Graph-based Simultaneous Localization and Mapping (SLAM) has experienced a recent surge towards robust methods. These methods take the combinatorial aspect of data association into account by allowing decisions of the graph topology to be made during optimization. In this paper, the Generalized Graph SLAM framework for SLAM under ambiguous data association is presented, and a formal description...

Real-time simultaneously localization and dense mapping is very helpful for providing Virtual Reality and Augmented Reality for surgeons or even surgical robots. In this paper, we propose MIS-SLAM: a complete real-time large scale dense deformable SLAM system with stereoscope in Minimal Invasive Surgery based on heterogeneous computing by making full use of CPU and GPU. Idled CPU is used to per...

The main focus of this paper is to present a case study of a SLAM solution for Automated Guided Vehicles (AGVs) operating in real-world industrial environments. The studied solution, called Gold-fish SLAM, was implemented to provide localization estimates in dynamic industrial environments, where there are static landmarks that are only rarely perceived by the AGVs. The main idea of Gold-fish S...

In this paper, we propose techniques which make SLAM accurate and practical in dynamic outdoor environment. In order to achieve the objective, stable feature detection by a laser range finder and efficient data management are introduced. The stable feature detection is used to select static and characteristic landmarks, it is possible to estimate every position of landmark accurately in the dyn...

In this paper we point out an overlooked structure of SLAM that distinguishes it from a generic nonlinear least squares problem. The measurement function in most common forms of SLAM is linear with respect to robot and features’ positions. Therefore, given an estimate for robot orientation, the conditionally optimal estimate for the rest of state variables can be easily obtained by solving a sp...

Signalling lymphocyte activation molecule (SLAM) acts as a cellular receptor for Measles virus (MV). The recombinant MV, based on a SLAM-using clinical isolate in which asparagine at position 481 of the haemagglutinin was replaced with tyrosine, was generated. Characterization of this recombinant virus revealed that the N481Y substitution in the haemagglutinin allowed it to utilize CD46 as an a...

Self-localization during navigation with noisy sensors in an ambiguous world is computationally challenging, yet animals and humans excel at it. In robotics, Simultaneous Location and Mapping (SLAM) algorithms solve this problem though joint sequential probabilistic inference of their own coordinates and those of external spatial landmarks. We generate the first neural solution to the SLAM prob...

In robotics, the key requirement for achieving autonomy is to provide robots with the ability to accurately map an environment and simultaneously localize themselves within that environment. This problem is referred to as Simultaneous Localization and Mapping (SLAM). In this research, a decentralized platform for SLAM with multiple robots has been developed. Single-robot SLAM is achieved throug...

Paul Michael Newman Doctor of Philosophy The University of Sydney March 1999 On the Structure and Solution of the Simultaneous Localisation and Map Building Problem This thesis is concerned with the simultaneous localisation and map building (SLAM) problem. The SLAM problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to inc...

In this paper, we deduce general observability condition of all types of SLAM solutions regardless what states they consider directly in estimation, i.e. whether SLAM is feature based or pose (graph) based. This result comes from doing nonlinear observability analysis of the pose-based SLAM. We consider general vehicle motion model whose control inputs are translational and rotational velocity ...