Quick Overview: This video presents the demo results of our paper: Semantic-Driven Voxel Representation for LiDAR–Inertial Odometry Author : Donghyun Kim and Jinwhan Kim* Paper Title : Hierarchical Planning for Vehicle Routing and Scheduling in Marsupial ... Supplemental video for “A High-Strength, Highly-Flexible Robotic Strap for Harnessing, Lifting, and Transferring Humans” ...

Ieee Ra L 2026 Bev - Detailed Overview & Context

This video presents the demo results of our paper: Semantic-Driven Voxel Representation for LiDAR–Inertial Odometry Author : Donghyun Kim and Jinwhan Kim* Paper Title : Hierarchical Planning for Vehicle Routing and Scheduling in Marsupial ... Supplemental video for “A High-Strength, Highly-Flexible Robotic Strap for Harnessing, Lifting, and Transferring Humans” ... 215 points, weeks of work, and a great run! Please see: [1] Z. Wu et al., 'Towards a Physics-Based Model for Steerable Eversion Growing Robots', Recent visual autonomous perception systems achieve remarkable performances with deep representation learning. However ...

Title: Scalable Modular Inflatable Origami Robots with Proprioceptive Length Control Authors: Minji Kim, Hyunkyu Park, Jung Kim, ... Transition Gradient from Standing to Traveling Waves for Energy-Efficient Slope Climbing of a Gecko-Inspired Robot Paper web ...

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[IEEE RA-L 2026] BEV-OSP: Obstacle State Prediction in Bird's-Eye View to Enable Obstacle Avoidance
[RA-L & ICRA 2026] Semantic-Driven Voxel Representation for LiDAR–Inertial Odometry | Demo Video
[RA-L 2026]Hierarchical Planning for Vehicle Routing and Scheduling in Marsupial Robotic Systems
Robotic Strap | IEEE RA-L 2023
ICRA 2026 - Join us in Vienna!
Our Perfect Run! IEEE Hardware Robotics 2026.
[IEEE RA-L'25] Intent Prediction-Driven MPC for UAV Planning and Navigation in Dynamic Environments
[RA-L 2026] TLC-Calib | Supplementary Video
IEEE RAL paper video introduction
IEEE at ERF 2026
Towards a Physics-Based Model for Steerable Eversion Growing Robots - IEEE RA-L 2023
Toward Deep Representation Learning for Event-Enhanced Visual Autonomous Perception (IEEE T-RO 2026)
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