6 research outputs found

    A Comparison of Visualisation Methods for Disambiguating Verbal Requests in Human-Robot Interaction

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    Picking up objects requested by a human user is a common task in human-robot interaction. When multiple objects match the user's verbal description, the robot needs to clarify which object the user is referring to before executing the action. Previous research has focused on perceiving user's multimodal behaviour to complement verbal commands or minimising the number of follow up questions to reduce task time. In this paper, we propose a system for reference disambiguation based on visualisation and compare three methods to disambiguate natural language instructions. In a controlled experiment with a YuMi robot, we investigated real-time augmentations of the workspace in three conditions -- mixed reality, augmented reality, and a monitor as the baseline -- using objective measures such as time and accuracy, and subjective measures like engagement, immersion, and display interference. Significant differences were found in accuracy and engagement between the conditions, but no differences were found in task time. Despite the higher error rates in the mixed reality condition, participants found that modality more engaging than the other two, but overall showed preference for the augmented reality condition over the monitor and mixed reality conditions

    Mobile Mixed-Reality Interfaces That Enhance Human–Robot Interaction in Shared Spaces

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    Although user interfaces with gesture-based input and augmented graphics have promoted intuitive human–robot interactions (HRI), they are often implemented in remote applications on research-grade platforms requiring significant training and limiting operator mobility. This paper proposes a mobile mixed-reality interface approach to enhance HRI in shared spaces. As a user points a mobile device at the robot’s workspace, a mixed-reality environment is rendered providing a common frame of reference for the user and robot to effectively communicate spatial information for performing object manipulation tasks, improving the user’s situational awareness while interacting with augmented graphics to intuitively command the robot. An evaluation with participants is conducted to examine task performance and user experience associated with the proposed interface strategy in comparison to conventional approaches that utilize egocentric or exocentric views from cameras mounted on the robot or in the environment, respectively. Results indicate that, despite the suitability of the conventional approaches in remote applications, the proposed interface approach provides comparable task performance and user experiences in shared spaces without the need to install operator stations or vision systems on or around the robot. Moreover, the proposed interface approach provides users the flexibility to direct robots from their own visual perspective (at the expense of some physical workload) and leverages the sensing capabilities of the tablet to expand the robot’s perceptual range

    A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI

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    Healthcare workers face a high risk of contagion during a pandemic due to their close proximity to patients. The situation is further exacerbated in the case of a shortage of personal protective equipment that can increase the risk of exposure for the healthcare workers and even non-pandemic related patients, such as those on dialysis. In this study, we propose an emergency, non-invasive remote monitoring and control response system to retrofit dialysis machines with robotic manipulators for safely supporting the treatment of patients with acute kidney disease. Specifically, as a proof-of-concept, we mock-up the touchscreen instrument control panel of a dialysis machine and live-stream it to a remote user’s tablet computer device. Then, the user performs touch-based interactions on the tablet device to send commands to the robot to manipulate the instrument controls on the touchscreen of the dialysis machine. To evaluate the performance of the proposed system, we conduct an accuracy test. Moreover, we perform qualitative user studies using two modes of interaction with the designed system to measure the user task load and system usability and to obtain user feedback. The two modes of interaction included a touch-based interaction using a tablet device and a click-based interaction using a computer. The results indicate no statistically significant difference in the relatively low task load experienced by the users for both modes of interaction. Moreover, the system usability survey results reveal no statistically significant difference in the user experience for both modes of interaction except that users experienced a more consistent performance with the click-based interaction vs. the touch-based interaction. Based on the user feedback, we suggest an improvement to the proposed system and illustrate an implementation that corrects the distorted perception of the instrumentation control panel live-stream for a better and consistent user experience

    Implementation of ROS-enabled Industrial Production Environment

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    This thesis presents the procedure to implement the ROS-Industrial architecture into the industrial robotic environment. This is implemented by developing the packages related to modeling and configuring the industrial robot with ROS-I. Using the ROS capabilities, libraries and tools, this thesis develops an industrial robot application which enables the industrial robot to adapt and react to its workspace changes. This implies that it acknowledges the presence of obstacles in its path and re-plans an alternative path in order to avoid those. The obstacles may be the objects or the humans working near the robot. This system enables the industrial robot to exhibit the flexible movements in a fixed as well as dynamic environments. The fixed objects present in the robot workspace are created manually in the ROS environment while the dynamic objects are brought into the ROS environment by integrating the 3D sensor (camera) with the ROS. Moreover, this thesis presents the mechanism for ROS integrated gripper control of the ABB IRB4600 robot. It provides the analysis on the motion planners for selecting the best motion planner for ABB IRB4600 robot. Furthermore, this research establishes the framework for letting the industrial robots out of their cages and enables the continuation of the robot operation while sharing the workspace with human operators. Safety of those operators is supported in this system with its collision avoidance feature. This feature provides an additional safety measure to human workers along with the already configured safety standards (ISO/TS 15066, ISO 10218-1 & 10218-2) of human-robot collaboration

    Augmented Reality and Robotics: A Survey and Taxonomy for AR-enhanced Human-Robot Interaction and Robotic Interfaces

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    This paper contributes to a taxonomy of augmented reality and robotics based on a survey of 460 research papers. Augmented and mixed reality (AR/MR) have emerged as a new way to enhance human-robot interaction (HRI) and robotic interfaces (e.g., actuated and shape-changing interfaces). Recently, an increasing number of studies in HCI, HRI, and robotics have demonstrated how AR enables better interactions between people and robots. However, often research remains focused on individual explorations and key design strategies, and research questions are rarely analyzed systematically. In this paper, we synthesize and categorize this research field in the following dimensions: 1) approaches to augmenting reality; 2) characteristics of robots; 3) purposes and benefits; 4) classification of presented information; 5) design components and strategies for visual augmentation; 6) interaction techniques and modalities; 7) application domains; and 8) evaluation strategies. We formulate key challenges and opportunities to guide and inform future research in AR and robotics

    Development and evaluation of mixed reality-enhanced robotic systems for intuitive tele-manipulation and telemanufacturing tasks in hazardous conditions

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    In recent years, with the rapid development of space exploration, deep-sea discovery, nuclear rehabilitation and management, and robotic-assisted medical devices, there is an urgent need for humans to interactively control robotic systems to perform increasingly precise remote operations. The value of medical telerobotic applications during the recent coronavirus pandemic has also been demonstrated and will grow in the future. This thesis investigates novel approaches to the development and evaluation of a mixed reality-enhanced telerobotic platform for intuitive remote teleoperation applications in dangerous and difficult working conditions, such as contaminated sites and undersea or extreme welding scenarios. This research aims to remove human workers from the harmful working environments by equipping complex robotic systems with human intelligence and command/control via intuitive and natural human-robot- interaction, including the implementation of MR techniques to improve the user's situational awareness, depth perception, and spatial cognition, which are fundamental to effective and efficient teleoperation. The proposed robotic mobile manipulation platform consists of a UR5 industrial manipulator, 3D-printed parallel gripper, and customized mobile base, which is envisaged to be controlled by non-skilled operators who are physically separated from the robot working space through an MR-based vision/motion mapping approach. The platform development process involved CAD/CAE/CAM and rapid prototyping techniques, such as 3D printing and laser cutting. Robot Operating System (ROS) and Unity 3D are employed in the developing process to enable the embedded system to intuitively control the robotic system and ensure the implementation of immersive and natural human-robot interactive teleoperation. This research presents an integrated motion/vision retargeting scheme based on a mixed reality subspace approach for intuitive and immersive telemanipulation. An imitation-based velocity- centric motion mapping is implemented via the MR subspace to accurately track operator hand movements for robot motion control, and enables spatial velocity-based control of the robot tool center point (TCP). The proposed system allows precise manipulation of end-effector position and orientation to readily adjust the corresponding velocity of maneuvering. A mixed reality-based multi-view merging framework for immersive and intuitive telemanipulation of a complex mobile manipulator with integrated 3D/2D vision is presented. The proposed 3D immersive telerobotic schemes provide the users with depth perception through the merging of multiple 3D/2D views of the remote environment via MR subspace. The mobile manipulator platform can be effectively controlled by non-skilled operators who are physically separated from the robot working space through a velocity-based imitative motion mapping approach. Finally, this thesis presents an integrated mixed reality and haptic feedback scheme for intuitive and immersive teleoperation of robotic welding systems. By incorporating MR technology, the user is fully immersed in a virtual operating space augmented by real-time visual feedback from the robot working space. The proposed mixed reality virtual fixture integration approach implements hybrid haptic constraints to guide the operator’s hand movements following the conical guidance to effectively align the welding torch for welding and constrain the welding operation within a collision-free area. Overall, this thesis presents a complete tele-robotic application space technology using mixed reality and immersive elements to effectively translate the operator into the robot’s space in an intuitive and natural manner. The results are thus a step forward in cost-effective and computationally effective human-robot interaction research and technologies. The system presented is readily extensible to a range of potential applications beyond the robotic tele- welding and tele-manipulation tasks used to demonstrate, optimise, and prove the concepts
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