Multisensor Fusion-Based Concurrent Environment Mapping and Moving Object Detection for Intelligent Service Robotics
Intelligent service robot development is an important and critical issue for human community applications. With the diverse and complex service needs, the perception and navigation are essential subjects. This investigation focuses on the synergistic fusion of multiple sensors for an intelligent ser...
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| Vydáno v: | IEEE transactions on industrial electronics (1982) Ročník 61; číslo 8; s. 4043 - 4051 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
IEEE
01.08.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Témata: | |
| ISSN: | 0278-0046, 1557-9948 |
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| Abstract | Intelligent service robot development is an important and critical issue for human community applications. With the diverse and complex service needs, the perception and navigation are essential subjects. This investigation focuses on the synergistic fusion of multiple sensors for an intelligent service robot that not only performs self-localization and mapping but also detects moving objects or people in the building it services. First of all, a new augmented approach of graph-based optimal estimation was derived for concurrent robot postures and moving object trajectory estimate. Moreover, all the moving object detection issues of a robot's indoor navigation are divided and conquered via multisensor fusion methodologies. From bottom to up, the estimation fusion methods are tactically utilized to get a more precise result than the one from only the laser ranger or stereo vision. Furthermore, for solving the consistent association problem of moving objects, a covariance area intersection belief assignment is applied for motion state evaluation and the complementary evidences such as kinematics and vision features are both synergized together to enhance the association efficiency with the evidence fusion method. The proof of concept with experiments has been successfully demonstrated and analyzed. |
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| AbstractList | Intelligent service robot development is an important and critical issue for human community applications. With the diverse and complex service needs, the perception and navigation are essential subjects. This investigation focuses on the synergistic fusion of multiple sensors for an intelligent service robot that not only performs self-localization and mapping but also detects moving objects or people in the building it services. First of all, a new augmented approach of graph-based optimal estimation was derived for concurrent robot postures and moving object trajectory estimate. Moreover, all the moving object detection issues of a robot's indoor navigation are divided and conquered via multisensor fusion methodologies. From bottom to up, the estimation fusion methods are tactically utilized to get a more precise result than the one from only the laser ranger or stereo vision. Furthermore, for solving the consistent association problem of moving objects, a covariance area intersection belief assignment is applied for motion state evaluation and the complementary evidences such as kinematics and vision features are both synergized together to enhance the association efficiency with the evidence fusion method. The proof of concept with experiments has been successfully demonstrated and analyzed. |
| Author | Luo, Ren C. Chun Chi Lai |
| Author_xml | – sequence: 1 givenname: Ren C. surname: Luo fullname: Luo, Ren C. email: renluo@ntu.edu.tw organization: Center for Intell. Robot. & Autom. Res., Nat. Taiwan Univ., Taipei, Taiwan – sequence: 2 surname: Chun Chi Lai fullname: Chun Chi Lai email: cclai@ira.ee.ntu.edu.tw organization: Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan |
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| SubjectTerms | Cameras Concurrent simultaneous localization and mapping (SLAM) and moving object detection environment perception Estimates Estimation Laser fusion Mapping Measurement by laser beam multisensor fusion Navigation Perception Robots Service robots Simultaneous localization and mapping Stereo vision Trajectories Vision |
| Title | Multisensor Fusion-Based Concurrent Environment Mapping and Moving Object Detection for Intelligent Service Robotics |
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