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Roland Siegwart

Professor and Lab Director

ETH Zürich

Switzerland

Research Interests

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About

Roland Siegwart is a Professor and Lab Director at ETH Zurich, Switzerland. His research areas encompass the evaluation of human-robot interfaces, aerial manipulation, geometric tracking control, and cooperative path planning for autonomous navigation. Recent publications highlight his work on haptic feedback systems, trajectory optimization for wheeled robots, and reactive navigation strategies.

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Collaborators (15)

Lukas Rosenberger Schmid

Professor of Machine Intelligence

University of Technology Nuremberg

GERMANY

Roland Siegwart

Research Interests

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About

Articles (25)

Toward Enhanced Sliding Performance With Aerial Robots: Analysis, Solutions, and Practical Insights

Toward Open-Source and Modular Space Systems With ATMOS

Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics

Towards Robust Optimization-Based Autonomous Dynamic Soaring With a Fixed-Wing UAV

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

How to Shake Trees With Aerial Manipulators? A Theoretical and Experimental Study

Geometric Tracking Control of Omnidirectional Multirotors for Aggressive Maneuvers

Traversing Mars: Cooperative Informative Path Planning to Efficiently Navigate Unknown Scenes

Comparison Between Behavior Trees and Finite State Machines

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

Unified Guidance and Jerk-Level Dynamic Inversion for Accurate Position Control of Hybrid UAVs

Safe Low-Altitude Navigation in Steep Terrain With Fixed-Wing Aerial Vehicles

Controlled Shaking of Trees With an Aerial Manipulator

Non-Smooth Trajectory Optimization for Wheeled Balancing Robots with Contact Switches and Impacts

Panoptic Vision-Language Feature Fields

Probabilistic Network Topology Prediction for Active Planning: An Adaptive Algorithm and Application

Robust Sampling-Based Control of Mobile Manipulators for Interaction With Articulated Objects

Sampling-Based Path Planning in Highly Dynamic and Crowded Pedestrian Flow

Dynablox: Real-Time Detection of Diverse Dynamic Objects in Complex Environments

Reinforcement Learning for Outdoor Balloon Navigation: A Successful Controller for an Autonomous Balloon

maplab 2.0 – A Modular and Multi-Modal Mapping Framework

A Planning-and-Control Framework for Aerial Manipulation of Articulated Objects

Adaptive Tank-based Control for Aerial Physical Interaction with Uncertain Dynamic Environments Using Energy-Task Estimation

Continual Adaptation of Semantic Segmentation Using Complementary 2D-3D Data Representations

Embodied Active Domain Adaptation for Semantic Segmentation via Informative Path Planning

Collaborators (15)

Lukas Rosenberger Schmid

Claudio Pacchierotti

Jonas Frey

Christian Smith

Kuanqi Cai

Cristian Secchi

Mirko Kovac

Olov Andersson

Tong Hui

Jen Jen Chung

Francesco Milano

Antonio Franchi

Anibal Ollero

Gunnar Tibert

José Guillermo Heredia Benot

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