Impact of Robot Initiative on Human-Robot Collaboration

Munzer, Thibaut; Mollard, Yoan; Lopes, Manuel

doi:10.1145/3029798.3038373

Cited by 11 publications

(10 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Studies investigating workers' perception of allocation processes in a collaborative context are quite rare. Munzer et al (2017) find that a self-learning, autonomous and initiatively task-executing robot is perceived as more helpful and is preferred in collaboration. Castro et al (2017) compare a human-led and a robot-led experimental setting in which humans and robots have to execute a task based on the division of labor.…”

Section: Influence On the Allocation Decisionmentioning

confidence: 91%

“…The question evolving is whether people are actually more pleased with the allocation process itself compared to making their own decision. Or is it just the higher productivity (Gombolay et al, 2015) and fluency of processes (Munzer et al, 2017) resulting from automation-generated planning that makes them more satisfied? An indication for this could be the findings of Cummings and Bruni (2010): They show how people even try to participate in a resource allocation task that can be highly automated, choosing a manual adaptation of automated decisions or comparing an automated to a manual solution instead of relying on the system.…”

Section: Influence On the Allocation Decisionmentioning

confidence: 99%

See 1 more Smart Citation

Psychological Effects of the Allocation Process in Human–Robot Interaction – A Model for Research on ad hoc Task Allocation

2020

View full text Add to dashboard Cite

Task allocation is immensely important when it comes to designing human-robot interaction (HRI), but although it is the shaping part of the interaction, it is merely regarded as a process with its own effects on human thinking and behavior. This study aims at linking research from different fields like psychological theory, HRI and allocation optimization to create a new process model of ad hoc task allocation in human-robot interaction. It addresses the process characteristics and psychological outcomes of a real-time allocation process that integrates the worker. To achieve this, we structured the process into steps and identified relevant psychological constructs associated with them. The model is a first step toward ergonomic research on the selforganized allocation of tasks in HRI, but may also be an inspiration for practitioners designing HRI systems. To create successful work in HRI, designing the technology is an important foundation, but a participative, thought-out process for allotting tasks could be the key to adequate autonomy, work satisfaction and successful cooperation.

show abstract

Section: Influence On the Allocation Decisionmentioning

confidence: 91%

Section: Influence On the Allocation Decisionmentioning

confidence: 99%

Psychological Effects of the Allocation Process in Human–Robot Interaction – A Model for Research on ad hoc Task Allocation

2020

View full text Add to dashboard Cite

show abstract

“…It also shows that people prefer a cooperating system as a team partner and feeling more important to the task in a shared decision (Gombolay et al 2015). Munzer et al (2017) show that users prefer a robot that acts semi-autonomously and initiates actions on its own compared to one that needs to be assigned each task manually. The reasons for these findings require further research.…”

Section: Task Allocation In Human-robot Interactionmentioning

confidence: 99%

The best task allocation process is to decide on one’s own: effects of the allocation agent in human–robot interaction on perceived work characteristics and satisfaction

Tausch

Kluge

2020

Cogn Tech Work

View full text Add to dashboard Cite

New technologies are ever evolving and have the power to change human work for the better or the worse depending on the implementation. For human–robot interaction (HRI), it is decisive how humans and robots will share tasks and who will be in charge for decisions on task allocation. The aim of this online experiment was to examine the influence of different decision agents on the perception of a task allocation process in HRI. We assume that inclusion of the worker in the allocation will create more perceived work resources and will lead to more satisfaction with the allocation and the work results than a decision made by another agent. To test these hypotheses, we used a fictional production scenario where tasks were allocated to the participant and a robot. The allocation decision was either made by the robot, by an organizational unit, or by the participants themselves. We then looked for differences between those conditions. Our sample consisted of 151 people. In multiple ANOVAs, we could show that satisfaction with the allocation process, the solution, and with the result of the work process was higher in the condition where participants themselves were given agency in the allocation process compared to the other two. Those participants also experienced more task identity and autonomy. This has implications for the design of allocation processes: The inclusion of workers in task allocation can play a crucial role in leveraging the acceptance of HRI and in designing humane work systems in Industry 4.0.

show abstract

“…Positioning and movement are a known interaction and communication vector in Human-Human relationships [6]. Various other vectors have received attention from the HRI field as seen in works studying gaze [14], intention [15], engagement [16], robot initiative [17], reaction time to touch stimuli [18]. In comparison, few works study the effect of varying the dimensions controlled by navigation algorithms on a robot's interaction with surrounding humans.…”

Section: Related Workmentioning

confidence: 99%

Studying Navigation as a Form of Interaction: a Design Approach for Social Robot Navigation Methods

Scales

Aycard

Auberge

2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

Social Navigation methods attempt to integrate knowledge from Human Sciences fields such as the notion of Proxemics into mobile robot navigation. They are often evaluated in simulations, or lab conditions with informed participants, and studies of the impact of the robot behavior on humans are rare. Humans communicate and interact through many vectors, among which are motion and positioning, which can be related to social hierarchy and the socio-physical context. If a robot is to be deployed among humans, the methods it uses should be designed with this in mind. This work acts as the first step in an ongoing project in which we explore how to design navigation methods for mobile robots destined to be deployed among humans. We aim to consider navigation as more than just a functionality of the robot, and to study the impact of robot motion on humans. In this paper, we focus on the personfollowing task. We selected a state of the art person-following method as the basis for our method, which we modified and extended in order for it to be more general and adaptable. We conducted pilot experiments using this method on a real mobile robot in ecological contexts. We used results from the experiments to study the Human-Robot Interaction as a whole by analysing both the person-following method and the human behavior. Our preliminary results show that the way in which the robot followed a person had an impact on the interaction that emerged between them.

show abstract

Impact of Robot Initiative on Human-Robot Collaboration

Cited by 11 publications

References 7 publications

Psychological Effects of the Allocation Process in Human–Robot Interaction – A Model for Research on ad hoc Task Allocation

Psychological Effects of the Allocation Process in Human–Robot Interaction – A Model for Research on ad hoc Task Allocation

The best task allocation process is to decide on one’s own: effects of the allocation agent in human–robot interaction on perceived work characteristics and satisfaction

Studying Navigation as a Form of Interaction: a Design Approach for Social Robot Navigation Methods

Contact Info

Product

Resources

About