16 citations · 23 across the 27 of their papers we have counts for
28 papers
Benchmarking Robots for Everyday Environments: From Lab Experiments to Real-World Operations
Raphael Memmesheimer, Martina Overbeck, Dominik Beyer +20
This study presents an interdisciplinary process for benchmarking service robots in public everyday environments, addressing the gap between laboratory metrics and real-world opera…
Sample, Simulate, Select: Physics-in-the-Loop Text-to-Motion for Humanoids Without Training
Raphael Memmesheimer, Sven Behnke
Text-to-motion models generate plausible human motion but do not model a robot's dynamics; whole-body tracking controllers execute robot references reliably but cannot replan an in…
Efficient Image Annotation via Semi-Supervised Object Segmentation with Label Propagation
Vitalii Tutevych, Raphael Memmesheimer, Luca Eichler +4
Reliable object perception is necessary for general-purpose service robots. Open-vocabulary detectors struggle to generalize beyond a few classes and fully supervised training of o…
OMCL: Open-vocabulary Monte Carlo Localization
Evgenii Kruzhkov, Raphael Memmesheimer, Sven Behnke
Robust robot localization is an important prerequisite for navigation, but it becomes challenging when the map and robot measurements are obtained from different sensors. Prior met…
EL3DD: Extended Latent 3D Diffusion for Language Conditioned Multitask Manipulation
Jonas Bode, Raphael Memmesheimer, Sven Behnke
Acting in human environments is a crucial capability for general-purpose robots, necessitating a robust understanding of natural language and its application to physical tasks. Thi…
Integration of the TIAGo Robot into Isaac Sim with Mecanum Drive Modeling and Learned S-Curve Velocity Profiles
Vincent Schoenbach, Marvin Wiedemann, Raphael Memmesheimer +2
Efficient physics simulation has significantly accelerated research progress in robotics applications such as grasping and assembly. The advent of GPU-accelerated simulation framew…
LIAM: Multimodal Transformer for Language Instructions, Images, Actions and Semantic Maps
Yihao Wang, Raphael Memmesheimer, Sven Behnke
The availability of large language models and open-vocabulary object perception methods enables more flexibility for domestic service robots. The large variability of domestic task…
RoboCup@Home 2024 OPL Winner NimbRo: Anthropomorphic Service Robots using Foundation Models for Perception and Planning
Raphael Memmesheimer, Jan Nogga, Bastian Pätzold +8
We present the approaches and contributions of the winning team NimbRo@Home at the RoboCup@Home 2024 competition in the Open Platform League held in Eindhoven, NL. Further, we desc…
Person Segmentation and Action Classification for Multi-Channel Hemisphere Field of View LiDAR Sensors
Svetlana Seliunina, Artem Otelepko, Raphael Memmesheimer +1
Robots need to perceive persons in their surroundings for safety and to interact with them. In this paper, we present a person segmentation and action classification approach that…
A Comparison of Prompt Engineering Techniques for Task Planning and Execution in Service Robotics
Jonas Bode, Bastian Pätzold, Raphael Memmesheimer +1
Recent advances in LLM have been instrumental in autonomous robot control and human-robot interaction by leveraging their vast general knowledge and capabilities to understand and…
Anticipating Human Behavior for Safe Navigation and Efficient Collaborative Manipulation with Mobile Service Robots
Simon Bultmann, Raphael Memmesheimer, Jan Nogga +2
The anticipation of human behavior is a crucial capability for robots to interact with humans safely and efficiently. We employ a smart edge sensor network to provide global observ…
Self-Centering 3-DoF Feet Controller for Hands-Free Locomotion Control in Telepresence and Virtual Reality
Raphael Memmesheimer, Christian Lenz, Max Schwarz +2
We present a novel seated feet controller for handling 3-DoF aimed to control locomotion for telepresence robotics and virtual reality environments. Tilting the feet on two axes yi…
Cleaning Robots in Public Spaces: A Survey and Proposal for Benchmarking Based on Stakeholders Interviews
Raphael Memmesheimer, Martina Overbeck, Bjoern Kral +4
Autonomous cleaning robots for public spaces have potential for addressing current societal challenges, such as labor shortages and cleanliness in public spaces. Other application…
NimbRo wins ANA Avatar XPRIZE Immersive Telepresence Competition: Human-Centric Evaluation and Lessons Learned
Christian Lenz, Max Schwarz, Andre Rochow +4
Robotic avatar systems can enable immersive telepresence with locomotion, manipulation, and communication capabilities. We present such an avatar system, based on the key component…
External Camera-based Mobile Robot Pose Estimation for Collaborative Perception with Smart Edge Sensors
Simon Bultmann, Raphael Memmesheimer, Sven Behnke
We present an approach for estimating a mobile robot's pose w.r.t. the allocentric coordinates of a network of static cameras using multi-view RGB images. The images are processed…
Audio-based Roughness Sensing and Tactile Feedback for Haptic Perception in Telepresence
Bastian Pätzold, Andre Rochow, Michael Schreiber +4
Haptic perception is highly important for immersive teleoperation of robots, especially for accomplishing manipulation tasks. We propose a low-cost haptic sensing and rendering sys…
Robust Immersive Telepresence and Mobile Telemanipulation: NimbRo wins ANA Avatar XPRIZE Finals
Max Schwarz, Christian Lenz, Raphael Memmesheimer +4
Robotic avatar systems promise to bridge distances and reduce the need for travel. We present the updated NimbRo avatar system, winner of the $5M grand prize at the international A…
RoboCup 2022 AdultSize Winner NimbRo: Upgraded Perception, Capture Steps Gait and Phase-based In-walk Kicks
Dmytro Pavlichenko, Grzegorz Ficht, Arash Amini +7
Beating the human world champions by 2050 is an ambitious goal of the Humanoid League that provides a strong incentive for RoboCup teams to further improve and develop their system…
Next-Best-View Estimation based on Deep Reinforcement Learning for Active Object Classification
Christian Korbach, Markus D. Solbach, Raphael Memmesheimer +2
The presentation and analysis of image data from a single viewpoint are often not sufficient to solve a task. Several viewpoints are necessary to obtain more information. The next-…
Fusion-GCN: Multimodal Action Recognition using Graph Convolutional Networks
Michael Duhme, Raphael Memmesheimer, Dietrich Paulus
In this paper, we present Fusion-GCN, an approach for multimodal action recognition using Graph Convolutional Networks (GCNs). Action recognition methods based around GCNs recently…
Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action Recognition
Raphael Memmesheimer, Simon Häring, Nick Theisen +1
One-shot action recognition allows the recognition of human-performed actions with only a single training example. This can influence human-robot-interaction positively by enabling…
Gimme Signals: Discriminative signal encoding for multimodal activity recognition
Raphael Memmesheimer, Nick Theisen, Dietrich Paulus
We present a simple, yet effective and flexible method for action recognition supporting multiple sensor modalities. Multivariate signal sequences are encoded in an image and are t…
SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition
Raphael Memmesheimer, Nick Theisen, Dietrich Paulus
Recognizing an activity with a single reference sample using metric learning approaches is a promising research field. The majority of few-shot methods focus on object recognition…
Gesture Recognition in RGB Videos UsingHuman Body Keypoints and Dynamic Time Warping
Pascal Schneider, Raphael Memmesheimer, Ivanna Kramer +1
Gesture recognition opens up new ways for humans to intuitively interact with machines. Especially for service robots, gestures can be a valuable addition to the means of communica…