U-Go Robot allows tele-operations by means of a remote wireless joypad. Different tests using this guidance methodology have been done mainly on the Etna volcano and on the Volcano island. During these tests, transportation capabilities in very rough outdoor environment have been tested. The on-board sensors suite is composed by Stereo Camera, Webcam, X-Sens MTi Attitude and Heading Reference System (AHRS), Laser range finder (LRF), Bumpers, UltraSound Sonars, Global Navigation Satellite System (GNSS) or DGPS receiver. Moreover there are two dual-core computers; one is used for navigations purpose while the other is used for artificial vision purpose.
By using these sensors or a subset, different navigation algorithms have been implemented. For example, using a DGPS receiver and a Laser range finder, a navigation and obstacle avoidance algorithm based on the potential field theory (PFM), has been implemented. By using the stereo cameras set, different road following and obstacles avoidance algorithm have been tested. AHRS unit is used in order to compensate different sensors for road slope. By using ultra sound rangers and webcam, a navigation algorithm able to move the robot between greenhouses corridors has been implemented.
Different tests of these algorithms have been performed in greenhouses, vineyards and open fields. These tests have been made in cooperation with DIA, University of Catania, Mechanical section that is conducting different research in the field of precision farming. The U-Go Robot is used as a 'carrier' for different tools as automatic sprayers. The robot has been used also during the M-Elrob 2010 trials in order to test the system in a very demanding environment.
Different kinds of structures have been tested after FEM simulations. Some initial trials have been done using inter-digited polyethylene coated structures. As this kind of structure showed very poor results, devices with parallel electrodes have been realized and tested. The final structures are obtained by thermal fusion of two polypropylene layers with a thickness of 25um, heated up to 120°C and pressed with high pressure with rollers on both sides of aluminum electrodes. The structure obtained has a high strength, flexibility and a high coefficient of static friction with the substrate on which it is applied. Using this kind of electro-adhesive pads, a tracked climbing robot has been developed and tested. For this application "Peeling" methodology of multiple electro-adhesive pads has been exploited. This methodology allows to further improve performances in terms of pad adhesion, total payload and travelling speed. The electro-adhesive track has been realised by fitting different pads on a flexible roller-chain.
This kind of vacuum cups can adhere to different kind of rough surfaces because it can sustain vacuum inside also in the case when the cup is not in contact with the surface. This allows to reduce to zero the friction between the cup and the wall, to save energy, to increase robot speed, allows the robot to move over small obstacles or irregularities and to climb from a floor to a wall while maintaining high payloads (about 1.5 kg).
The robot use four wheels with four independent DC motors to move along the surface and use an inclinometer as feedback sensor in order to follow a reference trajectory. Moreover a wireless CCD camera is mounted on-board. Different tests about the cooperation between the Robovolc rover and the Alicia VTX were performed in order to investigate the possible use of the two in outdoor environment in critical situations where human operator can't reach the target vertical wall and can't perform visual inspection for safety or rescue purpose.
the field of UAS covers several aspects related to the topic of flying
Stability and waypoints navigation algorithms have been developed and tested and are currently employed on the fleet.
Inertial Measurement Units (IMU), Air Data Attitude and Heading Reference Systems (AHRS), Inertial Navigation Systems (INS), calibrated and compensated compass have been realized by making the most of sensors fusion algorithms.
Extended Kalman Filtering, quaternion algebra, sensor modelling have been examined in order to develop noise-free calibrated sensors units able to guarantee high performance in all conditions and environments.
Control algorithms self-tuning
Autonomous navigation algorithms often require a certain number of hours of flight tests to determine the best values for the parameters involved in the control loops. Self-tuning procedures are actually under study to make fast and easy values determination, allowing a reduction of field trials.
Computer Vision Algorithms
Images coming from UAVs are used for target detection and localization, for moving targets (UGV) tracking , for UAV position estimation, to detect safe landing areas for UAV.
Several studies have fully demonstrated the benefits coming from the cooperation between heterogeneous set of machines: the integration of data coming from several type of sensors and from different points of view allows to increase the informative contents, leading to a “cooperative perception”. In this sense, UAV and UGV represent complementary vehicles, the use of whom represents, together an integrated sensors network, a powerful surveillance and monitoring system. UAVs (Volcan) are used for area overseeing and emergency communication and terrain morphology changes detection, UGVs (Robovolc) are involved in area approaching and sampling and measuring operations.
Hardware In the Loop (HIL) architecture
The “Hardware in Loop” (HIL) architecture represents a powerful and cheap method to test and tune control systems. The case of tuning devices involved in the aeronautical field is very critical, since experimental trials are performed with time-consuming test flights and unsatisfactory results could lead to dangerous situations. An HIL simulator cannot fully replace field experiments, but it is very useful, especially in the preliminary phases, to discover and solve various kinds of problems. Therefore, the major aim of an HIL platform regards improvement in development time, cost and risk reduction. Once the performance is suitable for the application, the same controller hardware can be directly connected to the real UAV. In the figure above the developed architecture is represented. In this case study, the X-Plane flight simulator by Laminar Research, was adapted to the Volcan UAV: a model of the real aircraft was developed to determine the flight parameters; AHRS and GPS data are sent out to the autopilot through a CAN Bus, using a dedicated plugin and using the CANaerospace protocol. The block named “Autopilot” is the real electronic board while the HMI runs on a separate PC.
Simulation tools development
X-Plane flight simulator and Google Earth based simulation tool are used to develop and validate control, navigation and stability algorithms. Moreover, the implemented tools are used to implement and test aerial target geo-localization algorithms: the software allows to simulate a camera mounted on an airplane and to use the collected virtual images to test methods for the detection and localization of ground targets. A geo-localization algorithm based on an Extended Kalman filter has been implemented by using the developed tool.
Vision Based Tracking for a Coaxial Helicopter
The cooperation between a coaxial helicopter and the “MORDUC” Unmanned Ground Vehicle is under study in order to create a robotic system based on the adoption of heterogeneous unmanned vehicles. A vision algorithm able to estimate the position of a coaxial helicopter was developed; the implementation of a discrete Kalman filter allowed to obtain more accurate and less noisy data values. The dynamic model of a coaxial helicopter was derived and used in order to create a vision-based control system that would allow a three-dimensional tracking. A PID based algorithm was implemented to control the helicopter pose; both empirical and analytical based calibration procedures were adopted to obtain the most performing parameter values.