9 accepted papers
Dynamic illumination is a challenging problem for visual robot localization and tracking. In indoor environments, the main source of light during the day is outdoor illumination. We propose a method that estimates the appearance of an indoor scene in real-time based on a reflectance map and the curr
Tracking the pose of a camera is at the core of visual localization methods used in many applications. As the observations of a camera are inherently affected by lighting, it has always been a challenge for these methods to cope with varying lighting conditions. Thus far, this issue has mainly been…
Indoor localization is one of the crucial enablers for deployment of service robots. Although several successful techniques for indoor localization have been proposed, the majority of them relies on maps generated from data gathered with the same sensor modality used for localization. Typically, ted…
The ability to build models of the environment is an essential prerequisite for many robotic applications. In recent years, mapping of dense surface geometry using RGB-D cameras has seen extensive progress. Many approaches build colored models, typically directly using the intensity values provided…
Robust data association is necessary for virtually every SLAM system and finding corresponding points is typically a preprocessing step for scan alignment algorithms. Traditionally, handcrafted feature descriptors were used for these problems but recently learned descriptors have been shown to perfo…
Modern automation demands mobile robots to be robustly localized in complex scenarios. Current localization systems typically use maps that require to be built and interpreted by experienced operators, increasing deployment costs as well as reducing the adaptability of robots to rearrangements in th…
Localizing a camera in a given map is essential for vision-based navigation. In contrast to common methods for visual localization that use maps acquired with cameras, we propose a novel approach, which tracks the pose of monocular camera with respect to a given 3D LiDAR map. We employ a visual odom…
Robots are expected to operate autonomously in increasingly complex scenarios such as crowded streets or heavy traffic situations. Perceiving the dynamics of moving objects in the environment is crucial for safe and smart navigation and therefore a key enabler for autonomous driving. In this paper w
The perception of the dynamic aspects of the environment is a highly relevant precondition for the realization of autonomous robot system acting in the real world. In this paper, we propose a novel method for estimating dense rigid scene flow in 3D LiDAR scans. We formulate the problem as an energy…