text: To design trustworthy robots, we need to understand the impact factors of trust: people's attitudes, experience, and characteristics; the robot's physical design, reliability, and performance; a task's specification and the circumstances under which it is to be performed, e.g. at leisure or under time pressure. As robots are used for a wide variety of tasks and applications, robot designers ought to be provided with evidence and guidance, to inform their decisions to achieve safe, trustworthy and efficient human-robot interactions. In this work, the impact factors of trust in a collaborative manufacturing scenario are studied by conducting an experiment with a real robot and participants where a physical object was assembled and then disassembled. Objective and subjective measures were employed to evaluate the development of trust, under faulty and non-faulty robot conditions, and the effect of previous experience with robots, and personality traits. Our findings highlight differences when compared to other, more social, scenarios with robotic assistants (such as a home care assistant), in that the condition (faulty or not) does not have a significant impact on the human's perception of the robot in terms of human-likeliness, likeability, trustworthiness, and even competence. However, personality and previous experience do have an effect on how the robot is perceived by participants, even though that is relatively small.
  @cite_22: In manufacturing, advanced robotic technology has opened up the possibility of integrating highly autonomous mobile robots into human teams. However, with this capability comes the issue of how to maximize both team efficiency and the desire of human team members to work with these robotic counterparts. To address this concern, we conducted a set of experiments studying the effects of shared decision-making authority in human---robot and human-only teams. We found that an autonomous robot can outperform a human worker in the execution of part or all of the process of task allocation ( @math p<0.001 for both), and that people preferred to cede their control authority to the robot @math (p<0.001). We also established that people value human teammates more than robotic teammates; however, providing robots authority over team coordination more strongly improved the perceived value of these agents than giving similar authority to another human teammate @math (p<0.001). In post hoc analysis, we found that people were more likely to assign a disproportionate amount of the work to themselves when working with a robot @math (p<0.01) rather than human teammates only. Based upon our findings, we provide design guidance for roboticists and industry practitioners to design robotic assistants for better integration into the human workplace.
  @cite_36: ABSTRACT: With the advent of collaborative robots, there is a great potential to improve work performance by human-robot collaboration in engineering tasks. Construction is no exception. Many construction tasks are based on the movement of objects (e.g., material), which are viable candidates for human-robot collaboration. However, due to the physically imposing nature of robot operations and the unstructured environments typical in construction, it is crucial to provide a safe and reliable environment for human workers when performing collaborative work with robots. In this paper, we use Immersive Virtual Environments (IVEs) to evaluate a human response to robots (e.g. perceived safety, trust, and team identification) while performing collaborative construction tasks with robots. By adopting IVEs, various types of robots, interactions, and tasks can be easily tested and evaluated to determine the best HRC practice, without the need to build and evaluate a physical prototype. Several experimental scenarios simulating collaborative masonry tasks were implemented using the Unity3D Game Engine and an Oculus Rift 3D Head-Mounted Display (HMD). The results demonstrate that it is important to take into account work environment of human-robot collaboration in order to understand how humans perceive robots when working with them.
  @cite_9: 
  @cite_21: This paper presents an overview of our work towards building humanoid robots that can work alongside people as cooperative teammates. We present our theoretical framework based on a novel combination of joint intention theory and collaborative discourse theory, and demonstrate how it can be applied to allow a human to work cooperatively with a humanoid robot on a joint task using speech, gesture, and expressive cues. Such issues must be addressed to enable many new and exciting applications for humanoid robots that require them to assist ordinary people in daily activities or to work as capable members of human-robot teams.
  @cite_0: 
  @cite_2: 
  @cite_5: Abstract Flexibility and changeability of assembly processes require a close cooperation between the worker and the automated assembly system. The interaction between human and robots improves the efficiency of individual complex assembly processes, particularly when a robot serves as an intelligent assistant. The paper gives a survey about forms of human–machine cooperation in assembly and available technologies that support the cooperation. Organizational and economic aspects of cooperative assembly including efficient component supply and logistics are also discussed.
  @cite_15: Prior work in human trust of autonomous robots suggests the timing of reliability drops impact trust and control allocation strategies. However, trust is traditionally measured post-run, thereby masking the real-time changes in trust, reducing sensitivity to factors like inertia, and subjecting the measure to biases like the primacy-recency effect. Likewise, little is known on how feedback of robot confidence interacts in real-time with trust and control allocation strategies. An experiment to examine these issues showed trust loss due to early reliability drops is masked in traditional post-run measures, trust demonstrates inertia, and feedback alters allocation strategies independent of trust. The implications of specific findings on development of trust models and robot design are also discussed.
  @cite_10: 
summary: Research in robotic co-workers has focused on the design aspects of such systems, including social and interaction aspects in terms of dialogues, gestures and social cues, or more engineering oriented such as scheduling shared collaborative building tasks and the design of protocols (e.g. turn taking), with the intention to obtain a collaboration between the user and the robot that is productive and efficient (e.g. @cite_21 @cite_5 @cite_22 ). Although trust metrics have been used to evaluate robotic systems in manufacturing tasks (e.g. in @cite_36 for collaborative masonry), research is needed to evaluate how trust is developed in these systems and their environments, compared to more social interactions such as in @cite_9 , or challenging remote interactions such as in @cite_10 @cite_0 @cite_15 @cite_2 .