◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Thomas Stastny

4 papers hereh-index 201.2k citations53 works total

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

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO4

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

cs.RO2026

Depth Completion in Unseen Field Robotics Environments Using Extremely Sparse Depth Measurements

Marco Job, Thomas Stastny, Eleni Kelasidi +2

Autonomous field robots operating in unstructured environments require robust perception to ensure safe and reliable operations. Recent advances in monocular depth estimation have…

cs.RO2026

Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics

Eugenio Cuniato, Mike Allenspach, Thomas Stastny +3

Tilt-rotor aerial robots are more dynamic and versatile than fixed-rotor platforms, since the thrust vector and body orientation are decoupled. However, the coordination of servos…

cs.RO2025

Safe Periodic Trochoidal Paths for Fixed-Wing UAVs in Confined Windy Environments

Jaeyoung Lim, David Rohr, Thomas Stastny +1

Due to their energy-efficient flight characteristics, fixed-wing type UAVs are useful robotic tools for long-range and duration flight applications in large-scale environments. How…

cs.RO2024

Radar Meets Vision: Robustifying Monocular Metric Depth Prediction for Mobile Robotics

Marco Job, Thomas Stastny, Tim Kazik +2

Mobile robots require accurate and robust depth measurements to understand and interact with the environment. While existing sensing modalities address this problem to some extent,…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.