2026-09-23T16:57:48Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/120333 2023-09-05 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Kim, Joohyung 2023-05 application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01 The student, Victoria Colthurst, accepted the attached license on 2023-01-18 at 13:15. The student, Victoria Colthurst, submitted this Thesis for approval on 2023-01-18 at 13:44. This Thesis was approved for publication on 2023-01-23 at 14:12. DSpace SAF Submission Ingestion Package generated from Vireo submission #18824 on 2023-09-01 at 17:12:31 Autonomous object model acquisition with parallel jaw gripper Colthurst, Victoria Ruth 2023-01-23 Robotics Robot Robots 3d Three Dimensions Autonomous Object Model Acquisition Gripper Grasp Grasping Geometric Grasps Geometry-based Geometry Registration Point Cloud Clouds Reconstruction Cluttered Rotation Papras Plug Robotic Depth Scan Scans Granting robots the ability to identify and interact with any object in a cluttered, real-world environment requires solutions that tackle partial visibility and object novelty. Humans overcome this challenge with experience, which we emulate by developing a method to build a database of known 3D object models over time. We present an autonomous object registration pipeline deployed on a self-contained camera and robotic arm hardware system that produces 3D object point clouds. Experimentation evaluates the quantitative and qualitative aspects of the produced point clouds, and we show that our methods produce representations comparable with state-of-the-art methods. It is our hope that the solution presented in this thesis will aid in perception-based tasks that require identifying and interacting with objects in an unstructured environment. Thesis eng https://hdl.handle.net/2142/120333 Copyright 2023 Victoria Colthurst M.S. Thesis Electrical & Computer Engr University of Illinois at Urbana-Champaign Electrical & Computer Eng