Multigrid CHOMP with Local Smoothing
Date
2013
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Producer
Director
Performer
Choreographer
Costume Designer
Music
Videographer
Lighting Designer
Set Designer
Crew Member
Funder
Rehearsal Director
Concert Coordinator
Advisor
Moderator
Panelist
Alternative Title
Department
Swarthmore College. Dept. of Engineering
Type
Thesis (B.A.)
Original Format
Running Time
File Format
Place of Publication
Date Span
Copyright Date
Award
Language
en_US
Note
Table of Contents
Terms of Use
Full copyright to this work is retained by the student author. It may only be used for non-commercial, research, and educational purposes. All other uses are restricted.
Rights Holder
Access Restrictions
Terms of Use
Tripod URL
Identifier
Abstract
In recent years, CHOMP has found many applications in robotics research, as it combines
motion planning and optimization. Its flexibility in initial trajectory enables it to solve many
complex problems without pre- or post-processing. Even though using CHOMP under constraints
has been investigated, such algorithms are slow for large trajectories. In this paper,
we present Multigrid CHOMP with Local Smoothing, an algorithm to improve the runtime of
CHOMP under constraints without significantly reducing optimality. The effectiveness of this
algorithm is demonstrated in planning for three different problems, including door opening for
Hubo, a humanoid robot used for the DARPA Robotics Challenge.