Localization, Grasping, and Transportation of Magnetic Objects by a Team of MAVs in Challenging Desert-Like Environments

Giuseppe Loianno, Vojtech Spurny, Justin Thomas, Tomas Baca, Dinesh Thakur, Daniel Hert, Robert Penicka, Tomas Krajnik, Alex Zhou, Adam Cho, Martin Saska, Vijay Kumar

Research output: Contribution to journalArticlepeer-review


Autonomous Micro Aerial Vehicles (MAVs) have the potential to assist in real-life tasks involving grasping and transportation, but not before solving several difficult research challenges. In this work, we address the design, control, estimation, and planning problems for cooperative localization, grasping, and transportation of objects in challenging outdoor scenarios. We demonstrate an autonomous team of MAVs able to plan safe trajectories for manipulation of ferrous objects, while guaranteeing interrobot collision avoidance and automatically creating a map of the objects in the environment. Our solution is predominantly distributed, allowing the team to pick and transport ferrous disks to a final destination without collisions. This result is achieved using a new magnetic gripper with a novel feedback approach, enabling the detection of successful grasping. The gripper design and all the components to build a platform are clearly provided as open-source hardware for reuse by the community. Finally, the proposed solution is validated through experimental results, where difficulties include inconsistent wind, uneven terrain, and sandy conditions.

Original languageEnglish (US)
Pages (from-to)1576-1583
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number3
StatePublished - Jul 2018


  • Aerial systems: applications
  • field robots
  • swarms

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence


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