Methods for Expressing Robot Intent for Human–Robot Collaboration in Shared Workspaces

Human–robot collaboration is becoming increasingly common in factories around the world; accordingly, we need to improve the interaction experiences between humans and robots working in these spaces. In this article, we report on a user study that investigated methods for providing information to a person about a robot’s intent to move when working together in a shared workspace through signals provided by the robot. In this case, the workspace was the surface of a tabletop. Our study tested the effectiveness of three motion-based and three light-based intent signals as well as the overall level of comfort participants felt while working with the robot to sort colored blocks on the tabletop. Although not significant, our findings suggest that the light signal located closest to the workspace—an LED bracelet located closest to the robot’s end effector—was the most noticeable and least confusing to participants. These findings can be leveraged to support human–robot collaborations in shared spaces.

The Difference Between Legal Control and Material Control - Coordination of Access Rights in Shared Workspaces

Research purpose. Modern work is increasingly taking place in temporary workgroups embedded in decentralized work environments that transcend organizational boundaries. The first implementations of the shared workspace idea emerged in the 1990s in the CSCW research area and are now firmly integrated into the working world with systems such as Google Drive, OneDrive or Dropbox. However, when it comes to accessing documents, problems arise in terms of coordinating access to documents. Who can access the documents, modify them, and upload them back to the shared workspace? It should be noted that concurrent changes can lead to inconsistencies. Furthermore, incorrect changes to the content of documents can have economic and legal consequences. Who is responsible for this? Strict access control can avoid this problem if necessary. However, it contradicts the approach of agile cooperation, which benefits, among other things, from access to documents that is not restricted in terms of time and place. Design / Methodology / Approach. The article proposes a semantic approach for access coordination of shared workspaces. Its basis is the legal distinction between the levels of legal control (owner) and material control (possessor). The owner of an object has the right and the duty to allow the other participants of the shared workspace to access it, i.e., to have material control. This is done through an agreement between the owner and the possessor, which specifies the conditions of material control. In addition to coordinating access, the owner is also responsible for arbitrating in case of conflict and deciding which changes are valid and which are not. Findings. Transferring the distinction between owner and possessor leads to three possible classes of conflicts: Ownership vs ownership, ownership vs possession, and possession vs possession. Conflict schemes within these classes of conflict are analyzed in detail. On the one hand, it is possible to use strict, conflict-avoiding settings, but this tends to limit cooperation. On the other hand, greater cooperation agility can be enabled if the owner situationally controls access or if the owner has preset flexible response tactics in case a conflict arises. A closer look at possible conflict classes shows that it is necessary to adapt the legal concepts of owner and possessor to the cooperation situation. Originality / Value / Practical implications. The concept of the legal distinction between owner and possessor has not yet been applied to the domain of access coordination in shared workspaces. This approach can introduce the previously missing semantics for access coordination, at least on an informal basis. It also improves participants’ awareness of the context of cooperation.

The Shared-Workspace Framework for Dialogue and Other Cooperative Joint Activities

We present a theory of dialogue as a form of cooperative joint activity. Dialogue is treated as a system involving two interlocutors and a shared workspace that contains their contributions and relevant non-linguistic context. The interlocutors construct shared plans and use them to “post” contributions to the workspace, to comprehend joint contributions, and to distribute control of the dialogue between them. A fundamental part of this process is to simulate their partner’s contributions and to use it to predict the upcoming state of the shared workspace. As a consequence, they align their linguistic representations and their representations of the situation and of the “games” underlying successful communication. The shared workspace is a highly limited resource, and the interlocutors use their aligned representations to say just enough and to speak in good time. We describe how dialogue and cooperative joint activity can be brought together in situated communication, and then sketch some implications of our account for human-like artificial systems.

Communication and Interaction between Humanoid Robots and Humans

This paper deals with future robots that will be developed to assist and/or partially replace human activities that would provide for humans very much and frequently needed general-types of repetitive services for their daily tasks and engagements. As indeed the very name of humanoid robots intensely suggests, these engagements despite being routinely self-understood by implication as necessities of daily life, their frequency and repetitiveness, alongside other necessities of distributed elements of an increasingly intelligent daily environment, impose the need for deployment of various kinds of robots. It is to be assumed that there will be middle grounds between different types of humanoid robots, depending on the strength of their field of application. Collaborative robots that are conceived and intended to work i.e., collaborate safely with humans in a joint and shared workspace will expand and develop and be applied in increasingly diverse functions and working environments. Nowadays, intelligent robots are of course widely feasible and also increasingly available, but needless to say, even in the long run they will and cannot surpass the people in their creativity, their ability to learn in their differentiation, and maybe not even manage to catch up with all human complex requirements and needs. People will understandably continue to have a firm grip on the main switch.

A Mixed-Perception Approach for Safe Human–Robot Collaboration in Industrial Automation

Digital-enabled manufacturing systems require a high level of automation for fast and low-cost production but should also present flexibility and adaptiveness to varying and dynamic conditions in their environment, including the presence of human beings; however, this presence of workers in the shared workspace with robots decreases the productivity, as the robot is not aware about the human position and intention, which leads to concerns about human safety. This issue is addressed in this work by designing a reliable safety monitoring system for collaborative robots (cobots). The main idea here is to significantly enhance safety using a combination of recognition of human actions using visual perception and at the same time interpreting physical human–robot contact by tactile perception. Two datasets containing contact and vision data are collected by using different volunteers. The action recognition system classifies human actions using the skeleton representation of the latter when entering the shared workspace and the contact detection system distinguishes between intentional and incidental interactions if physical contact between human and cobot takes place. Two different deep learning networks are used for human action recognition and contact detection, which in combination, are expected to lead to the enhancement of human safety and an increase in the level of cobot perception about human intentions. The results show a promising path for future AI-driven solutions in safe and productive human–robot collaboration (HRC) in industrial automation.

Human Cognition in Interaction With Robots: Taking the Robot’s Perspective Into Account

Objective The present study investigated whether and how different human–robot interactions in a physically shared workspace influenced human stimulus–response (SR) relationships. Background Human work is increasingly performed in interaction with advanced robots. Since human–robot interaction often takes place in physical proximity, it is crucial to investigate the effects of the robot on human cognition. Method In two experiments, we compared conditions in which humans interacted with a robot that they either remotely controlled or monitored under otherwise comparable conditions in the same shared workspace. The cognitive extent to which the participants took the robot’s perspective served as a dependent variable and was evaluated with a SR compatibility task. Results The results showed pronounced compatibility effects from the robot’s perspective when participants had to take the perspective of the robot during the task, but significantly reduced compatibility effects when human and robot did not interact. In both experiments, compatibility effects from the robot’s perspective resulted in statistically significant differences in response times and in error rates between compatible and incompatible conditions. Conclusion We concluded that SR relationships from the perspective of the robot need to be considered when designing shared workspaces that require users to take the perspective of the robot. Application The results indicate changed compatibility relationships when users share their workplace with an interacting robot and therefore have to take its perspective from time to time. The perspective-dependent processing times are expected to be accompanied by corresponding error rates, which might affect—for instance—safety and efficiency in a production process.