Cooperative Transportation of Cable Suspended Payloads with MAVs Using Monocular Vision and Inertial Sensing

Guanrui Li, Rundong Ge, Giuseppe Loianno

Research output: Contribution to journalArticlepeer-review


Micro Aerial Vehicles (MAVs) have the great potential to be deployed in commercial or health care services such as e-commerce package delivery, transportation of medicines, same-day food delivery, and other time-sensitive transportation tasks. A team of MAVs can cooperatively transport objects to overcome the physical limitations of a single vehicle, while concurrently increasing the system's resilience to vehicles' failures. In this letter, we address the state estimation, control and trajectory tracking problems of cooperative transportation of cable suspended rigid body payloads with MAVs using monocular vision and inertial sensing. The key contributions are (a) a distributed vision-based coordinated control of the cable-suspended rigid body payload on SE(3), (b) a distributed estimation approach that allows each agent to estimate its cable direction and velocity independently, and (c) a new cooperative estimation scheme that can infer the payload's full 6-DoF states. This is obtained by sharing the robots' local position estimates and their relative position with respect to their corresponding attachment points on the payload. It allows to infer the payload's 6-DoF state when it is not directly measurable by each vehicle. The proposed solution runs in real-time on board and is validated through experimental results with multiple quadrotors transporting a rigid body payload via cables.

Original languageEnglish (US)
Article number9376103
Pages (from-to)5316-5323
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number3
StatePublished - Jul 2021


  • Aerial systems
  • aerial systems
  • applications
  • perception and autonomy

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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