Biography

I received the B.S. degree in control science and enginieering from Zhejiang University, Hangzhou, China, in 2017, where I’m currently working toward the M.S. degree in control science and engineering. My research interests include human pose estimation and deep learning.

Research and Interests

• Human Pose Estimation

Publications

• Mengmeng Wang, Yong Liu, Daobilige Su, Yufan Liao, Lei Shi, Jinhong Xu, and Jaime Valls Miro. Accurate and Real-Time 3-D Tracking for the Following Robots by Fusing Vision and Ultrasonar Information. IEEE/ASME Transactions on Mechatronics, 23:997–1006, 2018.
  [BibTeX] [Abstract] [DOI] [PDF]

  Acquiring the accurate three-dimensional (3-D) position of a target person around a robot provides valuable information that is applicable to a wide range of robotic tasks, especially for promoting the intelligent manufacturing processes of industries. This paper presents a real-time robotic 3-D human tracking system that combines a monocular camera with an ultrasonic sensor by an extended Kalman filter (EKF). The proposed system consists of three submodules: a monocular camera sensor tracking module, an ultrasonic sensor tracking module, and the multisensor fusion algorithm. An improved visual tracking algorithm is presented to provide 2-D partial location estimation. The algorithm is designed to overcome severe occlusions, scale variation, target missing, and achieve robust redetection. The scale accuracy is further enhanced by the estimated 3-D information. An ultrasonic sensor array is employed to provide the range information from the target person to the robot, and time of flight is used for the 2-D partial location estimation. EKF is adopted to sequentially process multiple, heterogeneous measurements arriving in an asynchronous order from the vision sensor, and the ultrasonic sensor separately. In the experiments, the proposed tracking system is tested in both a simulation platform and actual mobile robot for various indoor and outdoor scenes. The experimental results show the persuasive performance of the 3-D tracking system in terms of both the accuracy and robustness.

  @article{wang2018accuratear,
  title = {Accurate and Real-Time 3-D Tracking for the Following Robots by Fusing Vision and Ultrasonar Information},
  author = {Mengmeng Wang and Yong Liu and Daobilige Su and Yufan Liao and Lei Shi and Jinhong Xu and Jaime Valls Miro},
  year = 2018,
  journal = {IEEE/ASME Transactions on Mechatronics},
  volume = 23,
  pages = {997--1006},
  doi = {https://doi.org/10.1109/TMECH.2018.2820172},
  abstract = {Acquiring the accurate three-dimensional (3-D) position of a target person around a robot provides valuable information that is applicable to a wide range of robotic tasks, especially for promoting the intelligent manufacturing processes of industries. This paper presents a real-time robotic 3-D human tracking system that combines a monocular camera with an ultrasonic sensor by an extended Kalman filter (EKF). The proposed system consists of three submodules: a monocular camera sensor tracking module, an ultrasonic sensor tracking module, and the multisensor fusion algorithm. An improved visual tracking algorithm is presented to provide 2-D partial location estimation. The algorithm is designed to overcome severe occlusions, scale variation, target missing, and achieve robust redetection. The scale accuracy is further enhanced by the estimated 3-D information. An ultrasonic sensor array is employed to provide the range information from the target person to the robot, and time of flight is used for the 2-D partial location estimation. EKF is adopted to sequentially process multiple, heterogeneous measurements arriving in an asynchronous order from the vision sensor, and the ultrasonic sensor separately. In the experiments, the proposed tracking system is tested in both a simulation platform and actual mobile robot for various indoor and outdoor scenes. The experimental results show the persuasive performance of the 3-D tracking system in terms of both the accuracy and robustness.}
  }