Low-cost uncrewed aerial vehicles (UAVs) are replacing manned aircraft for airborne radiation mapping applications such as nuclear accident response scenarios or surveying ore deposits and mine sites because of their cost-effectiveness and ability to conduct surveys at lower altitude compared to manned counterparts. Both multi-rotor UAVs and fixed-wing UAVs are well established technologies for aerial radiation mapping applications, however, both also have drawbacks: multi-rotor UAVs are very limited in flight time and range, and fixed-wing UAVs usually require facilities for take-off and landing. A compromise solution is introduced in this work, using a fixed-wing vertical take-off and landing (VTOL) UAV that combines the flexibility of a multi-rotor UAV with the range and flight time of a fixed-wing UAV. The first implementation of a VTOL with radiation mapping capabilities is presented, based on a commercial WingtraOne UAV augmented with CsI scintillator and CZT semiconductor gamma spectrometers. The radiation mapping capabilities of the prototype are demonstrated in a case study, mapping the distribution of radionuclides around the South Terras legacy uranium mine in the south of England, United Kingdom, and the results are compared with previous studies using multi-rotor and manned aircraft to survey the same area.

To reduce costs and effort, experiments in human-robot interaction can be carried out in Virtual Reality (VR) or in screen-based (SB) formats. However, it is not well examined whether robots are perceived and experienced in the same way in VR and SB as they are in the physical world. This study addresses this topic in a between-subjects experiment, measuring trust and engagement of an interaction with a mobile service robot in a museum scenario. Measures were made in three different settings, either the real world, in VR or in a game-like SB and then compared with an ANOVA. The results indicate, that neither trust nor engagement differ dependent on the experimental setting. The results imply that both VR and SB are eligible ways to explore the interaction with a mobile service robot, if some peculiarities of each medium are taken into account.

Based on the NASA in-Space Assembled Telescope (iSAT) study (Bulletin of the American Astronomical Society, 2019, 51, 50) which details the design and requirements for a 20-m parabolic in-space telescope, NASA Langley Research Center (LaRC) has been developing structural and robotic solutions to address the needs of building larger in-space assets. One of the structural methods studied involves stackable and collapsible modular solutions to address launch vehicle volume constraints. This solution uses a packing method that stacks struts in a dixie-cup like manner and a chemical composite bonding technique that reduces weight of the structure, adds strength, and offers the ability to de-bond the components for structural modifications. We present in this paper work towards a soft material robot end-effector, capable of suppling the manipulability, pressure, and temperature requirements for the bonding/de-bonding of these conical structural components. This work is done to investigate the feasibility of a hybrid soft robotic end-effector actuated by Twisted and Coiled Artificial Muscles (TCAMs) for in-space assembly tasks. TCAMs are a class of actuator which have garnered significant recent research interest due to their allowance for high force to weight ratio when compared to other popular methods of actuation within the field of soft robotics, and a muscle-tendon actuation design using TCAMs leads to a compact and lightweight system with controllable and tunable behavior. In addition to the muscle-tendon design, this paper also details the early investigation of an induction system for adhesive bonding/de-bonding and the sensors used for benchtop design and testing. Additionally, we discuss the viability of Robotic Operating System 2 (ROS2) and Gazebo modeling environments for soft robotics as they pertain to larger simulation efforts at LaRC. We show real world test results against simulation results for a method which divides the soft, continuous material of the end-effector into discrete links connected by spring-like joints.

Gaze cues serve an important role in facilitating human conversations and are generally considered to be one of the most important non-verbal cues. Gaze cues are used to manage turn-taking, coordinate joint attention, regulate intimacy, and signal cognitive effort. In particular, it is well established that gaze aversion is used in conversations to avoid prolonged periods of mutual gaze. Given the numerous functions of gaze cues, there has been extensive work on modelling these cues in social robots. Researchers have also tried to identify the impact of robot gaze on human participants. However, the influence of robot gaze behavior on human gaze behavior has been less explored. We conducted a within-subjects user study (N = 33) to verify if a robot’s gaze aversion influenced human gaze aversion behavior. Our results show that participants tend to avert their gaze more when the robot keeps staring at them as compared to when the robot exhibits well-timed gaze aversions. We interpret our findings in terms of intimacy regulation: humans try to compensate for the robot’s lack of gaze aversion.

The present work revisits how artificial intelligence, as technology and ideology, is based on the rational choice theory and the techno-liberal discourse, supported by large corporations and investment funds. Those that promote using different algorithmic processes (such as filter bubbles or echo chambers) create homogeneous and polarized spaces that reinforces people’s ethical, ideological, and political narratives. These mechanisms validate bubbles of choices as statements of fact and contravene the prerequisites for exercising deliberation in pluralistic societies, such as the distinction between data and values, the affirmation of reasonable dissent, and the relevance of diversity as a condition indispensable for democratic deliberation.