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Simultaneous Localization and Mapping (SLAM)

for Robots

@ Class: Introduction to Intelligent Robots

 

LiDAR SLAM

  • We mounted a LiDAR scanner, IMU, and encoder on a mobile robot and utilized PKU-RobotSDK to control it.

  • We realized LiDAR SLAM by sensor fusion

 

 

 

 

Monocular Visual SLAM - coolest part of my work!

  • We calculated monocular visual odometry.

    • Fundamental matrix is estimated by 8-point algorithm.

  • We estimated the global position by Extended Kalman Filter (EKF) with input of visual odometry, encoder and IMU.

  • We mounted Xtion to perceive depth.  

  • Finally, we reconstruct the whole 3D scene by OpenGL.

 

Person-following robot with ORB-SLAM

@ Research assistant in CMU RoboMechanics Lab

  • We mounted ORB-SLAM and ERL for localization , SSD.for object detection and FCN for scene segmentation on RHex.

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