2 citations · 4 across the 35 of their papers we have counts for
35 papers
MS-MEM: Multi-Skill Manipulation-Enhanced Mapping via Uncertainty- and Disturbance-Aware Action Selection
Yitian Shi, Jesper Mücke, Nils Dengler +3
Accurate scene understanding in confined, cluttered spaces such as shelves is essential for service robots, as many everyday tasks require them to locate and retrieve objects relia…
Semantic- and Density-Aware Planning for Accessibility-Preserving Multi-Object Placement
Benno Wingender, Nils Dengler, Nicolas Busch +2
Long-term manipulation planning requires robots to reason not only about immediate task success but also about how current decisions affect future interactions with the environment…
ACME: A Multi-Cultural, Multi-Embodiment Social-Navigation Dataset
Shashank Rao Marpally, Allan Wang, Atharva Ghotavadekar +35
Understanding how robots and humans move in shared spaces is essential for designing effective social robot navigation policies and predicting human behavior. However, existing dat…
Designing Privacy-Preserving Visual Perception for Robot Navigation Based on User Privacy Preferences
Xuying Huang, Sicong Pan, Delphine Reinhardt +1
Visual navigation is a fundamental capability of mobile service robots, yet the onboard cameras required for such navigation can capture privacy-sensitive information and raise use…
RHINO-AR: An Augmented Reality Exhibit for Teaching Mobile Robotics Concepts in Museums
Nils Dengler, Tim Graf, Leif Van Holland +3
Understanding autonomous mobile robots is challenging for people without robotics expertise, because key processes such as sensing, mapping, and planning are invisible. We present…
Interpreting Context-Aware Human Preferences for Multi-Objective Robot Navigation
Tharun Sethuraman, Subham Agrawal, Nils Dengler +3
Robots operating in human-shared environments must not only achieve task-level navigation objectives such as safety and efficiency, but also adapt their behavior to human preferenc…
An Approach to Joint Hybrid Decision Making between Humans and Artificial Intelligence
Jonas D. Rockbach, Sven Fuchs, Maren Bennewitz
Due to the progress in artificial intelligence, it is important to understand how capable artificial agents should be used when interacting with humans, since high level authority…
A Robust Placeability Metric for Model-Free Unified Pick-and-Place Reasoning
Benno Wingender, Nils Dengler, Rohit Menon +2
Reliable manipulation of previously unseen objects remains a fundamental challenge for autonomous robotic systems operating in unstructured environments. In particular, robust pick…
Efficient Manipulation-Enhanced Semantic Mapping With Uncertainty-Informed Action Selection
Nils Dengler, Jesper Mücke, Rohit Menon +1
Service robots operating in cluttered human environments such as homes, offices, and schools cannot rely on predefined object arrangements and must continuously update their semant…
Multi-Objective Reinforcement Learning for Adaptable Personalized Autonomous Driving
Hendrik Surmann, Jorge de Heuvel, Maren Bennewitz
Human drivers exhibit individual preferences regarding driving style. Adapting autonomous vehicles to these preferences is essential for user trust and satisfaction. However, exist…
Auditory Localization and Assessment of Consequential Robot Sounds: A Multi-Method Study in Virtual Reality
Marlene Wessels, Jorge de Heuvel, Leon Müller +3
Mobile robots increasingly operate alongside humans but are often out of sight, so that humans need to rely on the sounds of the robots to recognize their presence. For successful…
Immersive Explainability: Visualizing Robot Navigation Decisions through XAI Semantic Scene Projections in Virtual Reality
Jorge de Heuvel, Sebastian Müller, Marlene Wessels +3
End-to-end robot policies achieve high performance through neural networks trained via reinforcement learning (RL). Yet, their black box nature and abstract reasoning pose challeng…
The Impact of VR and 2D Interfaces on Human Feedback in Preference-Based Robot Learning
Jorge de Heuvel, Daniel Marta, Simon Holk +2
Aligning robot navigation with human preferences is essential for ensuring comfortable, and predictable robot movement in shared spaces. While preference-based learning methods, su…
PeRoI: A Pedestrian-Robot Interaction Dataset for Learning Avoidance, Neutrality, and Attraction Behaviors in Social Navigation
Subham Agrawal, Nico Ostermann-Myrau, Nils Dengler +1
Robots are increasingly being deployed in public spaces such as shopping malls, sidewalks, and hospitals, where safe and socially aware navigation depends on anticipating how pedes…
EvidMTL: Evidential Multi-Task Learning for Uncertainty-Aware Semantic Surface Mapping from Monocular RGB Images
Rohit Menon, Nils Dengler, Sicong Pan +2
For scene understanding in unstructured environments, an accurate and uncertainty-aware metric-semantic mapping is required to enable informed action selection by autonomous system…
GO-VMP: Global Optimization for View Motion Planning in Fruit Mapping
Allen Isaac Jose, Sicong Pan, Tobias Zaenker +3
Automating labor-intensive tasks such as crop monitoring with robots is essential for enhancing production and conserving resources. However, autonomously monitoring horticulture c…
Map Space Belief Prediction for Manipulation-Enhanced Mapping
Joao Marcos Correia Marques, Nils Dengler, Tobias Zaenker +4
Searching for objects in cluttered environments requires selecting efficient viewpoints and manipulation actions to remove occlusions and reduce uncertainty in object locations, sh…
A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks
Murad Dawood, Ahmed Shokry, Maren Bennewitz
Reinforcement learning (RL) has been successfully applied to a variety of robotics applications, where it outperforms classical methods. However, the safety aspect of RL and the tr…
Evaluating Robot Influence on Pedestrian Behavior Models for Crowd Simulation and Benchmarking
Subham Agrawal, Nils Dengler, Maren Bennewitz
The presence of robots amongst pedestrians affects them causing deviation to their trajectories. Existing methods suffer from the limitation of not being able to objectively measur…
Safe Leaf Manipulation for Accurate Shape and Pose Estimation of Occluded Fruits
Shaoxiong Yao, Sicong Pan, Maren Bennewitz +1
Fruit monitoring plays an important role in crop management, and rising global fruit consumption combined with labor shortages necessitates automated monitoring with robots. Howeve…
Context-Based Meta Reinforcement Learning for Robust and Adaptable Peg-in-Hole Assembly Tasks
Ahmed Shokry, Walid Gomaa, Tobias Zaenker +5
Autonomous assembly is an essential capability for industrial and service robots, with Peg-in-Hole (PiH) insertion being one of the core tasks. However, PiH assembly in unknown env…
Physically-Consistent Parameter Identification of Robots in Contact
Shahram Khorshidi, Murad Dawood, Benno Nederkorn +2
Accurate inertial parameter identification is crucial for the simulation and control of robots encountering intermittent contact with the environment. Classically, robots' inertial…
A Neuromorphic Approach to Obstacle Avoidance in Robot Manipulation
Ahmed Faisal Abdelrahman, Matias Valdenegro-Toro, Maren Bennewitz +1
Neuromorphic computing mimics computational principles of the brain in and motivates research into event-based vision and spiking neural networks (SNNs). Event ca…
Compact Multi-Object Placement Using Adjacency-Aware Reinforcement Learning
Benedikt Kreis, Nils Dengler, Jorge de Heuvel +3
Close and precise placement of irregularly shaped objects requires a skilled robotic system. The manipulation of objects that have sensitive top surfaces and a fixed set of neighbo…