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<h1 class="title is-1 publication-title">POGS: Persistent Object Gaussian Splat for Tracking Human and Robot Manipulation of Irregularly Shaped Objects</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://uynitsuj.github.io">Justin Yu</a><sup>*1</sup>,</span>
<span class="author-block">
<a href="">Kush Hari</a><sup>*1</sup>,</span>
<span class="author-block">
<a href="https://el-refai.github.io/">Karim El-Refai</a><sup>*1</sup>,
</span>
<span class="author-block">
<a href="">Arnav Dalil</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="">Justin Kerr</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="">Chung-Min Kim</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="">Richard Cheng</a><sup>2</sup>,
</span>
<span class="author-block">
<a href="">Muhammad Zubair Irshad</a><sup>2</sup>,
</span>
<span class="author-block">
<a href="">Ken Goldberg</a><sup>1</sup>
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<span class="author-block"><sup>1</sup>University of California, Berkeley</span>
<span class="author-block"><sup>2</sup>Toyota Research Institute</span>
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<h2 class="subtitle has-text-centered">
<span class="dnerf"><b>POGS</b></span> persistently tracks object states in the real world robot workspace.
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<h2 class="title is-3">Abstract</h2>
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<p>
Tracking and manipulating irregularly-shaped, previously unseen objects in dynamic environments is important for robotic applications in manufacturing, assembly, and logistics. Recently introduced Gaussian Splats can efficiently model the geometry of such objects. We present <b>Persistent Object Gaussian Splat (POGS)</b>, a system that embeds semantics, self-supervised visual features, and object grouping features into a compact representation. Embedded visual features enable online and persistent object tracking and manipulation by dynamically updating the POGS as objects move, without the need for scene recapture or retraining. After an initial multi-view scene capture and training phase, POGS uses a single stereo camera to identify and track multiple objects online, supporting grasping, reorientation, and natural language queries. We evaluate POGS through physical robot experiments on two tasks: sequential pick-and-place where a human randomly arranges irregular objects to different poses between grasps and tool in-gripper visual servoing to track a target as a human moves both the target and perturbs the tool in the robot gripper.
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<h2 class="title">BibTeX</h2>
<pre><code>@article{yu2025pogs,
author = {Yu, Justin and Hari, Kush and El-Refai, Karim and Dalil, Arnav and Kerr, Justin and Kim, Chung-Min and Cheng, Richard, and Irshad, Muhammad Z. and Goldberg, Ken},
title = {Persistent Object Gaussian Splat (POGS) for Tracking Human and Robot Manipulation of Irregularly Shaped Objects},
journal = {ICRA},
year = {2025},
}</code></pre>
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