Identifying Objects Buried in a Noisy Point Cloud

Identifying Objects Buried in a Noisy Point Cloud

This project focused on building an image perception pipeline for an RBGD camera. A table with assorted objects was presented in Gazebo simulation space, and after cleaning and segmenting the data I built an SVM perception model to identify each object. My perception pipeline accurately identified all items in each of the 3 provided scenes and packaged the information for a robot to pick up and place each object in a predefined bin.