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ABSTRACTDigital Twin can provide emergency response staff with large quantities of useful information about the emergency. However, the capability of the staff to understand and use the information correctly is equally as important. Hence, regular crisis management training is required in sophisticated manufacturing systems. Still, the time and location constraints limit the frequency of conducting such practices. As such, virtual reality-based crisis management training methods were proposed in the literature. However, little research was conducted to investigate the underlying mechanisms that drive both the perception and the adoption of virtual reality for crisis management training among users. To address this research gap, this study proposed a research model to examine the effects of perceived usefulness, perceived ease of use, perceived behavioral control, application-specific self-efficacy, and attitude on users’ acceptance of the system. A partial least squares structural equation modeling approach was used for model testing based on 103 valid observations. The results demonstrated that the constructs proposed in our study determined user acceptance of the system, and the research model was able to explain 60% of the variance in behavioral intention. The likelihood of acceptance of related technologies may be increased by applying the findings of this study.

This paper focuses on the performance analysis of multi-segment continuum robots, including reachable workspace and dexterity performance. Since excellent dexterity is an important feature of continuum robots, two local indices inspired by separating robotic Jacobian matrix, namely axiality and angularity dexterity, are introduced to explore the dexterity. Then, a Monte Carlo Method is adopted to simulate the distribution of local dexterity over the workspace. On this basis, the corresponding global indices in axiality and angularity are defined to assess global dexterity performance. To investigate the optimal kinematic performance, an objective function related to the segment lengths is designed under the consideration of reachable workspace and dexterity performance. Finally, Particle Swarm Optimization (PSO) algorithm is used to solve this optimization problem successfully. The optimal length distributions for two-segment and three-segment continuum robots are discovered. Most importantly, it is found that our method can also apply to general multi-segment continuum robots.

The unprecedented scale and number of natural and man-made disasters in the past decade has urged international emergency search and rescue communities to seek for novel technology to enhance operation efficiency. Tele-operated search and rescue robots that can navigate deep into rubble to search for victims and to transfer critical field data back to the control console has gained much interest among emergency response institutions. In response to this need, a low-cost autonomous mini robot equipped with thermal sensor, accelerometer, sonar, pin-hole camera, microphone, ultra-bright LED and wireless communication module is developed to study the control of a group of decentralized mini search and rescue robots. The robot can navigate autonomously between voids to look for living body heat and can send back audio and video information to allow the operator to determine if the found object is a living human. This paper introduces the design and control of a low-cost robotic search and rescue system based on an immuno control framework developed for controlling decentralized systems. Design and development of the physical prototype and the immunity-based control system are described in this paper.