Topological Map Building with Multiple Agents Having Abilities of Dropping Indexed Markers

2021 ◽  
Vol 103 (1) ◽  
Author(s):  
Jonghoek Kim
Keyword(s):  
Map Building ◽  
Multiple Agents ◽  
Topological Map

scholarly journals Topological Frontier-Based Exploration and Map-Building Using Semantic Information

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4595 ◽  
Author(s):  
Clara Gomez ◽  
Alejandra C. Hernandez ◽  
Ramon Barber
Keyword(s):  
Open Space ◽  
Semantic Information ◽  
State Of The Art ◽  
Fundamental Problem ◽  
Cost Utility ◽  
Indoor Environments ◽  
Map Building ◽  
Topological Map ◽  
Unknown Area ◽  
Closure Algorithm

Exploration of unknown environments is a fundamental problem in autonomous robotics that deals with the complexity of autonomously traversing an unknown area while acquiring the most important information of the environment. In this work, a mobile robot exploration algorithm for indoor environments is proposed. It combines frontier-based concepts with behavior-based strategies in order to build a topological representation of the environment. Frontier-based approaches assume that, to gain the most information of an environment, the robot has to move to the regions on the boundary between open space and unexplored space. The novelty of this work is in the semantic frontier classification and frontier selection according to a cost–utility function. In addition, a probabilistic loop closure algorithm is proposed to solve cyclic situations. The system outputs a topological map of the free areas of the environment for further navigation. Finally, simulated and real-world experiments have been carried out, their results and the comparison to other state-of-the-art algorithms show the feasibility of the exploration algorithm proposed and the improvement that it offers with regards to execution time and travelled distance.

scholarly journals Global Appearance Applied to Visual Map Building and Path Estimation Using Multiscale Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-23 ◽  
Author(s):  
Francisco Amorós ◽  
Luis Payá ◽  
Oscar Reinoso ◽  
Walterio Mayol-Cuevas ◽  
Andrew Calway
Keyword(s):  
Pose Estimation ◽  
Visual Information ◽  
Multiscale Analysis ◽  
Spatial Arrangement ◽  
Field Of View ◽  
Indoor Environments ◽  
Map Building ◽  
Topological Map ◽  
Complete Field ◽  
Estimation System

In this work we present a topological map building and localization system for mobile robots based on global appearance of visual information. We include a comparison and analysis of global-appearance techniques applied to wide-angle scenes in retrieval tasks. Next, we define multiscale analysis, which permits improving the association between images and extracting topological distances. Then, a topological map-building algorithm is proposed. At first, the algorithm has information only of some isolated positions of the navigation area in the form of nodes. Each node is composed of a collection of images that covers the complete field of view from a certain position. The algorithm solves the node retrieval and estimates their spatial arrangement. With these aims, it uses the visual information captured along some routes that cover the navigation area. As a result, the algorithm builds a graph that reflects the distribution and adjacency relations between nodes (map). After the map building, we also propose a route path estimation system. This algorithm takes advantage of the multiscale analysis. The accuracy in the pose estimation is not reduced to the nodes locations but also to intermediate positions between them. The algorithms have been tested using two different databases captured in real indoor environments under dynamic conditions.

Multi-channel Bayesian Adaptive Resonance Associate Memory for on-line topological map building

2016 ◽  
Vol 38 ◽  
pp. 269-280 ◽  
Author(s):  
Wei Hong Chin ◽  
Chu Kiong Loo ◽  
Manjeevan Seera ◽  
Naoyuki Kubota ◽  
Yuichiro Toda
Keyword(s):  
Map Building ◽  
Topological Map ◽  
Adaptive Resonance ◽  
On Line

Topological Gaussian ARTs with Short-Term and Long-Term Memory for Map Building and Fuzzy Motion Planning

2016 ◽  
Vol 6 (2) ◽  
pp. 63-87 ◽  
Author(s):  
Chin Wei Hong ◽  
Loo Chu Kiong ◽  
Kubota Naoyuki
Keyword(s):  
Motion Planning ◽  
Short Term Memory ◽  
Sensor Data ◽  
Long Term Memory ◽  
Map Building ◽  
Short Term ◽  
Topological Map ◽  
Term Memory ◽  
Input Layer

This paper proposes a cognitive architecture for building a topological map incrementally inspired by beta oscillations during place cell learning in hippocampus. The proposed architecture consists of two layer: the short-term memory layer and the long-term memory layer. The short-term memory layer emulates the entorhinal and the ? is the orientation system; the long-term memory layer emulates the hippocampus. Nodes in the topological map represent place cells (robot location), links connect nodes and store robot action (i.e. adjacent angle between connected nodes). The proposed method is formed by multiple Gaussian Adaptive Resonance Theory to receive data from various sensors for the map building. It consists of input layer and memory layer. The input layer obtains sensor data and incrementally categorizes the acquired information as topological nodes temporarily (short-term memory). In the long-term memory layer, the categorized information will be associated with robot actions to form the topological map (long-term memory). The advantages of the proposed method are: 1) it is a cognitive model that does not require human defined information and advanced knowledge to implement in a natural environment; 2) it can generate the map by processing various sensors data simultaneously in continuous space that is important for real world implementation; and 3) it is an incremental and unsupervised learning approach. Thus, the authors combine their Topological Gaussian ARTs method (TGARTs) with fuzzy motion planning to constitute a basis for mobile robot navigation in environment with slightly changes. Finally, the proposed approach was verified with several simulations using standardized benchmark datasets and real robot implementation.

Incremental online topological map building with a mobile robot

1999 ◽  
Author(s):  
Goksel Dedeoglu ◽  
Maja J. Mataric ◽  
Gaurav S. Sukhatme
Keyword(s):  
Mobile Robot ◽  
Map Building ◽  
Topological Map
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