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

  title = {Scalable {Cooperative} {Transport} of {Cable}-{Suspended} {Loads} {With} {UAVs} {Using} {Distributed} {Trajectory} {Optimization}},
  volume = {5},
  issn = {2377-3766, 2377-3774},
  url = {},
  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}