2A2-Q04 Indoor environment mapping of large space with multi-robot(Localization and Mapping)

2014 ◽  
Vol 2014 (0) ◽  
pp. _2A2-Q04_1-_2A2-Q04_2
Author(s):  
Reo MATSUMURA ◽  
Shun ENOMOTO ◽  
Yoji KURODA
Keyword(s):  
Indoor Environment ◽  
Robot Localization ◽  
Large Space ◽  
Localization And Mapping ◽  
Multi Robot

scholarly journals Keyframes Global Map Establishing Method for Robot Localization through Content-Based Image Matching

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Tianyang Cao ◽  
Haoyuan Cai ◽  
Dongming Fang ◽  
Hui Huang ◽  
Chang Liu
Keyword(s):  
Image Matching ◽  
Robot Localization ◽  
Map Building ◽  
Matching Method ◽  
Large Space ◽  
Localization And Mapping ◽  
Indoor Mobile Robot ◽  
Cleaning Robots ◽  
Improving Accuracy ◽  
Space Distance

Self-localization and mapping are important for indoor mobile robot. We report a robust algorithm for map building and subsequent localization especially suited for indoor floor-cleaning robots. Common methods, for example, SLAM, can easily be kidnapped by colliding or disturbed by similar objects. Therefore, keyframes global map establishing method for robot localization in multiple rooms and corridors is needed. Content-based image matching is the core of this method. It is designed for the situation, by establishing keyframes containing both floor and distorted wall images. Image distortion, caused by robot view angle and movement, is analyzed and deduced. And an image matching solution is presented, consisting of extraction of overlap regions of keyframes extraction and overlap region rebuild through subblocks matching. For improving accuracy, ceiling points detecting and mismatching subblocks checking methods are incorporated. This matching method can process environment video effectively. In experiments, less than 5% frames are extracted as keyframes to build global map, which have large space distance and overlap each other. Through this method, robot can localize itself by matching its real-time vision frames with our keyframes map. Even with many similar objects/background in the environment or kidnapping robot, robot localization is achieved with position RMSE <0.5 m.

Multi-Robot Localization and Mapping Based on Signed Distance Functions

2016 ◽  
Vol 83 (3-4) ◽  
pp. 409-428 ◽  
Author(s):  
Philipp Koch ◽  
Stefan May ◽  
Michael Schmidpeter ◽  
Markus Kühn ◽  
Christian Pfitzner ◽  
...  
Keyword(s):  
Distance Functions ◽  
Robot Localization ◽  
Signed Distance ◽  
Localization And Mapping ◽  
Signed Distance Functions ◽  
Multi Robot

scholarly journals Multi-Robot Indoor Environment Map Building Based on Multi-Stage Optimization Method

2021 ◽  
Vol 1 (2) ◽  
pp. 145-161
Author(s):  
Hui Lu ◽  
Siyi Yang ◽  
Meng Zhao ◽  
Shi Cheng
Keyword(s):  
Indoor Environment ◽  
Optimization Method ◽  
Map Building ◽  
Environment Map ◽  
Multi Stage ◽  
Multi Robot

A Set Theoretic Approach to Dynamic Robot Localization and Mapping

2004 ◽  
Vol 16 (1) ◽  
pp. 23-47 ◽  
Author(s):  
M. Di Marco ◽  
A. Garulli ◽  
A. Giannitrapani ◽  
A. Vicino
Keyword(s):  
Theoretic Approach ◽  
Robot Localization ◽  
Localization And Mapping
Sign in / Sign up

Export Citation Format

Share Document