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Simultaneous Localization and Mapping (SLAM)
for Robots
@ Class: Introduction to Intelligent Robots
LiDAR SLAM
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We mounted a LiDAR scanner, IMU, and encoder on a mobile robot and utilized PKU-RobotSDK to control it.
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We realized LiDAR SLAM by sensor fusion
Monocular Visual SLAM - coolest part of my work!
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We calculated monocular visual odometry.
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Fundamental matrix is estimated by 8-point algorithm.
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We estimated the global position by Extended Kalman Filter (EKF) with input of visual odometry, encoder and IMU.
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We mounted Xtion to perceive depth.
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Finally, we reconstruct the whole 3D scene by OpenGL.

Person-following robot with ORB-SLAM
@ Research assistant in CMU RoboMechanics Lab
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We mounted ORB-SLAM and ERL for localization , SSD.for object detection and FCN for scene segmentation on RHex.
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