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@@ -71,7 +71,7 @@ <h2>ICRA 2024 Papers on Autonomous Navigation under Uncertainty
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</h2><br />
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<div style="text-align: center;"><video width="560" height="315" controls> <source src="./Lin_ICRA24_Video.mp4" type=video/mp4> </video><br />
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</div><br />
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We recently presented three papers at ICRA 2024 addressing different forms of autonomous navigation under uncertainty. The first paper, "Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning,"
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We recently presented three papers at ICRA 2024 addressing autonomous navigation under different types of uncertainty. The first paper, "Decentralized Multi-Robot Navigation for Autonomous Surface Vehicles with Distributional Reinforcement Learning,"
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addresses ASV navigation in congested and disturbance-filled environments. A preprint of the paper is available on <a style="font-weight: bold;" href="https://arxiv.org/abs/2402.11799">arXiv</a>, the corresponding code is available on <a style="font-weight: bold;" href="https://github.com/RobustFieldAutonomyLab/Multi_Robot_Distributional_RL_Navigation">GitHub</a>,
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and more details are illustrated in the accompanying <a style="font-weight: bold;" href="https://robustfieldautonomylab.github.io/Lin_ICRA24_Video.mp4">video attachment</a> (shown above). This research was
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led by Xi Lin.

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