Scalable Cooperative Transport of Cable-Suspended Loads With UAVs Using Distributed Trajectory Optimization
@article{jackson_scalable_2020,
title = {Scalable {Cooperative} {Transport} of {Cable}-{Suspended} {Loads} {With} {UAVs} {Using} {Distributed} {Trajectory} {Optimization}},
volume = {5},
issn = {2377-3766, 2377-3774},
url = {https://ieeexplore.ieee.org/document/9007450/},
abstract = {Most approaches to multi-robot control either rely on local decentralized control policies that scale well in the number of agents, or on centralized methods that can handle constraints and produce rich system-level behavior, but are typically computationally expensive and scale poorly in the number of agents, relegating them to offline planning. This work presents a scalable approach that uses distributed trajectory optimization to parallelize computation over a group of computationally-limited agents while handling general nonlinear dynamics and non-convex constraints. The approach, including near-real-time onboard trajectory generation, is demonstrated in hardware on a cable-suspended load problem with a team of quadrotors automatically reconfiguring to transport a heavy load through a doorway.},
language = {en},
number = {2},
urldate = {2021-04-09},
journal = {IEEE Robotics and Automation Letters},
author = {Jackson, Brian E. and Howell, Taylor A. and Shah, Kunal and Schwager, Mac and Manchester, Zachary},
month = apr,
year = {2020},
pages = {3368--3374},
month_numeric = {4}
}