I want what you've got: Cross platform portabiity and human-robot interaction assessment.

Human-robot interaction is a subtle, yet critical aspect of design that must be assessed during the development of both the human-robot interface and robot behaviors if the human-robot team is to effectively meet the complexities of the task environment. Testing not only ensures that the system can successfully achieve the tasks for which it was designed, but more importantly, usability testing allows the designers to understand how humans and robots can, will, and should work together to optimize workload distribution. A lack of human-centered robot interface design, the rigidity of sensor configuration, and the platform-specific nature of research robot development environments are a few factors preventing robotic solutions from reaching functional utility in real word environments. Often the difficult engineering challenge of implementing adroit reactive behavior, reliable communication, trustworthy autonomy that combines with system transparency and usable interfaces is overlooked in favor of other research aims. The result is that many robotic systems never reach a level of functional utility necessary even to evaluate the efficacy of the basic system, much less result in a system that can be used in a critical, real-world environment. Further, because control architectures and interfaces are often platform specific, it is difficult or even impossible to make usability comparisons between them. This paper discusses the challenges inherent to the conduct of human factors testing of variable autonomy control architectures and across platforms within a complex, real-world environment. It discusses the need to compare behaviors, architectures, and interfaces within a structured environment that contains challenging real-world tasks, and the implications for system acceptance and trust of autonomous robotic systems for how humans and robots interact in true interactive teams

An augmented reality interface for multi-robot tele-operation and control

This thesis presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semi-autonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor\u27s ability to control multiple robots. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. A sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks

Just Around the Corner: The Impact of Instruction Method and Corner Geometry on Teleoperation of Virtual Unmanned Ground Vehicles

Teleoperated robots have proven useful across various domains, as they can more readily search for survivors, survey collapsed and structurally unsound buildings, map out safe routes for rescue workers, and monitor rescue environments. A significant drawback of these robots is that they require the operator to perceive the environment indirectly. As such, camera angles, uneven terrain, lighting, and other environmental conditions can result in robots colliding with obstacles, getting stuck in rubble, and falling over (Casper & Murphy, 2003). To better understand how operators remotely perceive and navigate unmanned ground vehicles, the present work investigated operators’ abilities to negotiate corners of varying widths. In Experiment 1, we evaluated how instruction method impacts cornering time and collisions, looking specifically at the speed-accuracy tradeoff for negotiating corners. Participants navigated a virtual vehicle around corners under the instruction to focus on accuracy (i.e., avoiding collisions) or speed (i.e., negotiating the corners as quickly as possible). We found that as the task became more difficult, subjects’ cornering times increased, and their probability of successful cornering decreased. We also demonstrated that the Fitts’ law speed-accuracy tradeoff could be extended to a cornering task. In Experiment 2, we challenged two of the assumptions of Pastel et al.’s (2007) cornering law and assessed how corner angle and differences in path widths impacted cornering time. Participants navigated a virtual vehicle around corners of varying angles (45°, 90°, and 135°) and varying path widths. We found that increases in corner angle resulted in increased cornering times and a decreased probability of successful cornering. The findings from these experiments are applicable to contexts where an individual is tasked with remotely navigating around corners (e.g., video gaming, USAR, surveillance, military operations, training)

Report of the Workshop on Nuclear Facility Design Information Examination and Verification for Safeguards

Executive Summary The International Atomic Energy Agency (IAEA) implements nuclear safeguards and verifies countries are compliant with their international nuclear safeguards agreements. One of the key provisions in the safeguards agreement is the requirement that the country provide nuclear facility design and operating information to the IAEA relevant to safeguarding the facility, and at a very early stage. , This provides the opportunity for the IAEA to verify the safeguards-relevant features of the facility and to periodically ensure that those features have not changed. The national authorities (State System of Accounting for and Control of Nuclear Material - SSAC) provide the design information for all facilities within a country to the IAEA. The design information is conveyed using the IAEA’s Design Information Questionnaire (DIQ) and specifies: (1) Identification of the facility’s general character, purpose, capacity, and location; (2) Description of the facility’s layout and nuclear material form, location, and flow; (3) Description of the features relating to nuclear material accounting, containment, and surveillance; and (4) Description of existing and proposed procedures for nuclear material accounting and control, with identification of nuclear material balance areas. The DIQ is updated as required by written addendum. IAEA safeguards inspectors examine and verify this information in design information examination (DIE) and design information verification (DIV) activities to confirm that the facility has been constructed or is being operated as declared by the facility operator and national authorities, and to develop a suitable safeguards approach. Under the Next Generation Safeguards Initiative (NGSI), the National Nuclear Security Administrations (NNSA) Office of Non-Proliferation and International Security identified the need for more effective and efficient verification of design information by the IAEA for improving international safeguards in the future. Consequently, the NNSA Office of International Regimes and Agreements (NA-243) sponsored a team of U.S. Department of Energy National Laboratory nuclear safeguards experts and technologists to conduct a workshop on methods and technologies for improving this activity, under the ASA-100 Advanced Safeguards Approaches Project. The workshop focused on reviewing and discussing the fundamental safeguards needs, and presented technology and/or methods that could potentially address those needs more effectively and efficiently. Conclusions and Recommendations for technology to enhance the performance of DIV inspections are presented by the workshop team

Virtual reality based multi-modal teleoperation using mixed autonomy

The thesis presents a multi modal teleoperation interface featuring an integrated virtual reality based simulation aumented by sensors and image processing capabilities onboard the remotely operated vehicle. The virtual reality interface fuses an existing VR model with live video feed and prediction states, thereby creating a multi modal control interface. Virtual reality addresses the typical limitations of video-based teleoperation caused by signal lag and limited field of view thereby allowing the operator to navigate in a continuous fashion. The vehicle incorporates an on-board computer and a stereo vision system to facilitate obstacle detection. A vehicle adaptation system with a priori risk maps and real state tracking system enables temporary autonomous operation of the vehicle for local navigation around obstacles and automatic re-establishment of the vehicle\u27s teleoperated state. As both the vehicle and the operator share absolute autonomy in stages, the operation is referred to as mixed autonomous. Finally, the system provides real time update of the virtual environment based on anomalies encountered by the vehicle. The system effectively balances the autonomy between the human operator and on board vehicle intelligence. The reliability results of individual components along with overall system implementation and the results of the user study helps show that the VR based multi modal teleoperation interface is more adaptable and intuitive when compared to other interfaces

HUMAN CONTROL OF COOPERATING ROBOTS

Advances in robotic technologies and artificial intelligence are allowing robots to emerge fromresearch laboratories into our lives. Experiences with field applications show that we haveunderestimated the importance of human-robot interaction (HRI) and that new problems arise inHRI as robotic technologies expand. This thesis classifies HRI along four dimensions - human,robot, task, and world and illustrates that previous HRI classifications can be successfullyinterpreted as either about one of these elements or about the relationship between two or moreof these elements. Current HRI studies of single-operator single-robot (SOSR) control andsingle-operator multiple-robots (SOMR) control are reviewed using this approach.Human control of multiple robots has been suggested as a way to improve effectiveness inrobot control. Unlike previous studies that investigated human interaction either in low-fidelitysimulations or based on simple tasks, this thesis investigates human interaction with cooperatingrobot teams within a realistically complex environment. USARSim, a high-fidelity game-enginebasedrobot simulator, and MrCS, a distributed multirobot control system, were developed forthis purpose. In the pilot experiment, we studied the impact of autonomy level. Mixed initiativecontrol yielded performance superior to fully autonomous and manual control.To avoid limitation to particular application fields, the present thesis focuses on commonHRI evaluations that enable us to analyze HRI effectiveness and guide HRI design independentlyof the robotic system or application domain. We introduce the interaction episode (IEP), whichwas inspired by our pilot human-multirobot control experiment, to extend the Neglect ToleranceHUMAN CONTROL OF COOPERATING ROBOTSJijun Wang, Ph.D.University of Pittsburgh, 2007vmodel to support general multiple robots control for complex tasks. Cooperation Effort (CE),Cooperation Demand (CD), and Team Attention Demand (TAD) are defined to measure thecooperation in SOMR control. Two validation experiments were conducted to validate the CDmeasurement under tight and weak cooperation conditions in a high-fidelity virtual environment.The results show that CD, as a generic HRI metric, is able to account for the various factors thataffect HRI and can be used in HRI evaluation and analysis