No abstract

Cooperative manipulation is a basic skill in groups of humans, animals, and in many robotic applications. Besides being an interesting challenge, communication-less approaches have been applied to groups of robots in order to achieve higher scalability and simpler hardware and software design. We present a generic model and control law for robots cooperatively manipulating an object, for both ground and floating systems. The control method exploits a leader-follower scheme and is based only on implicit communication (i.e., the sensing of contact forces). The control objective mainly consists of steering the object manipulated by the swarm of robots to a desired position and orientation in a cooperative way. For a system with just one leader, we present analytical results on the equilibrium configurations and their stability that are then validated by numerical simulations. The role of object internal forces (induced by the robots through contact forces) is discussed in terms of convergence of the object position and orientation to the desired values. We also present a discussion on additional properties of the controlled system that were investigated using thorough numerical analysis, namely, the robustness of the system when the object is subject to external disturbances in non-ideal conditions, and how the number of leaders in the swarm can affect the aforementioned convergence and robustness.

This work introduces the G-Fly-Crane, a proof-of-concept aerial multi-robot system designed to demonstrate the advantage of using multiple aerial robots as a valuable tool for novel construction techniques, not requiring the use of heavy engines and costly infrastructures. We experimentally demonstrate its capability to perform pick-and-place and manipulation tasks in a construction scenario, with an increased payload capacity and dexterity compared to the single robot case. The system is composed of three aerial robots connected to a platform by three pairs of cables. The platform is equipped with a gripper, enabling the grasping of objects. The paper describes in detail the hardware and software architecture of our prototype and explains the implemented control methods. A shared control strategy incorporates the human operator in the control loop, thus increasing the overall system reliability when performing complex tasks. The paper also discusses the next steps required to bring this technology from indoor laboratory conditions to real-world applications.

The Fly-Crane is a multi-robot aerial manipulator system composed of three aerial vehicles towed to a platform by means of six cables. This paper presents a method to estimate the mass and the position of the center of mass of a loaded platform (i.e. the Fly-Crane platform including a transported load). The precise knowledge of these parameters allows to sensibly minimize the total effort exerted during a full-pose manipulation task The estimation is based on the measure of the forces applied by the aerial vehicles to the platform in different static configurations. We demonstrate that only two different configurations are sufficient to estimate the inertial parameters. Far-from-ideal numerical simulations show the effectiveness of the estimation method. Once the parameters are estimated, we show the enhancement of the system performances by minimizing the total exerted effort. The validity of the proposed algorithm in non-ideal conditions is presented through simulations based on the Gazebo simulator.