Safe and Efficient Motion Planning in Robotic Manipulation through Formal Methods
Name
Yu-yumx35-SM-AeroAstro-2024-thesis.pdf
Description
Thesis PDF
Size
15.92 MB
Format
Adobe PDF
Checksum (MD5)
b7824924152b7c9df77d75898ffcaa23
Author(s)
Yu, Mingxin
Advisor(s)
Fan, Chuchu
Date Issued
May 2024
Publisher
Massachusetts Institute of Technology
Abstract
Manipulating rigid body objects in crowded environments poses significant challenges due to the need for rapid, real-time planning and the assurance of safe operational paths.
The challenges come from varying shapes of the manipulated objects and high-dimensional nature of manipulators.
This thesis addresses these issues by developing (1) a mixed-integer linear programming (MILP)-based approach to plan safe paths for rigid-body objects; and (2) a learned control barrier function (CBF) tailored for manipulators with multiple degrees of freedom (DoF) and an associated framework CBF-RRT to enable efficient planning for robotic manipulators. Comprehensive experimental results have shown that the proposed methods outperform baseline methods, providing tools for improving the safety and efficiency of robotic manipulators in complex environments.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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