Author

Nils Dengler

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Preprint Sep 2026

PolyUMI: Accessible Visual-Tactile-Audio Data Collection for Object Inference and Manipulation

Humans typically rely on vision, touch, hearing, and proprioception to perceive contact and adapt their actions during manipulation. Providing robots with comparable responsiveness therefore requires hardware that can retain and use these complementary sensory signals. Most imitation-learning systems, however, observe...

Conor W. Hayes, Rickmer Krohn, Aravind Ramaswami et al. · 0 citations

Preprint Sep 2026

MS-MEM: Multi-Skill Manipulation-Enhanced Mapping via Uncertainty- and Disturbance-Aware Action Selection

Experimental results show that, compared with single-skill and unconstrained baselines that ignore scene disturbance, MS-MEM achieves higher mapping accuracy while substantially reducing scene disturbance, highlighting the synergistic effects of active viewpoint selection, push, and grasp actions.

Yi-Tian Shi, Jesper Mücke, Nils Dengler et al. · 0 citations

Preprint Aug 2026

Semantic- and Density-Aware Planning for Accessibility-Preserving Multi-Object Placement

Semantic-Dense Placement Planning (SDPP) is proposed, an accessibility-preserving approach that ranks candidate poses using a semantic-density score combining inter-object semantic similarity with spatial proximity and significantly improves semantic placement quality over state-of-the-art baselines.

Benno Wingender, Nils Dengler, Nicolas Busch et al. · 0 citations