The genetic defect in X-linked lymphoproliferative syndrome (XLP) is the Src homology 2 domain-containing protein SAP. SAP constitutively associates with the cell surface molecule, signaling lymphocytic activation molecule (SLAM), and competes with SH2-domain containing protein tyrosine phosphatase-2 (SHP-2) for recruitment to SLAM. SLAM exhibits homology with the mouse cell surface receptor 2B...

We investigate simultaneous localization and mapping (SLAM) involving multiple robots through collaborations. In particular, we assume that robots may communicate to each other when in communication range. Several scenarios are considered: (i) robots fully able to communicate while conducting SLAM; (ii) robot communications are intermittent due to each robot having a limited but equal communica...

One fundamental problem in mobile robotics research is Simultaneous Localization and Mapping (SLAM): A mobile robot has to localize itself in an unknown environment, and at the same time generate a map of the surrounding area. One fundamental part of SLAM algorithms is loop closing: The robot detects whether it has reached an area that has been visited before, and uses this information to impro...

Robotic mapping is an enabling technology for the navigation of autonomous vehicles. The problem of estimating both a vehicle’s state and a map of its environment is referred to as Simultaneous Localization and Mapping (SLAM). This paper presents a SLAM framework suitable of a Micro Air Vehicle (MAV) equipped only with a monocular camera. Structure from Motion (SFM) is employed to infer three-d...

9 This work presents real time implementation algorithms of simultaneous localization and map building (SLAM) with emphasis to outdoor land vehicle applications in large environments. It presents the problematic of outdoors navigation in areas with combination of feature and featureless regions. The aspect of feature detection and validation is investigated to reliably detect the predominant fe...

Cloud Robotics is one of the emerging area of robotics. It has created a lot of attention due to its direct practical implications on Robotics. In Cloud Robotics, the concept of cloud computing is used to offload computational extensive jobs of the robots to the cloud. Apart from this, additional functionalities can also be offered on run to the robots on demand. Simultaneous Localization and M...

Local Bundle Adjustments were recently introduced for visual SLAM (Simultaneous Localization and Mapping). In Monocular Visual SLAM, the scale factor is not observable and the reconstruction scale drifts as time goes by. On long trajectory, this problem makes absolute localisation not usable. To overcome this major problem, data fusion is a possible solution. In this paper, we describe Weighted...

To navigate successfully, a mobile robot must be able to estimate the spatial relationships of the objects of interest accurately. A SLAM (Simultaneous Localization and Mapping) system employs its sensor data to build incrementally a map of an unknown environment and to localize itself in the map simultaneously. Thanks to recent advances in computer vision and cheaper cameras, vision sensors ha...

Simultaneous localization and mapping (SLAM) is a fundamental problem in robotics. It is the process of creating a map of the environment while, at the same time, estimating the position and attitude of the robot relative to the map. SLAM enables autonomous path planning and control. The extended Kalman Filter (EKF), Particle Filters, and Expectation Minimization are among the most popular SLAM...

Mobile robots are widely used in medicine, agriculture, home furnishing, and industry. Simultaneous localization mapping (SLAM) is the working basis of mobile robots, so it extremely necessary meaningful for making researches on SLAM technology. technology involves robot mechanism kinematics, logic, mathematics, perceptual detection, other fields. However, faces problem classifying technical co...