The basis for most vision based applications like robotics, self-driving cars and potentially augmented and virtual reality is a robust, continuous estimation of the position and orientation of a camera system w.r.t the observed environment (scene). In recent years many vision based systems that perform simultaneous localization and mapping (SLAM) have been presented and released as open source...

In this work the Kalman filter and the Particle filter are described and their performance in the Simaltaneous Localization And Mapping (SLAM) problem in static environments is discussed. Furthermore, this paper presents how derivatives of these filters are applied in order to solve the SLAM problem in dynamic environments. The Particle filter makes less assumptions about the probability distri...

Signalling lymphocytic activation molecule (SLAM, CD150), originally identified as a lymphocyte activation molecule, is now known to be expressed also on mature dendritic cells and on activated monocytes. Importantly, SLAM is distinct from other monocyte activation markers because its expression on monocytes is readily induced in vitro by bacteria derived ligands of Toll-like receptors (TLRs), ...

Signalling lymphocytic activation molecule (SLAM, CD150), originally identified as a lymphocyte activation molecule, is now known to be expressed also on mature dendritic cells and on activated monocytes. Importantly, SLAM is distinct from other monocyte activation markers because its expression on monocytes is readily induced in vitro by bacteria derived ligands of Toll-like receptors (TLRs), ...

Real-time six degrees-of-freedom pose estimation with ground vehicles represents a relevant and well-studied topic in robotics due to its many applications such as autonomous driving 3D mapping. Although some systems already exist, they are either not accurate or struggle real-time settings. In this letter, we propose fast, modular LiDAR SLAM system for both batch online estimation. We first ap...

Abstract Current visual-based simultaneous localization and mapping(SLAM) system suffers from feature loss caused by fast motion unstructured scene in complex environments. Addressing this problem, a semi-direct SLAM algorithm is proposed paper. The main idea of method to combine the point with direct order improve robustness environment scarce visual features low texture. First, enhancement mo...

Simultaneous localization and mapping (SLAM) is one of the most essential technologies for mobile robots. Although great progress has been made in field SLAM recent years, there are a number challenges dynamic environments high-level semantic scenes. In this paper, we propose novel multimodal system (MISD-SLAM), which removes objects reconstructs static background with information. MISD-SLAM bu...

This work is motivated by robot-sensor network cooperation techniques where sensor nodes (beacons) are used as landmarks for range-only (RO) simultaneous localization and mapping (SLAM). This paper presents a RO-SLAM scheme that actuates over the measurement gathering process using mechanisms that dynamically modify the rate and variety of measurements that are integrated in the SLAM filter. It...

In this work, we focus on key topics related to underwater Simultaneous Localization and Mapping (SLAM) applications. Moreover, a detailed review of major studies in the literature and our proposed solutions for addressing the problem are presented. The main goal of this paper is the enhancement of the accuracy and robustness of the SLAM-based navigation problem for underwater robotics with low...

In this paper, we address the problem of creating an objective benchmark for comparing SLAM approaches. We propose a framework for analyzing the results of SLAM approaches based on a metric for measuring the error of the corrected trajectory. The metric uses only relative relations between poses and does not rely on a global reference frame. The idea is related to graph-based SLAM approaches, n...