Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency
A novel mobile robots 3D-perception obstacle regions method in indoor environment based on Improved Salient Region Extraction (ISRE) is proposed. This model acquires the original image by the Kinect sensor and then gains Original Salience Map (OSM) and Intensity Feature Map (IFM) from the original i...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
|
| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2015/720174 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832564268887703552 |
|---|---|
| author | Tao Xu Songmin Jia Zhengyin Dong Xiuzhi Li |
| author_facet | Tao Xu Songmin Jia Zhengyin Dong Xiuzhi Li |
| author_sort | Tao Xu |
| collection | DOAJ |
| description | A novel mobile robots 3D-perception obstacle regions method in indoor environment based on Improved Salient Region Extraction (ISRE) is proposed. This model acquires the original image by the Kinect sensor and then gains Original Salience Map (OSM) and Intensity Feature Map (IFM) from the original image by the salience filtering algorithm. The IFM was used as the input neutron of PCNN. In order to make the ignition range more exact, PCNN ignition pulse input was further improved as follows: point multiplication algorithm was taken between PCNN internal neuron and binarization salience image of OSM; then we determined the final ignition pulse input. The salience binarization region abstraction was fulfilled by improved PCNN multiple iterations finally. Finally, the binarization area was mapped to the depth map obtained by Kinect sensor, and mobile robot can achieve the obstacle localization function. The method was conducted on a mobile robot (Pioneer3-DX). The experimental results demonstrated the feasibility and effectiveness of the proposed algorithm. |
| format | Article |
| id | doaj-art-7ae2f8f092914441be8e526e07b20d78 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-7ae2f8f092914441be8e526e07b20d782025-02-03T01:11:24ZengWileyJournal of Robotics1687-96001687-96192015-01-01201510.1155/2015/720174720174Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual SaliencyTao Xu0Songmin Jia1Zhengyin Dong2Xiuzhi Li3College of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, ChinaCollege of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, ChinaCollege of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, ChinaCollege of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, ChinaA novel mobile robots 3D-perception obstacle regions method in indoor environment based on Improved Salient Region Extraction (ISRE) is proposed. This model acquires the original image by the Kinect sensor and then gains Original Salience Map (OSM) and Intensity Feature Map (IFM) from the original image by the salience filtering algorithm. The IFM was used as the input neutron of PCNN. In order to make the ignition range more exact, PCNN ignition pulse input was further improved as follows: point multiplication algorithm was taken between PCNN internal neuron and binarization salience image of OSM; then we determined the final ignition pulse input. The salience binarization region abstraction was fulfilled by improved PCNN multiple iterations finally. Finally, the binarization area was mapped to the depth map obtained by Kinect sensor, and mobile robot can achieve the obstacle localization function. The method was conducted on a mobile robot (Pioneer3-DX). The experimental results demonstrated the feasibility and effectiveness of the proposed algorithm.http://dx.doi.org/10.1155/2015/720174 |
| spellingShingle | Tao Xu Songmin Jia Zhengyin Dong Xiuzhi Li Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency Journal of Robotics |
| title | Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency |
| title_full | Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency |
| title_fullStr | Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency |
| title_full_unstemmed | Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency |
| title_short | Obstacles Regions 3D-Perception Method for Mobile Robots Based on Visual Saliency |
| title_sort | obstacles regions 3d perception method for mobile robots based on visual saliency |
| url | http://dx.doi.org/10.1155/2015/720174 |
| work_keys_str_mv | AT taoxu obstaclesregions3dperceptionmethodformobilerobotsbasedonvisualsaliency AT songminjia obstaclesregions3dperceptionmethodformobilerobotsbasedonvisualsaliency AT zhengyindong obstaclesregions3dperceptionmethodformobilerobotsbasedonvisualsaliency AT xiuzhili obstaclesregions3dperceptionmethodformobilerobotsbasedonvisualsaliency |