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This project focuses on training robots to grasp everyday objects accurately. We gather a unique point cloud dataset using an iPhone's LiDAR and process it with Polycam. We develop a PointNet model from scratch to perform multi-class classification and part-segmentation, guiding the robot on where to grasp objects.

Python 100.00%
classification computer-vision deep-learning lidar point-cloud pointnet pytorch grasp manipulator-robotics robotics

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