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Frank Kirchner

7 papers hereh-index 14 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4
  • last author3

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.RO4
  • cs.LG2
  • cs.AI1
same name
  • Frank Kirchner — 11 papers, h 4
  • Frank Kirchner — 4 papers, h 4
  • Frank Kirchner — 3 papers, h 1
  • Frank Kirchner — 3 papers, h 3
  • Frank Kirchner — 3 papers, h 2
  • Frank Kirchner — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators
Showing cs.ROShow all

4 papers · 1 filter

cs.RO2026

Hardware-Accelerated Instance Segmentation for Resource-Constrained Space Robotics with Criticality Analysis

Siddhant Shete, Hilmi Dogu Kücüker, Udo Frese +1

Autonomous lunar missions require real-time per- ception under three coupled constraints: extreme low-light conditions, limited onboard compute, and radiation-induced hardware faul…

cs.RO2026

DINO-Explorer: Active Underwater Discovery via Ego-Motion Compensated Semantic Predictive Coding

Yuhan Jin, Nayari Marie Lessa, Mariela De Lucas Alvarez +4

Marine ecosystem degradation necessitates continuous, scientifically selective underwater monitoring. However, most autonomous underwater vehicles (AUVs) operate as passive data lo…

cs.RO2026

Contextual Multi-Task Reinforcement Learning for Autonomous Reef Monitoring

Melvin Laux, Yi-Ling Liu, Rina Alo +4

Although autonomous underwater vehicles promise the capability of marine ecosystem monitoring, their deployment is fundamentally limited by the difficulty of controlling vehicles u…

cs.RO2025

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning

Octavio Arriaga, Rebecca Adam, Melvin Laux +4

Real-world robotic applications, from autonomous exploration to assistive technologies, require adaptive, interpretable, and data-efficient learning paradigms. While deep learning…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.