Topological map building for mobile robots based on GIS in urban environments

2011 ◽  
Author(s):  
Yu-Cheol Lee ◽  
Christiand ◽  
Seung-Hwan Park ◽  
Wonpil Yu ◽  
Sung-Hoon Kim
Keyword(s):  
Mobile Robots ◽  
Urban Environments ◽  
Map Building ◽  
Topological Map

scholarly journals A novel edge gradient algorithm for multiple mobile robots cooperative mapping in unknown environment

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986038
Author(s):  
Huang Yiqing ◽  
Wang Hui ◽  
Wei Lisheng ◽  
Gao Wengen ◽  
Ge Yuan
Keyword(s):  
Visual Field ◽  
Mobile Robots ◽  
Information Exchange ◽  
Field Of View ◽  
Gradient Algorithm ◽  
Movement Direction ◽  
Mapping Technique ◽  
Map Building ◽  
Multiple Mobile Robots ◽  
Motion Behavior

This article presented a cooperative mapping technique using a novel edge gradient algorithm for multiple mobile robots. The proposed edge gradient algorithm can be divided into four behaviors such as adjusting the movement direction, evaluating the safety of motion behavior, following behavior, and obstacle information exchange, which can effectively prevent multiple mobile robots falling into concave obstacle areas. Meanwhile, a visual field factor is constructed based on biological principles so that the mobile robots can have a larger field of view when moving away from obstacles. Also, the visual field factor will be narrowed due to the obstruction of the obstacle when approaching an obstacle and the obtained map-building data are more accurate. Finally, three sets of simulation and experimental results demonstrate the performance superiority of the presented algorithm.

scholarly journals Safe Navigation for Indoor Mobile Robots. Part II: Exploration, Self-Localization and Map Building

2003 ◽  
Vol 22 (12) ◽  
pp. 1019-1039 ◽  
Author(s):  
Alessandro Corrêa Victorino ◽  
Patrick Rives ◽  
Jean-Jacques Borrelly
Keyword(s):  
Mobile Robots ◽  
Map Building ◽  
Safe Navigation

Probabilistic and Count Methods in Map Building for Autonomous Mobile Robots

2000 ◽  
pp. 120-137 ◽  
Author(s):  
Miguel Rodríguez ◽  
José Correa ◽  
Roberto Iglesias ◽  
Carlos V. Regueiro ◽  
Senén Barro
Keyword(s):  
Mobile Robots ◽  
Autonomous Mobile Robots ◽  
Map Building

POSSIBILISTIC SONAR DATA MODELING FOR MOBILE ROBOTS

1999 ◽  
Vol 07 (02) ◽  
pp. 173-198 ◽  
Author(s):  
K. DEMIRLI ◽  
M. MOLHIM ◽  
A. BULGAK
Keyword(s):  
Probability Theory ◽  
Mobile Robots ◽  
Data Modeling ◽  
Possibility Theory ◽  
Sensor Design ◽  
Map Building ◽  
Sonar Sensors ◽  
New Models ◽  
Possibility Distributions ◽  
Target Characteristics

Sonar sensors are widely used in mobile robots applications such as navigation, map building, and localization. The performance of these sensors is affected by the environmental phenomena, sensor design, and target characteristics. Therefore, the readings obtained from these sensors are uncertain. This uncertainity is often modeled by using Probability Theory. However, the probablistic approach is valid when the available knowledge is precise which is not the case in sonar readings. In this paper, the behavior of sonar readings reflected from walls and corners are studied, then new models of angular uncertainty and radial imprecision for sonar readings obtained from corners and walls are proposed. These models are represented by using Possibility Theory, mainly possibility distributions.

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.

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