Bayesian Fusion of Ceiling Mounted Camera and Laser Range Finder on a Mobile Robot for People Detection and Localization

2012 ◽  
pp. 41-51 ◽  
Author(s):  
Ninghang Hu ◽  
Gwenn Englebienne ◽  
Ben J. A. Kröse
Keyword(s):  
Mobile Robot ◽  
Laser Range Finder ◽  
Range Finder ◽  
People Detection ◽  
Laser Range ◽  
Bayesian Fusion ◽  
Detection And Localization

scholarly journals Human Tracking with a Mobile Robot using a Laser Range-Finder

2006 ◽  
Vol 24 (5) ◽  
pp. 605-613 ◽  
Author(s):  
Shinichi Okusako ◽  
Shigeyuki Sakane
Keyword(s):  
Mobile Robot ◽  
Human Tracking ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range

Landmark detection and localization for mobile robot applications: a multisensor approach

Robotica ◽  
2009 ◽  
Vol 28 (5) ◽  
pp. 663-673 ◽  
Author(s):  
Dilan Amarasinghe ◽  
George K. I. Mann ◽  
Raymond G. Gosine
Keyword(s):  
The Other ◽  
Laser Range Finder ◽  
Fusion Method ◽  
Range Finder ◽  
Landmark Detection ◽  
Laser Range ◽  
Localization And Mapping ◽  
Laser Data ◽  
Single Sensor ◽  
Detection And Localization

SUMMARYThis paper describes a landmark detection and localization using an integrated laser-camera sensor. Laser range finder can be used to detect landmarks that are direction invariant in the laser data such as protruding edges in walls, edges of tables, and chairs. When such features are unavailable, the dependant processes will fail to function. However, in many instances, larger number of landmarks can be detected using computer vision. In the proposed method, camera is used to detect landmarks while the location of the landmark is measured by the laser range finder using laser-camera calibration information. Thus, the proposed method exploits the beneficial aspects of each sensor to overcome the disadvantages of the other sensor. While highlighting the drawbacks and limitations of single sensor based methods, an experimental results and important statistics are provided for the verification of the affectiveness sensor fusion method using Extended Kalman Filter (EKF) based simultaneous localization and mapping (SLAM) as an example application.

Development and Experimental Verification of a Person Tracking System of Mobile Robots Using Sensor Fusion of Inertial Measurement Unit and Laser Range Finder for Occlusion Avoidance

2021 ◽  
Vol 33 (1) ◽  
pp. 33-43
Author(s):  
Kazuhiro Funato ◽  
Ryosuke Tasaki ◽  
Hiroto Sakurai ◽  
Kazuhiko Terashima ◽  
◽  
...  
Keyword(s):  
Mobile Robot ◽  
Sensor Fusion ◽  
Experimental Verification ◽  
Inertial Measurement Unit ◽  
Tracking System ◽  
Measurement Unit ◽  
Laser Range Finder ◽  
Range Finder ◽  
Inertial Measurement ◽  
Laser Range

The authors have been developing a mobile robot to assist doctors in hospitals in managing medical tools and patient electronic medical records. The robot tracks behind a mobile medical worker while maintaining a constant distance from the worker. However, it was difficult to detect objects in the sensor’s invisible region, called occlusion. In this study, we propose a sensor fusion method to estimate the position of a robot tracking target indirectly by an inertial measurement unit (IMU) in addition to the direct measurement by an laser range finder (LRF) and develop a human tracking system to avoid occlusion by a mobile robot. Based on this, we perform detailed experimental verification of tracking a specified person to verify the validity of the proposed method.

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