Human guided reach and grasp planner

Authors
Dallas, Matthew
ORCID
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Files
172584_Dallas_rpi_0185N_10341.pdf (2.46 MB)
Other Contributors
Trinkle, Jeffrey C.
Wen, John T.
Stewart, Charles V.
Issue Date
2014-05
Keywords
Computer science
Degree
MS
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
URI
https://hdl.handle.net/20.500.13015/1080
Abstract
Humans are extremely adept at grasping and manipulating a large variety of novel objects. The current state of robotic grasping, though improving, has not approached the level of robustness found in humans. In order to improve robotic grasping, this paper describes a method of integrating human grasp data into automated path planning and grasp acquisition called the Human-Guided Reach and Grasp Planner. Human grasp data is collected by combining input from two hardware systems: an array of infrared motion tracking cameras for spacial orientation and a sensor glove for highly accurate joint information. Collected data is stored for later use in robotic grasp planning. The Human-Guided Reach and Grasp Planner is then able to generate a trajectory for accomplishing the demonstrated task on the same object in new environments. This planner combines previous research in the fields of robotic learning, sequence alignment, human grasping and path planning among others.
Description
May 2014
School of Science
Department
Dept. of Computer Science
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
Access
CC BY-NC-ND. Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.
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