Détection et résolution de conflits d'autorité dans un système homme-robot

Dans le cadre de missions réalisées conjointement par un agent artificiel et un agent humain, nous présentons un contrôleur de la dynamique de l'autorité, fondé sur un graphe de dépendances entre ressources contrôlables par les deux agents, dont l'objectif est d'adapter le comportement de l'agent artificiel ou de l'agent humain en cas de conflit d'autorité sur ces ressources. Nous définissons l'autorité relative de deux agents par rapport au contrôle d'une ressource, ainsi que la notion de conflit d'autorité : une première expérience nous montre en effet que le conflit constitue un déclencheur pertinent pour une redistribution de l'autorité entre agents. Une seconde expérience montre qu'au-delà de la modification du comportement de l'agent artificiel, il est effectivement possible d'adapter le comportement de l'opérateur humain en vue de résoudre un tel conflit

An assigned responsibility system for robotic teleoperation control

This paper proposes an architecture that explores a gap in the spectrum of existing strategies for robot control mode switching in adjustable autonomy. In situations where the environment is reasonably known and/or predictable, pre-planning these control changes could relieve robot operators of the additional task of deciding when and how to switch. Such a strategy provides a clear division of labour between the automation and the human operator(s) before the job even begins, allowing for individual responsibilities to be known ahead of time, limiting confusion and allowing rest breaks to be planned. Assigned Responsibility is a new form of adjustable autonomy-based teleoperation that allows the selective inclusion of automated control elements at key stages of a robot operation plan’s execution. Progression through these stages is controlled by automatic goal accomplishment tracking. An implementation is evaluated through engineering tests and a usability study, demonstrating the viability of this approach and offering insight into its potential applications

Designing for dynamic task allocation

Future platforms are envisioned in which human-machine teams are able to share and trade tasks as demands in situations change. It seems that human-machine coordination has not received the attention it deserves by past and present approaches to task allocation. In this paper a simple way to make coordination requirements explicit is proposed and for dynamic task allocation a dual-route approach is suggested. Advantages of adaptable automation, in which the human adjusts the way tasks are divided and shared, are complemented with those of adaptive automation, in which the machine allocates tasks. To be able to support design for dynamic task allocation, a theory about task allocation decision making by means of modeling of trust is proposed. It is suggested that dynamic task allocation is improved when information about situational abilities of agents is provided and the cost of observing and re-directing agents is reduced

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

The Immersive Education Laboratory: understanding affordances, structuring experiences, and creating constructivist, collaborative processes, in mixed-reality smart environments

In this paper we describe how the iClassroom and other technologies are providing the testbed through which we are able to design, develop, and research future intelligent environments. We describe the process of distinguishing between the technical and pedagogical aspects of immersive learning environments, while simultaneously considering both in the redefinition of effective intelligent learning spaces. This paper describes how our laboratory is working on specific projects that increase our understanding of the distinct advantages of technical design elements, like immersive visual displays, and pedagogical design elements that need to be in place as we go through the process of structuring learning situations that create constructivist, collaborative experiences. We describe specific technologies and their design across these multiple dimensions and the ways in which they are helping us better understand how to maximize technological affordances for increased positive learning outcomes. Finally, through this design research process, as we begin to better understand the affordances and iteratively create design guidelines, our hope is that eventually a prescriptive framework emerges that informs both the practice of embedded technology development and the deliberate incorporation of technical attributes into both the educational space and the pedagogy through which students learn

Social Order and Adaptability in Animal and Human Cultures as Analogues for Agent Communities: Toward a Policy-Based Approach

Abstract. In this paper we discuss some of the ways social order is maintained in animal and human realms, with the goal of enriching our thinking about mechanisms that might be employed in developing similar means of ordering communities of agents. We present examples from our current work in human-agent teamwork, and we speculate about some new directions this kind of research might take. Since communities also need to change over time to cope with changing circumstances, we also speculate on means that regulatory bodies can use to adapt. 1

Human-robot Interaction For Multi-robot Systems

Designing an effective human-robot interaction paradigm is particularly important for complex tasks such as multi-robot manipulation that require the human and robot to work together in a tightly coupled fashion. Although increasing the number of robots can expand the area that the robots can cover within a bounded period of time, a poor human-robot interface will ultimately compromise the performance of the team of robots. However, introducing a human operator to the team of robots, does not automatically improve performance due to the difficulty of teleoperating mobile robots with manipulators. The human operator’s concentration is divided not only among multiple robots but also between controlling each robot’s base and arm. This complexity substantially increases the potential neglect time, since the operator’s inability to effectively attend to each robot during a critical phase of the task leads to a significant degradation in task performance. There are several proven paradigms for increasing the efficacy of human-robot interaction: 1) multimodal interfaces in which the user controls the robots using voice and gesture; 2) configurable interfaces which allow the user to create new commands by demonstrating them; 3) adaptive interfaces which reduce the operator’s workload as necessary through increasing robot autonomy. This dissertation presents an evaluation of the relative benefits of different types of user interfaces for multi-robot systems composed of robots with wheeled bases and three degree of freedom arms. It describes a design for constructing low-cost multi-robot manipulation systems from off the shelf parts. User expertise was measured along three axes (navigation, manipulation, and coordination), and participants who performed above threshold on two out of three dimensions on a calibration task were rated as expert. Our experiments reveal that the relative expertise of the user was the key determinant of the best performing interface paradigm for that user, indicating that good user modiii eling is essential for designing a human-robot interaction system that will be used for an extended period of time. The contributions of the dissertation include: 1) a model for detecting operator distraction from robot motion trajectories; 2) adjustable autonomy paradigms for reducing operator workload; 3) a method for creating coordinated multi-robot behaviors from demonstrations with a single robot; 4) a user modeling approach for identifying expert-novice differences from short teleoperation traces