Scalable Cooperative Transport of Cable-Suspended Loads With UAVs Using Distributed Trajectory Optimization

Brian E. Jackson, Taylor A. Howell, Kunal Shah, Mac Schwager, Zachary Manchester

IEEE Robotics and Automation Letters, 2020

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.

BibTeX

@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},
  keywords = {multi-robot, aerial, optimization},
  pages = {3368--3374},
  month_numeric = {4}
}