activity
20182026
most citedFrom Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation

35 citations · 55 across the 24 of their papers we have counts for

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13 papers · 1 filter

cs.RO2026

AnchorD: Metric Grounding of Monocular Depth Using Factor Graphs

Simon Dorer, Martin Büchner, Nick Heppert +1

Dense and accurate depth estimation is essential for robotic manipulation, grasping, and navigation, yet currently available depth sensors are prone to errors on transparent, specu…

cs.RO2025

ParkDiffusion: Heterogeneous Multi-Agent Multi-Modal Trajectory Prediction for Automated Parking using Diffusion Models

Jiarong Wei, Niclas Vödisch, Anna Rehr +2

Automated parking is a critical feature of Advanced Driver Assistance Systems (ADAS), where accurate trajectory prediction is essential to bridge perception and planning modules. D…

cs.RO2025

Collaborative Dynamic 3D Scene Graphs for Open-Vocabulary Urban Scene Understanding

Tim Steinke, Martin Büchner, Niclas Vödisch +1

Mapping and scene representation are fundamental to reliable planning and navigation in mobile robots. While purely geometric maps using voxel grids allow for general navigation, o…

cs.RO2024

Traffic and Safety Rule Compliance of Humans in Diverse Driving Situations

Michael Kurenkov, Sajad Marvi, Julian Schmidt +6

The increasing interest in autonomous driving systems has highlighted the need for an in-depth analysis of human driving behavior in diverse scenarios. Analyzing human data is cruc…

cs.RO2024

A Good Foundation is Worth Many Labels: Label-Efficient Panoptic Segmentation

Niclas Vödisch, Kürsat Petek, Markus Käppeler +2

A key challenge for the widespread application of learning-based models for robotic perception is to significantly reduce the required amount of annotated training data while achie…

cs.RO20222 cited

OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics

N. Passalis, S. Pedrazzi, R. Babuska +15

Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their r…