In June 2015, the Defense Advanced Research Projects Agency (DARPA) Robotics Challenge (DRC) Finals were held in Pomona, California. The DRC Finals served as the third phase of the program designed to test the capabilities of semi-autonomous, remote humanoid robots to perform disaster response tasks with degraded communications. All competition teams were responsible for developing their own interaction method to control their robot. Of the 23 teams in the competition, 20 consented to participate in this study of human–robot interaction (HRI). The evaluation team observed the consenting teams during task execution in their control rooms (with the operators), and all 23 teams were observed on the field during the public event (with the robot). A variety of data were collected both before the competition and on-site. Each participating team’s interaction methods were distilled into a set of characteristics pertaining to the robot, operator strategies, control methods, and sensor fusion. Each task was decomposed into subtasks that were classified according to the complexity of the mobility and/or manipulation actions being performed. Performance metrics were calculated regarding the number of task attempts, performance time, and critical incidents, which were then correlated to each team’s interaction methods. The results of this analysis suggest that a combination of HRI characteristics, including balancing the capabilities of the operator with those of the robot and multiple sensor fusion instances with variable reference frames, positively impacted task performance. A set of guidelines for designing HRI with remote, semi-autonomous humanoid robots is proposed based on these results.

In terms of safety and convenience, an Unmanned Aerial Vehicle (UAV) offers significant benefits when conducting remote NDT evaluations by mitigating hazards and inefficiencies associated with manned access. Traditionally, UAV remote inspections rely on high-resolution cameras, providing a visual overview of surface condition. This photogrammetric inspection, however, cannot distinguish minute discontinuities or deformations beneath a surface coating. Ultrasonic inspection is a Non-Destructive Testing (NDT) method conventionally used in corrosion mapping. Surface contacting ultrasonic transducers offer the potential for internal inspection of an industrial asset, providing enhanced structural integrity information. However, manually piloting a UAV with sufficient surface proximity to perform a detailed, contact-based examination requires a highly developed skillset and intense concentration. Limitations of payload mass and electronic interference also represent significant challenges to be overcome. Addressing such issues, this paper demonstrates the implementation of an autonomous UAV system with an integrated ultrasonic contact measurement payload. The prototype is autonomously guided and undertakes the contact thickness measurement process without manual intervention.

Remote photogrammetric inspection is a Non-Destructive Testing method used to quantify surface integrity and detect external discontinuities. The mobility and size of an unmanned aerial vehicle (UAV) offer the flexibility to quickly deploy remote photogrammetric inspections for large-scale assets. In this paper, the results of a photogrammetric inspection are presented as a 3D profile, reconstructed from UAV captured images. Experiments were conducted indoors using a wind turbine blade section obtained from a recently decommissioned asset. The naturally occurring surface features representative of environmental wear were augmented with a small number of artificial features to aid in the visualisation of inspection quality. An autonomous UAV system for photogrammetric inspections is demonstrated and the influence of image parameters such as environmental light levels, motion blur and focal blur quantified in terms of their impact on the inspection accuracy. Over the range of parameter values studied, the poorest scenario was observed to cause a degradation in reconstruction error by a factor of 13 versus the optimal. Reconstruction quality when employing a laser range scanner to maintain standoff distance relative to the object during flight was also investigated. In this schema, the controller automatically generated a real-time adaptive flight path to follow the outer profile of the wind turbine blade and, consequently, demonstrated improved image quality during close-range inspection of an object with complex geometry. Inspection accuracy was quantified using the error of the photogrammetric reconstruction as compared to a model acquired using independent metrology equipment. While utilising the laser-based adaptive path, error in the reconstructed geometry was reduced by a factor of 2.7 versus a precomputed circular path. In the best case, the mean deviation was below 0.25 mm. Instances of wind turbine blade damage such as edge crushing, surface imperfections, early stage leading edge erosion were clearly observed in the textured 3D reconstruction profiles, indicating the utility of the successful inspection process. The results of this paper evaluate the impact of optical environmental effects on photogrammetric inspection accuracy, offering practical insight towards mitigation of negative effects.

The mobility of an Unmanned Aerial Vehicle (UAV) offers significant benefits when deploying remote Non-Destructive Testing (NDT) inspections of large-scale assets. Ultrasonic inspection is primarily a contact-based NDT method, that grants the opportunity to remotely monitor the structural health of an industrial asset with enhanced internal integrity information. Presented in this paper is an implementation of an autonomous UAV system, equipped with an ultrasonic thickness measurement payload. This system is designed to conduct ultrasonic inspections of non-magnetic facilities and industrial infrastructure where surface adhesion cannot be achieved magnetically. Operating within a laboratory environment, this system autonomously positioned the transducer on a vertically mounted, unpainted, aluminium sample and completed an ultrasonic thickness measurement without manual intervention. An onboard laser scanner provided instantaneous UAV alignment and standoff error measurements versus the sample's surface normal vector. While inspecting a region of the aluminium sample with 12.92 mm nominal thickness, the UAV system demonstrated a measurement error of 0.03 mm. During this process, the standard deviation of the craft's positional error was recorded to be below 63.26 mm, accompanied by an angular alignment error versus the surface normal vector of below 2.71°. The accuracy of the UAV deployed inspection, including thickness measurement accuracy and positional accuracy, depends on many factors. As such, transducer alignment constraints, electrical noise and UAV stability are investigated and discussed. Findings from this paper may be taken to inform future research regarding autonomous airborne ultrasonic inspection of constructed infrastructure and industrial facilities.

Intact soil-core microcosms were used to compare persistence of Pseudomonas chlororaphis 3732RN-L11 in fallow soil and on wheat roots with field releases at diverse sites. Parallel field and microcosm releases at four sites in 1996 were repeated with addition of one site in 1997. Microcosms were obtained fresh and maintained at 60% soil water holding capacity in a growth chamber at 70% relative humidity, a 12-hour photoperiod, and constant temperature. Persistence of 3732RN-L11 was measured at each site in field plots and microcosms at 7-21 day intervals, and in duplicate microcosms sampled at an independent laboratory. Linear regression slopes of field plot and microcosm persistence were compared for each site, and between identical microcosms sampled at different sites, using log10 transformed plate counts. Microcosm persistence closely matched field plots for wheat roots, but persistence in fallow soil differed significantly in several instances where persistence in field plots was lower than in microcosms. Analysis of weather variations at each site indicated that rainfall events of 30-40 mm caused decreased persistence in fallow soil. Cooler temperatures enhanced persistence in field plots at later time points. Inter-laboratory comparison of regression slopes showed good agreement for data generated at different sites, though in two instances, longer sampling periods at one site caused significant differences between the sites. Soil characteristics were compared and it was found that fertility, namely the carbon to nitrogen ratio, and the presence of expanding clays, were related to persistence. These microcosm protocols produced reliable data at low cost, and were useable for pre-release risk analyses for microorganisms.