAR and odometry. We used behavior cloning with Transformer neural network to learn the optimization-based baseline algorithm. We inject Gaussian noise during expert demonstration to increase the robustness of learned policy. We evaluate the performance of LiCS using both simulation and hardware experiments. It outperforms all other baselines in terms of navigation performance and can maintain its robust performance even on highly cluttered environments. During the hardware experiments, LiCS can maintain safe navigation at maximum speed of $1.5\ m/s$.
format Preprint
id arxiv_https___arxiv_org_abs_2406_14947
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle LiCS: Navigation using Learned-imitation on Cluttered Space
Damanik, Joshua Julian
Jung, Jae-Won
Deresa, Chala Adane
Choi, Han-Lim
Robotics
In this letter, we propose a robust and fast navigation system in a narrow indoor environment for UGV (Unmanned Ground Vehicle) using 2D LiDAR and odometry. We used behavior cloning with Transformer neural network to learn the optimization-based baseline algorithm. We inject Gaussian noise during expert demonstration to increase the robustness of learned policy. We evaluate the performance of LiCS using both simulation and hardware experiments. It outperforms all other baselines in terms of navigation performance and can maintain its robust performance even on highly cluttered environments. During the hardware experiments, LiCS can maintain safe navigation at maximum speed of $1.5\ m/s$.
title LiCS: Navigation using Learned-imitation on Cluttered Space
topic Robotics
url https://arxiv.org/abs/2406.14947