Collaborative transportation using MAVs via passive force control

Abstract

This paper shows a strategy based on passive force control for collaborative object transportation using Micro Aerial Vehicles (MAVs), focusing on the transportation of a bulky object by two hexacopters. The goal is to develop a robust approach which does not rely on: (a) communication links between the MAVs, (b) the knowledge of the payload shape and (c) the position of grasping point. The proposed approach is based on the master-slave paradigm, in which the slave agent guarantees compliance to the external force applied by the master to the payload via an admittance controller. The external force acting on the slave is estimated using a non-linear estimator based on the Unscented Kalman Filter (UKF) from the information provided by a visual inertial navigation system. Experimental results demonstrate the performance of the force estimator and show the collaborative transportation of a 1.2 m long object.

Two PVTOLs cooperative slung‐load transport control based on passivity

“…It can be seen that the control was able to asymptotically stabilize the system using the proposed methodology in an similar manner as the impedance control. The key advantage of our method comes from the fact that the proposed control does not require the estimation of the external forces acting on each platform, unlike the ones proposed in other works …”

“…The key advantage of our method comes from the fact that the proposed control does not require the estimation of the external forces acting on each platform, unlike the ones proposed in other works. 34,35,37 There also exists literature that addresses the slung-load problem using a passivity-based approach. The work presented in the work of Guerrero et al 38 uses an interconnection and damping assignment passivity-based control (IDA-PBC) that allows a quadcopter to stabilize a slung load.…”

“…The main contributions come from the properties of the proposed design approach. The system is guaranteed to be locally asymptotically stable toward a desired state set using very little system information, unlike similar approaches like the ones in other works . The algorithm in its minimum expression only requires the velocity information of each vehicle, which makes this an attractive option for a fail‐safe strategy in cooperative control schemes.…”

“…The system is guaranteed to be locally asymptotically stable toward a desired state set using very little system information, unlike similar approaches like the ones in other works. [34][35][36][37] The algorithm in its minimum expression only requires the velocity information of each vehicle, which makes this an attractive option for a fail-safe strategy in cooperative control schemes. Like the works of Guerrero et al 38 and Valk and Keviczky, 39 the proposed approach is based on passivity, which adds robustness to the system by modifying the point of minimal mechanical energy.…”

The ETH‐MAV Team in the MBZ International Robotics Challenge

“…Small objects have a cylindrical shape with a diameter of 200 mm and a maximum weight of 500 g. Large objects have a rectangular shape with dimensions , a maximum weight of 2 kg, and require collabrative transportation. Note that the presented system ignores large objects because our collaboration approach was not integrated at the time of the challenge (Tagliabue, Kamel, Siegwart, & Nieto, ; Tagliabue, Kamel, Verling, Siegwart, & Nieto, ) . The color of an object determines its type and score.…”