Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Magnusson, Martin"'
Publikováno v:
2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)
The human gaze is an important cue to signal intention, attention, distraction, and the regions of interest in the immediate surroundings. Gaze tracking can transform how robots perceive, understand, and react to people, enabling new modes of robot c
Externí odkaz:
http://arxiv.org/abs/2406.06300
Autonomous driving technology is increasingly being used on public roads and in industrial settings such as mines. While it is essential to detect pedestrians, vehicles, or other obstacles, adverse field conditions negatively affect the performance o
Externí odkaz:
http://arxiv.org/abs/2404.05307
Autor:
Zhu, Yufei, Fan, Han, Rudenko, Andrey, Magnusson, Martin, Schaffernicht, Erik, Lilienthal, Achim J.
Long-term human motion prediction (LHMP) is essential for safely operating autonomous robots and vehicles in populated environments. It is fundamental for various applications, including motion planning, tracking, human-robot interaction and safety m
Externí odkaz:
http://arxiv.org/abs/2403.13640
We propose a dense RGBD SLAM system based on 3D Gaussian Splatting that provides metrically accurate pose tracking and visually realistic reconstruction. To this end, we first propose a Gaussian densification strategy based on the rendering loss to m
Externí odkaz:
http://arxiv.org/abs/2403.12535
Autor:
Schreiter, Tim, de Almeida, Tiago Rodrigues, Zhu, Yufei, Maestro, Eduardo Gutierrez, Morillo-Mendez, Lucas, Rudenko, Andrey, Palmieri, Luigi, Kucner, Tomasz P., Magnusson, Martin, Lilienthal, Achim J.
We present a new large dataset of indoor human and robot navigation and interaction, called TH\"OR-MAGNI, that is designed to facilitate research on social navigation: e.g., modelling and predicting human motion, analyzing goal-oriented interactions
Externí odkaz:
http://arxiv.org/abs/2403.09285
Neural implicit surface representations are currently receiving a lot of interest as a means to achieve high-fidelity surface reconstruction at a low memory cost, compared to traditional explicit representations.However, state-of-the-art methods stil
Externí odkaz:
http://arxiv.org/abs/2401.07164
There is a current increase in the development of "4D" Doppler-capable radar and lidar range sensors that produce 3D point clouds where all points also have information about the radial velocity relative to the sensor. 4D radars in particular are int
Externí odkaz:
http://arxiv.org/abs/2310.18117
Many practically relevant robot grasping problems feature a target object for which all grasps are occluded, e.g., by the environment. Single-shot grasp planning invariably fails in such scenarios. Instead, it is necessary to first manipulate the obj
Externí odkaz:
http://arxiv.org/abs/2310.17785
Autor:
Galeote-Luque, Andres, Kubelka, Vladimír, Magnusson, Martin, Ruiz-Sarmiento, Jose-Raul, Gonzalez-Jimenez, Javier
We present a novel 3D odometry method that recovers the full motion of a vehicle only from a Doppler-capable range sensor. It leverages the radial velocities measured from the scene, estimating the sensor's velocity from a single scan. The vehicle's
Externí odkaz:
http://arxiv.org/abs/2310.04113
RadaRays allows for the accurate modeling and simulation of rotating FMCW radar sensors in complex environments, including the simulation of reflection, refraction, and scattering of radar waves. Our software is able to handle large numbers of object
Externí odkaz:
http://arxiv.org/abs/2310.03505