arXiv AI July 10, 2026 By Zhirui Dai, Qihao Qian, Tianxing Fan, Nikolay Atanasov

OREN: Octree Residual Network for Real-Time Euclidean Signed Distance Mapping

arXiv:2510. 18999v3 Announce Type: replace-cross Abstract: Reconstructing signed distance functions (SDFs) from point cloud data benefits many robot autonomy capabilities, including localization, mapping, motion planning, and control.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jul 22

From Distances to Trajectories: Real-Time Signed Distance Function Mapping and Distance-Accelerated Motion Planning for UAVs

arXiv:2607. 19306v1 Announce Type: cross Abstract: Autonomous flight in cluttered environments requires a robot to build a geometric map of its surroundings and plan safe, dynamically feasible trajectories, all onboard and in real time.

By Jason Stanley (UC San Diego, La Jolla, USA), Zhirui Dai (UC San Diego, La Jolla, USA), Qihao Qian (UC San Diego, La Jolla, USA), Tzu-Chin Ho (UC San Diego, La Jolla, USA), Tianxing Fan (UC San Diego, La Jolla, USA), Siddharth Saha (Shield AI, San Diego, USA), Christopher Barngrover (Shield AI, San Diego, USA), Ki Myung Brian Lee (UC San Diego, La Jolla, USA), Nikolay Atanasov (UC San Diego, La Jolla, USA)

agents robotics

arXiv AI

Jul 21

Depth Estimators Are Implicit Neural Fields for 3D Scene Geometry Inpainting and Reconstruction

arXiv:2607. 16286v1 Announce Type: cross Abstract: The 3D geometry of real-world scene data is often incomplete.

By Yingzhao Jian, Zihao Lin, Hehe Fan

benchmarks

arXiv AI

Jun 26

Learning Motion Feasibility from Point Clouds in Cluttered Environments

arXiv:2606. 26700v1 Announce Type: cross Abstract: Motion feasibility prediction plays a central role in robotics, particularly in task and motion planning and manipulation.

By Sajid Ansari, Arthi, Girish Varma, Antony Thomas

llms robotics benchmarks

arXiv AI

Jul 1

3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance

arXiv:2606. 31329v1 Announce Type: cross Abstract: Hierarchical Vision-Language-Action (VLA) models decouple high-level planning from low-level control to improve generalization in robot manipulation.

By Dongyoon Hwang, Byungkun Lee, Dongjin Kim, Hyojin Jang, Hoiyeong Jin, Jueun Mun, Minho Park, Hojoon Lee, Hyunseung Kim, Jaegul Choo

llms robotics multimodal benchmarks

arXiv Machine Learning

Jun 17

Can Vision Foundation Models Navigate? Zero-Shot Real-World Evaluation and Lessons Learned

arXiv:2603. 25937v2 Announce Type: replace-cross Abstract: Visual Navigation Models (VNMs) promise generalizable, robot navigation by learning from large-scale visual demonstrations.

By Maeva Guerrier, Karthik Soma, Jana Pavlasek, Giovanni Beltrame

llms diffusion robotics benchmarks

arXiv AI

1d ago

VGGT-Align: Bridging Local Reconstruction and Global Consistency for Long-Sequence 3D Reconstruction

arXiv:2608. 15260v1 Announce Type: cross Abstract: Maintaining global geometric consistency is a central challenge in long-sequence 3D reconstruction, with scale drift being the most critical failure mode.

By Wei Zhang, Yihang Wu, Songhua Li, Qi Wang

benchmarks safety

Related stories

From Distances to Trajectories: Real-Time Signed Distance Function Mapping and Distance-Accelerated Motion Planning for UAVs

Depth Estimators Are Implicit Neural Fields for 3D Scene Geometry Inpainting and Reconstruction

Learning Motion Feasibility from Point Clouds in Cluttered Environments

3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance

Can Vision Foundation Models Navigate? Zero-Shot Real-World Evaluation and Lessons Learned

VGGT-Align: Bridging Local Reconstruction and Global Consistency for Long-Sequence 3D Reconstruction