2 citations · 4 across the 35 of their papers we have counts for
14 papers · 1 filter
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…
Sound Matters: Auditory Detectability of Mobile Robots
Subham Agrawal, Marlene Wessels, Jorge de Heuvel +2
Mobile robots are increasingly being used in noisy environments for social purposes, e.g. to provide support in healthcare or public spaces. Since these robots also operate beyond…
Demonstration-Enhanced Adaptable Multi-Objective Robot Navigation
Jorge de Heuvel, Tharun Sethuraman, Maren Bennewitz
Preference-aligned robot navigation in human environments is typically achieved through learning-based approaches, utilizing user feedback or demonstrations for personalization. Ho…
EnQuery: Ensemble Policies for Diverse Query-Generation in Preference Alignment of Robot Navigation
Jorge de Heuvel, Florian Seiler, Maren Bennewitz
To align mobile robot navigation policies with user preferences through reinforcement learning from human feedback (RLHF), reliable and behavior-diverse user queries are required.…
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…
Exploiting Priors from 3D Diffusion Models for RGB-Based One-Shot View Planning
Sicong Pan, Liren Jin, Xuying Huang +3
Object reconstruction is relevant for many autonomous robotic tasks that require interaction with the environment. A key challenge in such scenarios is planning view configurations…
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…
Centroidal State Estimation based on the Koopman Embedding for Dynamic Legged Locomotion
Shahram Khorshidi, Murad Dawood, Maren Bennewitz
In this paper, we introduce a novel approach to centroidal state estimation, which plays a crucial role in predictive model-based control strategies for dynamic legged locomotion.…