Using Virtual Reality to Test Human-Robot Interaction During a Collaborative Task

Author(s):  
Roberta Etzi ◽  
Siyuan Huang ◽  
Giulia Wally Scurati ◽  
Shilei Lyu ◽  
Francesco Ferrise ◽  
...  

Abstract The use of collaborative robots in the manufacturing industry has widely spread in the last decade. In order to be efficient, the human-robot collaboration needs to be properly designed by also taking into account the operator’s psychophysiological reactions. Virtual Reality can be used as a tool to simulate human-robot collaboration in a safe and cheap way. Here, we present a virtual collaborative platform in which the human operator and a simulated robot coordinate their actions to accomplish a simple assembly task. In this study, the robot moved slowly or more quickly in order to assess the effect of its velocity on the human’s responses. Ten participants tested this application by using an Oculus Rift head-mounted display; ARTracking cameras and a Kinect system were used to track the operator’s right arm movements and hand gestures respectively. Performance, user experience, and physiological responses were recorded. The results showed that while humans’ performances and evaluations varied as a function of the robot’s velocity, no differences were found in the physiological responses. Taken together, these data highlight the relevance of the kinematic aspects of robot’s motion within a human-robot collaboration and provide valuable insights to further develop our virtual human-machine interactive platform.

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092529
Author(s):  
Junhao Xiao ◽  
Pan Wang ◽  
Huimin Lu ◽  
Hui Zhang

Human–robot interaction is a vital part of human–robot collaborative space exploration, which bridges the high-level decision and path planning intelligence of human and the accurate sensing and modelling ability of the robot. However, most conventional human–robot interaction approaches rely on video streams for the operator to understand the robot’s surrounding, which lacks situational awareness and force the operator to be stressed and fatigued. This research aims to improve efficiency and promote the natural level of interaction for human–robot collaboration. We present a human–robot interaction method based on real-time mapping and online virtual reality visualization, which is implemented and verified for rescue robotics. At the robot side, a dense point cloud map is built in real-time by LiDAR-IMU tightly fusion; the resulting map is further transformed into three-dimensional normal distributions transform representation. Wireless communication is employed to transmit the three-dimensional normal distributions transform map to the remote control station in an incremental manner. At the remote control station, the received map is rendered in virtual reality using parameterized ellipsoid cells. The operator controls the robot with three modes. In complex areas, the operator can use interactive devices to give low-level motion commands. In the less unstructured region, the operator can specify a path or even a target point. Afterwards, the robot follows the path or navigates to the target point autonomously. In other words, these two modes rely more on the robot’s autonomy. By virtue of virtual reality visualization, the operator can have a more comprehensive understanding of the space to be explored. In this case, the high-level decision and path planning intelligence of human and the accurate sensing and modelling ability of the robot can be well integrated as a whole. Although the method is proposed for rescue robots, it can also be used in other out-of-sight teleoperation-based human–robot collaboration systems, including but not limited to manufacturing, space, undersea, surgery, agriculture and military operations.


Technologies ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 77
Author(s):  
Sanika Doolani ◽  
Callen Wessels ◽  
Varun Kanal ◽  
Christos Sevastopoulos ◽  
Ashish Jaiswal ◽  
...  

Recently, the use of extended reality (XR) systems has been on the rise, to tackle various domains such as training, education, safety, etc. With the recent advances in augmented reality (AR), virtual reality (VR) and mixed reality (MR) technologies and ease of availability of high-end, commercially available hardware, the manufacturing industry has seen a rise in the use of advanced XR technologies to train its workforce. While several research publications exist on applications of XR in manufacturing training, a comprehensive review of recent works and applications is lacking to present a clear progress in using such advance technologies. To this end, we present a review of the current state-of-the-art of use of XR technologies in training personnel in the field of manufacturing. First, we put forth the need of XR in manufacturing. We then present several key application domains where XR is being currently applied, notably in maintenance training and in performing assembly task. We also reviewed the applications of XR in other vocational domains and how they can be leveraged in the manufacturing industry. We finally present some current barriers to XR adoption in manufacturing training and highlight the current limitations that should be considered when looking to develop and apply practical applications of XR.


2019 ◽  
Vol 38 (6) ◽  
pp. 747-765 ◽  
Author(s):  
Federica Ferraguti ◽  
Chiara Talignani Landi ◽  
Lorenzo Sabattini ◽  
Marcello Bonfè ◽  
Cesare Fantuzzi ◽  
...  

Admittance control allows a desired dynamic behavior to be reproduced on a non-backdrivable manipulator and it has been widely used for interaction control and, in particular, for human–robot collaboration. Nevertheless, stability problems arise when the environment (e.g. the human) the robot is interacting with becomes too stiff. In this paper, we investigate the stability issues related to a change of stiffness of the human arm during the interaction with an admittance-controlled robot. We propose a novel method for detecting the rise of instability and a passivity-preserving strategy for restoring a stable behavior. The results of the paper are validated on two robotic setups and with 50 users performing two tasks that emulate industrial operations.


2021 ◽  
Vol 8 ◽  
Author(s):  
Sebastian Zörner ◽  
Emy Arts ◽  
Brenda Vasiljevic ◽  
Ankit Srivastava ◽  
Florian Schmalzl ◽  
...  

As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilize two Neuro-Inspired COmpanion (NICO) - robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of non-verbal communication. We observe a correlation of 0.43 (p=0.02) between self-assessed trust and trust measured from the game, and a positive impact of non-verbal communication on trust (p=0.0008) and robot perception for anthropomorphism (p=0.007) and animacy (p=0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human’s trust in robots.


2020 ◽  
Author(s):  
Thomas Williams

In previous work, researchers in Human-Robot Interaction (HRI) have demonstrated that user trust in robots depends on effective and transparent communication. This may be particularly true forrobots used for transportation, due to user reliance on such robots for physical movement and safety. In this paper, we present the design of an experiment examining the importance of proactive communication by robotic wheelchairs, as compared to non-vehicular mobile robots, within a Virtual Reality (VR) environment. Furthermore, we describe the specific advantages – and limitations – of conducting this type of HRI experiment in VR.


2020 ◽  
Vol 110 (03) ◽  
pp. 146-150
Author(s):  
Marco Baumgartner ◽  
Tobias Kopp ◽  
Steffen Kinkel

Die industrielle Mensch-Roboter-Interaktion (MRI) eignet sich nach Einschätzung von Experten vor allem für die spezifischen Produktionsbedingungen kleiner und mittlerer Unternehmen (KMU). Nichtsdestotrotz finden sich MRI-Lösungen derzeit vorwiegend in Großunternehmen. Eine empirische Befragung von 81 Vertretern deutscher Industrieunternehmen legt die Vermutung nahe, dass es sich hierbei nicht nur um ein Umsetzungsdefizit handelt. Vielmehr scheinen KMU die Potenziale von MRI-Lösungen systematisch zu unterschätzen.   According to experts, industrial human-robot interaction (HRI) is particularly suitable for the specific production conditions of small and medium-sized enterprises (SMEs). Nevertheless, HRI solutions are currently mainly found in large companies. An empirical survey of 81 representatives of German industrial companies suggests that this is not just due to barriers in implementing collaborative robots. On the contrary, SMEs seem to systematically underestimate the potential of HRI solutions.


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