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Decentralized Adaptive Aerospace Transportation of Unknown Loads Using A Team of Robots

Longsen Gao, Kevin Aubert, David Saldana, Claus Danielson, Rafael Fierro

Abstract

Transportation missions in aerospace are limited to the capability of each aerospace robot and the properties of the target transported object, such as mass, inertia, and grasping locations. We present a novel decentralized adaptive controller design for multiple robots that can be implemented in different kinds of aerospace robots. Our controller adapts to unknown objects in different gravity environments. We validate our method in an aerial scenario using multiple fully actuated hexarotors with grasping capabilities, and a space scenario using a group of space tugs. In both scenarios, the robots transport a payload cooperatively through desired three-dimensional trajectories. We show that our method can adapt to unexpected changes that include the loss of robots during the transportation mission.

Decentralized Adaptive Aerospace Transportation of Unknown Loads Using A Team of Robots

Abstract

Transportation missions in aerospace are limited to the capability of each aerospace robot and the properties of the target transported object, such as mass, inertia, and grasping locations. We present a novel decentralized adaptive controller design for multiple robots that can be implemented in different kinds of aerospace robots. Our controller adapts to unknown objects in different gravity environments. We validate our method in an aerial scenario using multiple fully actuated hexarotors with grasping capabilities, and a space scenario using a group of space tugs. In both scenarios, the robots transport a payload cooperatively through desired three-dimensional trajectories. We show that our method can adapt to unexpected changes that include the loss of robots during the transportation mission.
Paper Structure (12 sections, 18 equations, 4 figures, 1 table)

This paper contains 12 sections, 18 equations, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Decentralized Adaptive Transportation Problem
  3. Robots and Reference Frames
  4. Dynamics
  5. Vehicle's Wrench
  6. Grasping Dynamics of Manipulator System
  7. Decentralized Adaptive Transportation
  8. Simulation Results
  9. Simulation-1: Transportation Task in Earth
  10. Simulation-2: Transportation Task in Space
  11. Conclusion and Future Work
  12. Acknowledgement

Figures (4)

  • Figure 1: (a) Fully actuated hexarotor UAV with a grasping mechanism. (b) Space tug with 6 rockets around its sides. The red arrows indicate the propulsion direction of each rocket.
  • Figure 2: A group of fully actuated hexarotor UAVs grasping a free-floating object during the transportation task in 3D space.
  • Figure 3: (a) Transportation task implemented on multiple fully actuated hexarotor UAVs with a grasping system in Earth on MuJoCo platform. (b)-(f) Simulation results for using $n$ UAVs collaboratively to transport the payload in $SE(3)$ under gravity environment.
  • Figure 4: (a) Transportation task implemented on a group of space tugs in space on MuJoCo platform. (b)-(f) Simulation results for using $n$ space tugs collaboratively to transport the payload in $SE(3)$ under zero-gravity environment.

Theorems & Definitions (2)

  • definition thmcounterdefinition: Drone
  • definition thmcounterdefinition: Space Tug