16 citations · 21 across the 23 of their papers we have counts for
25 papers
Do My Samples Help? Compute Budget Allocation for Real-World Sampling-Based MPC in Contact-Rich Manipulation
Magnus Dierking, João Carvalho, Vince Kurtz +3
Sampling-based model predictive control (SMPC) is increasingly practical for contact-rich manipulation because GPU-based physics simulators enable real-time evaluation of large num…
PolyUMI: Accessible Visual-Tactile-Audio Data Collection for Object Inference and Manipulation
Conor W. Hayes, Rickmer Krohn, Aravind Ramaswami +6
Humans typically rely on vision, touch, hearing, and proprioception to perceive contact and adapt their actions during manipulation. Providing robots with comparable responsiveness…
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…
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…
Efficient Trajectory Optimization for Autonomous Racing via Formula-1 Data-Driven Initialization
Samir Shehadeh, Lukas Kutsch, Nils Dengler +2
Trajectory optimization is a central component of fast and efficient autonomous racing. However practical optimization pipelines remain highly sensitive to initialization and may c…
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…
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…
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…
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…
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…
Learning Goal-Directed Object Pushing in Cluttered Scenes With Location-Based Attention
Nils Dengler, Juan Del Aguila Ferrandis, João Moura +2
In complex scenarios where typical pick-and-place techniques are insufficient, often non-prehensile manipulation can ensure that a robot is able to fulfill its task. However, non-p…
RHINO-VR Experience: Teaching Mobile Robotics Concepts in an Interactive Museum Exhibit
Erik Schlachhoff, Nils Dengler, Leif Van Holland +4
In 1997, the very first tour guide robot RHINO was deployed in a museum in Germany. With the ability to navigate autonomously through the environment, the robot gave tours to over…
Safe Multi-Agent Reinforcement Learning for Behavior-Based Cooperative Navigation
Murad Dawood, Sicong Pan, Nils Dengler +3
In this paper, we address the problem of behavior-based cooperative navigation of mobile robots using safe multi-agent reinforcement learning~(MARL). Our work is the first to focus…
DawnIK: Decentralized Collision-Aware Inverse Kinematics Solver for Heterogeneous Multi-Arm Systems
Salih Marangoz, Rohit Menon, Nils Dengler +1
Although inverse kinematics of serial manipulators is a well studied problem, challenges still exist in finding smooth feasible solutions that are also collision aware. Furthermore…
Integrating One-Shot View Planning with a Single Next-Best View via Long-Tail Multiview Sampling
Sicong Pan, Hao Hu, Hui Wei +4
Existing view planning systems either adopt an iterative paradigm using next-best views (NBV) or a one-shot pipeline relying on the set-covering view-planning (SCVP) network. Howev…
Viewpoint Push Planning for Mapping of Unknown Confined Spaces
Nils Dengler, Sicong Pan, Vamsi Kalagaturu +3
Viewpoint planning is an important task in any application where objects or scenes need to be viewed from different angles to achieve sufficient coverage. The mapping of confined s…
Handling Sparse Rewards in Reinforcement Learning Using Model Predictive Control
Murad Dawood, Nils Dengler, Jorge de Heuvel +1
Reinforcement learning (RL) has recently proven great success in various domains. Yet, the design of the reward function requires detailed domain expertise and tedious fine-tuning…
NBV-SC: Next Best View Planning based on Shape Completion for Fruit Mapping and Reconstruction
Rohit Menon, Tobias Zaenker, Nils Dengler +1
Active perception for fruit mapping and harvesting is a difficult task since occlusions occur frequently and the location as well as size of fruits change over time. State-of-the-a…
Learning Goal-Oriented Non-Prehensile Pushing in Cluttered Scenes
Nils Dengler, David Großklaus, Maren Bennewitz
Pushing objects through cluttered scenes is a challenging task, especially when the objects to be pushed have initially unknown dynamics and touching other entities has to be avoid…
Sensor-Based Navigation Using Hierarchical Reinforcement Learning
Christopher Gebauer, Nils Dengler, Maren Bennewitz
Robotic systems are nowadays capable of solving complex navigation tasks. However, their capabilities are limited to the knowledge of the designer and consequently lack generalizab…