By Topic

Human tracking and following using sensor fusion approach for mobile assistive companion robot

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Luo, R.C. ; Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Nai-Wen Chang ; Shih-Chi Lin ; Shih-Chiang Wu

The ability to track and follow target person in intelligent service mobile robot is indispensable. A robust method for tracking and following a target person with a small size mobile robot by integrating single vision sensor and laser range finder is proposed. Instead of stereo-vision, we acquire the distance between mobile robot and target person by single camera. The laser range finder and vision sensor have their respective drawbacks. To compensate the drawbacks of each sensor we present the complementary data fusion approach - covariance intersection, it will complement the uncertainty of each sensor measure and enhance the reliability of human's position information. The virtual spring model is the control rule of mobile robot that can smoothly tracking target person. Experimental results validate the robust performance of the method.

Published in:

Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE

Date of Conference:

3-5 Nov. 2009