SLAM with occupancy grid and particle filter, using lidar, joints, IMU and odometry data from THOR humanoid robot
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Updated
Mar 22, 2018 - Python
SLAM with occupancy grid and particle filter, using lidar, joints, IMU and odometry data from THOR humanoid robot
6D Object Pose Estimation using RGBD Data and Fast-ICP
a quaternion-based Unscented Kalman Filter on IMU to estimate quadrotor orientation. With estimates and camera data, a sphere panorama is generated by image stitching
Simultaneous Localization and Mapping using particle filters
Path planning in aerial images using imitation learning
Gesture recognition using Hidden Markov Models
a hybrid Gaussian Mixture Model for color segmentation, and connected component analysis for object detection
a left-to-right Hidden Markov Model for cellphone gesture recognition, using IMU data
ESE 650: Learning in Robotics, Project 3, Gesture Recognition using Hidden Markov Models and IMU Data
Object detection of red barrels using Gaussian Mixture Models
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