Safe and Efficient Motion Planning in Robotic Manipulation through Formal Methods

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.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Aeronautics and Astronautics

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Yu, Mingxin

Advisor dc:contributor.advisor

• Fan, Chuchu

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/155366

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/155366