194 citations · 1.5k across the 123 of their papers we have counts for
29 papers · 1 filter
Flexible-Joint Manipulator Trajectory Tracking with Learned Two-Stage Model employing One-Step Future Prediction
Dmytro Pavlichenko, Sven Behnke
Flexible-joint manipulators are frequently used for increased safety during human-robot collaboration and shared workspace tasks. However, joint flexibility significantly reduces t…
Semantic Interaction in Augmented Reality Environments for Microsoft HoloLens
Peer Schüett, Max Schwarz, Sven Behnke
Augmented Reality is a promising technique for human-machine interaction. Especially in robotics, which always considers systems in their environment, it is highly beneficial to di…
Fourier-based Video Prediction through Relational Object Motion
Malte Mosbach, Sven Behnke
The ability to predict future outcomes conditioned on observed video frames is crucial for intelligent decision-making in autonomous systems. Recently, deep recurrent architectures…
Semantic Prediction: Which One Should Come First, Recognition or Prediction?
Hafez Farazi, Jan Nogga, and Sven Behnke
The ultimate goal of video prediction is not forecasting future pixel-values given some previous frames. Rather, the end goal of video prediction is to discover valuable internal r…
Unsupervised Image Decomposition with Phase-Correlation Networks
Angel Villar-Corrales, Sven Behnke
The ability to decompose scenes into their object components is a desired property for autonomous agents, allowing them to reason and act in their surroundings. Recently, different…
NimbRo Avatar: Interactive Immersive Telepresence with Force-Feedback Telemanipulation
Max Schwarz, Christian Lenz, Andre Rochow +2
Robotic avatars promise immersive teleoperation with human-like manipulation and communication capabilities. We present such an avatar system, based on the key components of immers…
Bimanual Telemanipulation with Force and Haptic Feedback and Predictive Limit Avoidance
Christian Lenz, Sven Behnke
Robotic teleoperation is a key technology for a wide variety of applications. It allows sending robots instead of humans in remote, possibly dangerous locations while still using t…
Low-Latency Immersive 6D Televisualization with Spherical Rendering
Max Schwarz, Sven Behnke
We present a method for real-time stereo scene capture and remote VR visualization that allows a human operator to freely move their head and thus intuitively control their perspec…
T6D-Direct: Transformers for Multi-Object 6D Pose Direct Regression
Arash Amini, Arul Selvam Periyasamy, Sven Behnke
6D pose estimation is the task of predicting the translation and orientation of objects in a given input image, which is a crucial prerequisite for many robotics and augmented real…
Rendering and Tracking the Directional TSDF: Modeling Surface Orientation for Coherent Maps
Malte Splietker, Sven Behnke
Dense real-time tracking and mapping from RGB-D images is an important tool for many robotic applications, such as navigation or grasping. The recently presented Directional Trunca…
Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles
Simon Bultmann, Jan Quenzel, Sven Behnke
Unmanned aerial vehicles (UAVs) equipped with multiple complementary sensors have tremendous potential for fast autonomous or remote-controlled semantic scene analysis, e.g., for d…
LatticeNet: Fast Spatio-Temporal Point Cloud Segmentation Using Permutohedral Lattices
Radu Alexandru Rosu, Peer Schütt, Jan Quenzel +1
Deep convolutional neural networks (CNNs) have shown outstanding performance in the task of semantically segmenting images. Applying the same methods on 3D data still poses challen…
Mapless Humanoid Navigation Using Learned Latent Dynamics
Andre Brandenburger, Diego Rodriguez, Sven Behnke
In this paper, we propose a novel Deep Reinforcement Learning approach to address the mapless navigation problem, in which the locomotion actions of a humanoid robot are taken onli…
NeuralMVS: Bridging Multi-View Stereo and Novel View Synthesis
Radu Alexandru Rosu, Sven Behnke
Multi-View Stereo (MVS) is a core task in 3D computer vision. With the surge of novel deep learning methods, learned MVS has surpassed the accuracy of classical approaches, but sti…
6D Object Pose Estimation using Keypoints and Part Affinity Fields
Moritz Zappel, Simon Bultmann, Sven Behnke
The task of 6D object pose estimation from RGB images is an important requirement for autonomous service robots to be able to interact with the real world. In this work, we present…
SynPick: A Dataset for Dynamic Bin Picking Scene Understanding
Arul Selvam Periyasamy, Max Schwarz, Sven Behnke
We present SynPick, a synthetic dataset for dynamic scene understanding in bin-picking scenarios. In contrast to existing datasets, our dataset is both situated in a realistic indu…
Real-time Pose Estimation from Images for Multiple Humanoid Robots
Arash Amini, Hafez Farazi, Sven Behnke
Pose estimation commonly refers to computer vision methods that recognize people's body postures in images or videos. With recent advancements in deep learning, we now have compell…
Real-Time Multi-View 3D Human Pose Estimation using Semantic Feedback to Smart Edge Sensors
Simon Bultmann, Sven Behnke
We present a novel method for estimation of 3D human poses from a multi-camera setup, employing distributed smart edge sensors coupled with a backend through a semantic feedback lo…
Autonomous Fire Fighting with a UAV-UGV Team at MBZIRC 2020
Jan Quenzel, Malte Splietker, Dmytro Pavlichenko +6
Every day, burning buildings threaten the lives of occupants and first responders trying to save them. Quick action is of essence, but some areas might not be accessible or too dan…
FaDIV-Syn: Fast Depth-Independent View Synthesis using Soft Masks and Implicit Blending
Andre Rochow, Max Schwarz, Michael Weinmann +1
Novel view synthesis is required in many robotic applications, such as VR teleoperation and scene reconstruction. Existing methods are often too slow for these contexts, cannot han…
DeepWalk: Omnidirectional Bipedal Gait by Deep Reinforcement Learning
Diego Rodriguez, Sven Behnke
Bipedal walking is one of the most difficult but exciting challenges in robotics. The difficulties arise from the complexity of high-dimensional dynamics, sensing and actuation lim…
Team NimbRo's UGV Solution for Autonomous Wall Building and Fire Fighting at MBZIRC 2020
Christian Lenz, Jan Quenzel, Arul Selvam Periyasamy +7
Autonomous robotic systems for various applications including transport, mobile manipulation, and disaster response are becoming more and more complex. Evaluating and analyzing suc…
Empirical Error Modeling Improves Robustness of Noisy Neural Sequence Labeling
Marcin Namysl, Sven Behnke, Joachim Köhler
Despite recent advances, standard sequence labeling systems often fail when processing noisy user-generated text or consuming the output of an Optical Character Recognition (OCR) p…
Local Frequency Domain Transformer Networks for Video Prediction
Hafez Farazi, Jan Nogga, Sven Behnke
Video prediction is commonly referred to as forecasting future frames of a video sequence provided several past frames thereof. It remains a challenging domain as visual scenes evo…