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<!DOCTYPE html>
<html>
<head>
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<meta name="description" content="ASFM: Augmented Social Force Model for Legged Robot Social Navigation">
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<title>ASFM: Augmented Social Force Model for Legged Robot Social Navigation</title>
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<h1 class="title is-1 publication-title">ASFM: Augmented Social Force Model <br> for Legged Robot Social Navigation</h1>
<div class="is-size-4 publication-authors">
<span class="author-block">
<a href="https://rpl-as-ucl.github.io/people/">Sebastian Aegidius</a>
<a href="https://www.imperial.ac.uk/personal-robotics/people/post-doctoral-researchers-and-research-assistants/dr-rodrigo-chacon-quesada/">Rodrigo Chacón-Quesada</a>
<a href="">Andromachi Maria Delfaki</a>
<br>
<a href="https://www.imperial.ac.uk/people/y.demiris">Yiannis Demiris</a>
<a href="https://dkanou.github.io/">Dimitrios Kanoulas</a>
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<h2 class="title is-3">Under Review</h2>
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<!-- Video 1 -->
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<video controls autoplay muted loop style="max-width: 100%; border: 1px solid #bbb; border-radius: 10px;">
<source src="./resources/ASFM1.mp4" type="video/mp4">
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<p>Meeting an oncoming pedestrian.</p>
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<p>Navigating around a crowd in narrow space</p>
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<p>Following a guide through a crowded area</p>
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<p>Reacting to seen and unseen pedestrians</p>
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<h3 class="title is-2">Abstract</h3>
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<p> Social navigation in robotics primarily involves guiding mobile robots through human-populated areas, with pedestrian comfort balanced with efficient path-finding. Al- though progress has been seen in this field, a solution for the seamless integration of robots into pedestrian settings remains elusive. In this paper, a social force model for legged robots is developed, utilizing visual perception for human localization. In particular, an augmented social force model is introduced, incorporating refined interpretations of repulsive forces and avoidance behaviors based on pedestrian actions, alongside a target following mechanism. Experimental evaluation on a quadruped robot, through various scenarios, including interac- tions with oncoming pedestrians, crowds, and obstructed paths, demonstrates that the proposed augmented model significantly improves upon previous state-of-the-art methods in terms of chosen path length, average velocity, and time-to-goal for effective and efficient social navigation. </p>
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<h3 class="title is-2">ASFM vs SFM</h3>
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<p>
We present the Augmented Social Force Model (ASFM) for social navigation and compare it with the standard Social Force Model (SFM).
</p>
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