Autonomous object model acquisition with parallel jaw gripper

Colthurst, Victoria Ruth

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https://hdl.handle.net/2142/120333 Copy

Description

Title

Autonomous object model acquisition with parallel jaw gripper

Author(s)

Colthurst, Victoria Ruth

Issue Date

2023-01-23

Director of Research (if dissertation) or Advisor (if thesis)

Kim, Joohyung

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• 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

Language

eng

Abstract

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.

Graduation Semester

2023-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/120333

Copyright and License Information

Copyright 2023 Victoria Colthurst

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