## 5 Results and Discussion  
### Experimental Setup  
This section describes the strategy used to evaluate the UAV-UGV cooperation in face of ground obstacles for the accomplishment of a load transportation task our configuration setup is show in Figure 8. As can be seen in the figure, the UGVs adopted are the Pioneer 3-DX nonholonomic unicycle mobile platform, and the UAV is the Bebop 2 quadrotor. The posture of the vehicles is tracked by the OptiTrack motion tracking system, consisting of 15 cameras, which are placed around the experimental arena. The data captured by using mocap technology is then used as a constraint to reduce the ambiguity of the real-time inverse kinematic process by capturing the posture of all elements that make up the experiment and thus updating the control signals. To communicate with the robots, the robot operating system (ROS) is used. As for the high-level control code, it was executed by using MATLAB(r). Communication between ROS and MATLAB is done through a proprietary MATLAB library, which emulates the necessary ROS nodes and topics. The positions of the load, the electromagnet, and the trailer are also captured by the OptiTrack system.  
Once this work aims to perform a load transportation task, the electromagnet actuator is one of the main components of our system. However, the device should not have a permanent magnet, because the proposal considers capture and release actions only at opportune moments. Furthermore, to reduce the weight of the device, which must be on board the UAV, we have chosen to trigger it remotely. Thus, the capture and release action is decided externally and transmitted via wireless to the actuator.  
The electromagnet has a capacity of up to 2.5 kg and runs on DC power through a two-cell, 7.4-V, 300-mA lithium polymer battery. The receiver board that controls the operation of the electromagnet is controlled by an Arduino Nano microcontroller. Furthermore, such a board allocates all the necessary components on a compact-sized board, so as not to interfere with the controllability of the UAV during flight. Table 1 lists the components used to make the transmitter and receiver, shown in Figure 9. Note that there is a yellow LED in Figure 9a. If it is on, the electromagnet is on; otherwise, it is off.  
Figure 8: The experimental setup.  
\begin{table}
\begin{tabular}{l c c} \hline \hline \multirow{2}{*}{**Component**} & \multirow{2}{*}{**Quantity**} & **Present in** \\  & & **Transmitter (T)** \\  & & **or Receptor (R)** \\ \hline Arduino Nano & 2 & T and R \\ Battery & 1 & R \\ TBJ 538 & 1 & R \\ Electromagnet & 1 & R \\ LED & 1 & T \\ Push Button & 1 & T \\ Resistors 220 \(\Omega\) & 2 & T and R \\ Switch & 1 & R \\ Radio NRF24L01 & 2 & T and R \\ Antenna for WiFi Module & 1 & R \\
2.4 GHz Wireless Transceiver Module—NRF24L01 & 2 & T and R \\ \hline \hline \end{tabular}
\end{table}
Table 1: Table of components used in transmitter and receptor.  
Figure 9: Printed circuit boards (PCBs) for electromagnet actuation.  
Importantly, one of the biggest challenges faced with suspended cable transportation is the effect of the load swinging after being captured by the electromagnet device. In other words, the actuator must be able to support the weight of the load even when the swing effect is present as a consequence of the UAV's displacement maneuvers. In the case of this work, cautious movements, with small angles of tilt and rotation of the UAV, helped mitigate the oscillations.  
In terms of the load, it has a cubic shape of 10 cm side and weight of 72 g. Figure 10 shows two configurations: empty and full cargo. In the last case, a set of five styrofoam block increases the cargo weight by 25 g. The metal plate over the cargo prototype makes possible its interaction with the magnetic actuator.