Trajectory Planning for the Shapeshifting of Autonomous Surface Vessels
Name
20190916_Gheneti-etal_Trajectory_IEEE_.pdf
Description
Accepted version
Size
5.62 MB
Format
Adobe PDF
Checksum (MD5)
bc0848a21d835a9e09a5e8ef698081d8
Author(s)
Gheneti, Banti
Park, Shinkyu
Kelly, Ryan
Meyers, Drew
Leoni, Pietro
Ratti, Carlo
Rus, Daniela L
Date Issued
November 2019
Journal
International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Gheneti, Banti, Park, Shinkyu, Kelly, Ryan, Meyers, Drew, Leoni, Pietro et al. 2019. "Trajectory Planning for the Shapeshifting of Autonomous Surface Vessels." International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019.
Version
Author's final manuscript
Abstract
© 2019 IEEE. We present a trajectory planning algorithm for the shapeshifting of reconfigurable modular surface vessels. Each vessel is designed to latch with and unlatch from other vessels, which we aim to use to create dynamic infrastructure, such as on-demand bridges and temporary market squares, in canal environments. Our algorithm generates smooth and collision-free trajectories that the vessels can track to reconfigure their connections. We formulate the trajectory planning problem as Mixed Integer Quadratic Programming (MIQP) with a B-spline representation. We conceive a physical platform of the reconfigurable modular vessels and, through swimming pool experiments, show the efficacy of our trajectory planning algorithm for the shapeshifting of the vessels.
MIT Department
Senseable City Laboratory
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/MRS.2019.8901099
