activity
20172026
most citedAn Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environments

306 citations · 619 across the 18 of their papers we have counts for

collaborators

23 papers

cs.RO2026

Continual Learning for 6-DoF Grasp Synthesis via Experience and Demonstrations

Giulio Schiavi, Andrei Cramariuc, Michael Pantic +1

Most current grasp synthesis systems are trained offline and remain fixed during deployment. While this works well when deployment conditions resemble the training data, performanc…

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.RO2024

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★ 1 cited

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

Pushing the Limits of Reactive Planning: Learning to Escape Local Minima

Isar Meijer, Michael Pantic, Helen Oleynikova +1

When does a robot planner need a map? Reactive methods that use only the robot's current sensor data and local information are fast and flexible, but prone to getting stuck in loca…