Object-Centric Planning for Long-Horizon Robotic Manipulation and Navigation

A primary objective within the robotics research community is the development of robotic agents capable of executing long-horizon tasks within complex and novel environments. The sparse and factored nature of object-centric planning makes it a good candidate for the reasoning engine inside such an agent. However, several challenges remain under an object-centric planning framework. Challenges arise in areas such as efficiently grounding states with novel objects in cluttered environments, maintaining efficiency under large object sets, and safe exploration and manipulation in partially observable and nondeterministic environments. This thesis examines these limitations and proposes several strategies for solving them while maintaining the generalizability and flexibility of object-centric planning in long-horizon tasks.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Curtis, Aidan

Advisors dc:contributor.advisor

• Kaelbling, Leslie P.
• Lozano-Pérez, Tomás
• Tenenbaum, Joshua B.

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/1721.1/151515

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/151515