The Characteristics of the Map Merging Methods: A Survey <s> VI. CONCLUSIONS <s> This paper describes a landmark-based algorithm for map matching, and demonstrates its use in efficiently combining topological maps of indoor environments built by autonomous mobile robots. Results of the first implementation are presented, in which two robots with different mechanics and sensory capabilities independently explore their environments with no a priori maps. Each robot is initially unaware of the other’s relative position and orientation. Using the match algorithm, they eventually merge their maps into a topologically correct single map in real time, based only on the feature sets they have discovered independently. <s> BIB001 </s> The Characteristics of the Map Merging Methods: A Survey <s> VI. CONCLUSIONS <s> This paper presents a novel approach to the multi-vehicle simultaneous localisation and mapping (SLAM) problem that exploits the manner in which observations are fused into the global map of the environment to manage the computational complexity of the algorithm and improve the data association process. Rather than incorporating every observation directly into the global map of the environment, the constrained local submap filter (CLSF) relies on creating an independent, local submap of the features in the immediate vicinity of the vehicle. This local submap is then periodically fused into the global map of the environment. This representation is shown to reduce the computational complexity of maintaining the global map estimates as well as improving the data association process. This paper examines the prospect of applying the CLSF algorithm to the multi-vehicle SLAM problem. <s> BIB002 </s> The Characteristics of the Map Merging Methods: A Survey <s> VI. CONCLUSIONS <s> We address the problem of merging multiple noisy maps in the rescue environment. The problem is tackled by performing a stochastic search in the space of possible map transformations, i.e. rotations and translations. The proposed technique, which performs a time variant Gaussian random walk, turns out to be a generalization of other search techniques like hill-climbing or simulated annealing. Numerical examples of its performance while merging partial maps built by our rescue robots are provided. <s> BIB003 </s> The Characteristics of the Map Merging Methods: A Survey <s> VI. CONCLUSIONS <s> The purpose of this paper is to present a technique to create a global map of robots' surroundings by converting the raw data acquired from a scanning sensor to a compact map composed of just a few generalized polylines (polygonal curves). We propose a new approach to merging robots' maps that is composed of a local geometric process of merging similar line segments (termed discrete segment evolution) with a global statistical control process. In the case of single robot, we are able to incrementally build a map showing the environment the robot has traveled through by merging its polygonal map with actual scans. In the case of a robot team, we are able to identify common parts of their partial maps and if common parts are present construct a joint map of the explored environment. <s> BIB004 </s> The Characteristics of the Map Merging Methods: A Survey <s> VI. CONCLUSIONS <s> Mapping can potentially be speeded up in a significant way by using multiple robots exploring different parts of the environment. But the core question of multirobot mapping is how to integrate the data of the different robots into a single global map. A significant amount of research exists in the area of multirobot mapping that deals with techniques to estimate the relative robots poses at the start or during the mapping process. With map merging, the robots in contrast individually build local maps without any knowledge about their relative positions. The goal is then to identify regions of overlap at which the local maps can be joined together. A concrete approach to this idea is presented in form of a special similarity metric and a stochastic search algorithm. Given two maps m and m', the search algorithm transforms m' by rotations and translations to find a maximum overlap between m and m'. In doing so, the heuristic similarity metric guides the search algorithm toward optimal solutions. Results from experiments with up to six robots are presented based on simulated as well as real-world map data <s> BIB005 </s> The Characteristics of the Map Merging Methods: A Survey <s> VI. CONCLUSIONS <s> Merging local maps, acquired by multiple robots, into a global map, (also known as map merging) is one of the important issues faced by virtually all cooperative exploration techniques. We present a novel and simple solution to the problem of map merging by reducing it to the problem of SLAM of a single ?virtual? robot. The individual local maps and their shape information constitute the sensor information for the virtual robot. This approach allows us to adapt the framework of Rao-Blackwellized particle filtering used in SLAM of a single robot for the problem of map merging. <s> BIB006
In this paper different map merging approaches were surveyed and the state of the art in the field of map merging was described. Multiple map merging characteristics were identified during the survey and the interrelations of these characteristics were acquired. The characteristics that could be used for the classification of the map merging methods include the reference frames, the type of the maps, the map merging decision, the structure of the environment, the enabler of the map merging, and the duration of the map merging. Some of these characteristics, i.e. reference frames, map type, map merging decision, have been used previously for the classification of the map merging approaches, whereas the other characteristics haven't been taken into account. All the characteristics and their interrelations were summarized in one table and the table was supplemented with the corresponding map merging methods for each set of characteristics. A remarkable relationship is observable between the reference frame characteristic and the corresponding map merging approaches. While the metric maps are more often used for the map merging when the relative reference frames are known or determined during the mapping, the topological and feature maps dominate the area of the map merging when the relative reference frames of the maps are unknown. Even if metric maps are used they are often augmented with features before the actual merging. Thus, the feature extraction is currently the dominant paradigm in the metric map merging when the relative positions of the robots are unknown. The work started in this paper can be continued by analyzing other characteristics that are currently mostly ignored in the field of map merging, i.e. the merging of heterogeneous maps, or the merging of differently scaled maps. The "perfect" map merging approach could be defined and compared with the existing map merging approaches. Thus, the main drawbacks of the existing map merging approaches could be easier detected and dealt with.  , BIB005 , BIB006 , BIB003 ,  Topological or Feature Unverified or Verifiable Heuristics Online Structured  -  , BIB001 , BIB004 , BIB002 роботами до сих пор имеются некоторые неокончательно решённые проблемы. Использование группы роботов для составления карт решает некоторые из этих проблем, но в этом случае возникают новые проблемы, специфичные для составления карт несколькими роботами. Одна из таких проблем -это объединение всех локальных карт, созданных группой роботов, в одну глобальную карту. Применение групп роботов в исследовании пространства и составлении карт является относительно новой отраслью исследований; вначале методы составления карт многими роботами просто были расширением методов составления карт одним роботом. В связи с этим проблема объединения карт была упрощена. Исследования в области объединения карт начали развиваться относительно недавно, и поэтому имеющиеся публикации об объединении карт описывают только специфичные методы объединения карт, и не существует разносторонних обзоров об общем состоянии в отрасли объединения карт. Поэтому целью данной статьи является описать существующую ситуацию в области объединения карт и выделить главные характерные особенности методов объединения карт. После определения характерных особенностей становится возможным определить их взаимосвязи, а также для каждой группы таких взаимосвязей определить соответствующие методы объединения карт.