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Large scale factories such as steel, wood, construction, recycling plants and landfills involve the procurement of raw material which may include radiating parts, that must be monitored, because potentially dangerous for workers. Manufacturing operations are carried out in unstructured environments, where fully autonomous unmanned aerial vehicle (UAV) inspection is hardly applicable. In this work we report on the development of a haptic teleoperated UAV for localization of radiation sources in industrial plants. Radiation sources can be localized and identified thanks to a novel CZT-based custom gamma-ray detector integrated on the UAV, providing light, compact, spectroscopic, and low power operation. UAV operation with a human in the loop allows an expert operator to focus on selected candidate areas, thereby optimizing short flight mission in face of the constrained acquisition times required by nuclear inspection. To cope with the reduced situational awareness of the remote operator, force feedback is exploited as an additional sensory channel. The developed prototype has been demonstrated both in relevant and operational environments.

We describe a remotely-piloted aerial system (RPAS) designed for environmental monitoring and specifically equipped for detection of nuclear radiating substances or materials in outdoor environments. The RPAS comprises an unmanned aerial vehicle (UAV), a lightweight radiation detector mounted on a gimbal connected to the UAV and providing real-time radiation information, a suitable communication infrastructure, and an HMI system including a novel haptic-based teleoperation interface purposely designed for environmental monitoring. The haptic interface supplements the standard graphical and visual sensorial channels to improve the efficiency of the UAV exploration. Simulation tests as well as preliminary experiments with the RPAS have shown that the haptic component of the HMI interface reduces the mental load of the operator who drives the UAV.

This work proposes a haptic teleoperation system of an unmanned aerial vehicle (UAV) aimed at localizing radiation sources in outdoor environments. Radiation sources are localized and identified by equipping the UAV with a CdZnTe-based custom X-ray detector providing light, compact, and low power operation. The UAV is guided in direct sight by the operator. The system allows exploration of potentially dangerous areas without a close exposure of the human operator. The operator is able to provide motion commands to the UAV while receiving force feedback from a 3DOF haptic interface. Force feedback provides an attractive basin around the location of the most intense detected radiation. Preliminary experiments have been conducted to test the elements of the system.

Localization and identification of nuclear and radiological material are main issues in case of nuclear accident or terrorist attack. In these cases, the use of a unmanned aerial vehicle would be highly recommended in order to preserve the safety of the human operators. For this purpose, we have integrated a compact, light, low power operating, CZT-based gamma ray detector on a commercially available UAV. The system allows exploration of potentially dangerous areas without a close exposure of the human operator. The operator is able to provide motion commands to the UAV while receiving force feedback from a 3DOF haptic interface. Force feedback provides an attractive basin around the location of the most intense detected radiation. A field experiment has been carried out and a 192Ir nuclear source has been localized and identified exploiting the novel teleoperation system.

This work investigates the use of visuo-haptic augmented reality for programming object manipulation tasks by demonstration. A desktop augmented reality system is presented in which the user is not co-located with the environment and a 3DOF haptic device, providing force feedback, is adopted for user interaction. The interaction paradigm allows the user to select and manipulate virtual objects superimposed upon a visual representation of the real workspace. The approach also supports physics-based animation of rigid bodies. In the proposed method automatic object recognition and registration are performed from 3D range data acquired by a laser scanner mounted on a robot arm. We next investigate the potential of the augmented reality system for programming manipulation tasks by demonstration. Experiments show that a precedence graph, encoding the sequential structure of the task, can be successfully extracted from multiple user demonstrations.