@@ -166,7 +166,7 @@ <h2 class="subheader">Under Review</h1>
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< div class ="section base-row add-top-padding ">
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< h1 class ="tldr ">
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< b > TL;DR</ b > :
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- Robot See Robot Do uses a < b > 4D </ b > < b > D </ b > ifferentiable < b > P </ b > art < b > M </ b > odel (4D-DPM) to visually imitate articulated motions from an object scan and single monocular video .
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+ Botany-Bot uses Gaussian Splatting and Garfield to create a segmented 3D reconstruction of plants and then uses this to guide a robot's interaction with the plant to reveal even more information .
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</ h1 >
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< video id ="main-video " autobuffer muted autoplay loop controls playsinline >
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< source id ="mp4 " src ="data/supp_video.mp4 " type ="video/mp4 ">
@@ -181,7 +181,7 @@ <h1>Abstract</h1>
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<h1 class="tldr">
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Humans imitate manipulation by watching <b>object</b> motion, not <b>hand</b> motion. RSRD does the same. <br>
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This enables imitation from a single video robust to orientation and across the human-robot embodiment gap.
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<img src="data/favicon.png" style="height: 40px; margin-left: 5px; margin-right: 5px; margin-top: 40px; margin-bottom: 40px;">
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<h1>4D Part Reconstruction</h1>
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By creating part-aware 3D representations using <a href="https://www.garfield.studio/" class="author-text" target="_blank">GARField</a> (parts, toggle for clusters) and
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<a href="https://github.com/facebookresearch/dinov2" class="author-text"target="_blank">DINOv2</a> (tracking SE3 pose),
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these smartphone-captured inputs can generate these 4D reconstructions:
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- < h1 class ="tldr "> < b > Input demonstration video</ b > </ h1 >
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- < div class ="carousel-container " id ="videoCarousel ">
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+ <!-- < div id="main-results">
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+ <h1 class="tldr"><b>Input demonstration video</b></h1> -->
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<video autoplay muted loop playsinline height="400px">
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<source src="data/demo_vids/cal_bear_naked_wave.mp4" type="video/mp4">
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</video>
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<video autoplay muted loop playsinline height="400px">
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<source src="data/demo_vids/scissors2.mp4" type="video/mp4">
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</video>
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<video autoplay muted loop playsinline height="400px">
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<source src="data/demo_vids/sunglasses_fold.mp4" type="video/mp4">
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</video>
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</video>
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</div>
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<!-- <h1 class="tldr"><b>
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<img src="data/drag_icon.png" alt="" class="inline-image">Click and move me!<img src="data/drag_icon.png" alt="" class="inline-image">
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</b></h1> -->
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<div class="click-and-move-overlay">
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<h1 class="tldr">
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<b>
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<img src="data/favicon.png" style="height: 40px; margin-left: 5px; margin-right: 5px; margin-top: 40px; margin-bottom: 40px;">
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<img src="data/favicon.png" style="height: 40px; margin-left: 5px; margin-right: 5px; margin-top: 40px; margin-bottom: 40px;">
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<h1>Robot Motion Retargeting</h1>
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<p class="paragraph">
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After recovering 3D part motion, RSRD optimizes grasps and robot motions to reproduce the 4D reconstructions.
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</div>
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</div>
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<img src="data/favicon.png" style="height: 40px; margin-left: 5px; margin-right: 5px; margin-top: 40px; margin-bottom: 40px;">
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<img src="data/favicon.png" style="height: 40px; margin-left: 5px; margin-right: 5px; margin-top: 40px; margin-bottom: 40px;">
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Because 4D-DPM uses gradient descent, any differentiable prior is easily incorporated like temporal smoothness and rigidity.
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</p>
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<img src="data/4ddpm_ablation.jpg" style="max-width: 90%" />
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<h1>Retargeting Robot Trajectory</h1>
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<p class="paragraph">
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With the recovered 3D part motion and the object placed in the robot workspace,
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</p>
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<h1>Limitations and Failures</h1>
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<p class="paragraph">
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4D monocular reconstruction is an extremely under-constrained and challenging problem, and 4D-DPM still suffers from sensitivity to demonstration viewpoint, occlusions, reconstruction quality, and more.
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</video>
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<h1 id="abstract">Citation </h1>
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<p class="paragraph"> If you use this work or find it helpful, please consider citing: (bibtex) </p>
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<pre id="codecell0">@inproceedings{kerr2024rsrd,
@@ -643,7 +643,7 @@ <h1 id="abstract">Citation </h1>
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booktitle={8th Annual Conference on Robot Learning},
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year={2024},
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url={https://openreview.net/forum?id=2LLu3gavF1}
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</ pre >
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</ div >
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< footer >
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