Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Bultmann, Simon"'
The human gait is a complex interplay between the neuronal and the muscular systems, reflecting an individual's neurological and physiological condition. This makes gait analysis a valuable tool for biomechanics and medical experts. Traditional obser
Externí odkaz:
http://arxiv.org/abs/2411.09538
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 observations along with future predictions and goal information to integrate
Externí odkaz:
http://arxiv.org/abs/2410.05015
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 online, locally on smart edge sensors by deep neural networks to detec
Externí odkaz:
http://arxiv.org/abs/2303.03797
Autonomous robots that interact with their environment require a detailed semantic scene model. For this, volumetric semantic maps are frequently used. The scene understanding can further be improved by including object-level information in the map.
Externí odkaz:
http://arxiv.org/abs/2211.11354
Unmanned aerial vehicles (UAVs) equipped with multiple complementary sensors have tremendous potential for fast autonomous or remote-controlled semantic scene analysis, e.g., for disaster examination. Here, we propose a UAV system for real-time seman
Externí odkaz:
http://arxiv.org/abs/2210.09739
Calibration of multi-camera systems, i.e. determining the relative poses between the cameras, is a prerequisite for many tasks in computer vision and robotics. Camera calibration is typically achieved using offline methods that use checkerboard calib
Externí odkaz:
http://arxiv.org/abs/2209.07393
Autor:
Bultmann, Simon, Behnke, Sven
We present a system for 3D semantic scene perception consisting of a network of distributed smart edge sensors. The sensor nodes are based on an embedded CNN inference accelerator and RGB-D and thermal cameras. Efficient vision CNN models for object
Externí odkaz:
http://arxiv.org/abs/2205.01460
Autor:
Beul, Marius, Schwarz, Max, Quenzel, Jan, Splietker, Malte, Bultmann, Simon, Schleich, Daniel, Rochow, Andre, Pavlichenko, Dmytro, Rosu, Radu Alexandru, Lowin, Patrick, Scheider, Bruno, Schreiber, Michael, Süberkrüb, Finn, Behnke, Sven
The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020 posed diverse challenges for unmanned aerial vehicles (UAVs). We present our four tailored UAVs, specifically developed for individual aerial-robot tasks of MBZIRC, including custom
Externí odkaz:
http://arxiv.org/abs/2201.03844
Unmanned aerial vehicles (UAVs) equipped with multiple complementary sensors have tremendous potential for fast autonomous or remote-controlled semantic scene analysis, e.g., for disaster examination. In this work, we propose a UAV system for real-ti
Externí odkaz:
http://arxiv.org/abs/2108.06608
Publikováno v:
Proceedings of 24th RoboCup International Symposium, June 2021
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 a two-step pipeline for estimating the 6 DoF translation and orientat
Externí odkaz:
http://arxiv.org/abs/2107.02057