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cs.RO2026

When Your State Estimator Has Lost The Plot: Detecting Estimator Failures Via Spectral Analysis

Christian Lanegger, Helen Oleynikova, Roland Siegwart +1

Reliable onboard state estimation is essential for safe robotic operation, yet unmodeled disturbances, such as sensor aliasing or out-of-distribution noise, still cause estimators…

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.RO2024

Evaluation of Human-Robot Interfaces based on 2D/3D Visual and Haptic Feedback for Aerial Manipulation

Julien Mellet, Mike Allenspach, Eugenio Cuniato +3

Most telemanipulation systems for aerial robots provide the operator with only 2D screen visual information. The lack of richer information about the robot's status and environment…

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,…

cs.RO2024

Enhancing Sliding Performance with Aerial Robots: Analysis and Solutions for Non-Actuated Multi-Wheel Configurations

Tong Hui, Jefferson Ghielmini, Dimitrios Papageorgiou +3

Sliding tasks performed by aerial robots are valuable for inspection and simple maintenance tasks at height, such as non-destructive testing and painting. Although various end-effe…