Simultaneous localization and mapping
PulseAugur coverage of Simultaneous localization and mapping — every cluster mentioning Simultaneous localization and mapping across labs, papers, and developer communities, ranked by signal.
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Shanghai Jiao Tong U. advances SLAM for dynamic, deformable environments
Researchers at Shanghai Jiao Tong University, led by Professor Hesheng Wang, are advancing Simultaneous Localization and Mapping (SLAM) beyond static environments. Their work focuses on enabling robots to navigate and u…
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ICRA 2026 opens with rat exoskeleton, VLA debate, and 28 new papers
The International Conference on Robotics and Automation (ICRA) 2026 has commenced in Vienna, featuring over 8,000 scholars. The opening day saw significant attention drawn to a rat exoskeleton for neurorehabilitation, w…
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Depth2Pose benchmark evaluates monocular depth models using camera pose
Researchers have introduced Depth2Pose, a new benchmark for evaluating monocular depth estimation models. This framework assesses depth quality based on the accuracy of camera pose estimation, a more practical metric fo…
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DynoSLAM uses GNNs for safer robot navigation in crowded spaces
Researchers have developed DynoSLAM, a novel Dynamic GraphSLAM architecture that integrates Graph Neural Networks (GNNs) into factor graph optimization for improved robot navigation in crowded environments. This system …
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FreeOcc framework offers training-free 3D occupancy prediction from visual data
Researchers have developed FreeOcc, a novel framework for open-vocabulary occupancy prediction that does not require any prior training or 3D annotations. This system processes monocular or RGB-D image sequences to buil…
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Holo360D dataset advances panoramic 3D reconstruction with continuous trajectories
Researchers have introduced Holo360D, a new large-scale dataset designed to improve panoramic 3D reconstruction. This dataset features over 109,000 panoramas with registered point clouds, meshes, and camera poses, addre…
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Flow4DGS-SLAM: Optical Flow-Guided 4D Gaussian Splatting SLAM
Researchers have developed Flow4DGS-SLAM, a novel framework that enhances Simultaneous Localization and Mapping (SLAM) by integrating optical flow with 4D Gaussian Splatting. This approach aims to improve the reconstruc…
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New system improves camera-to-mocap calibration for AR/VR and robotics
Researchers have developed a new system for calibrating and verifying multi-camera setups with optical motion capture, specifically addressing challenges posed by fisheye lenses. The system enhances robustness against c…