Les robots sont les futurs compagnons et équipiers de demain. Que ce soit pour aider les personnes âgées ou handicapées dans leurs vies de tous les jours ou pour réaliser des tâches répétitives ou dangereuses, les robots apparaîtront petit à petit dans notre environnement. Cependant, nous sommes encore loin d'un vrai robot autonome, qui agirait de manière naturelle, efficace et sécurisée avec l'homme. Afin de doter le robot de la capacité d'agir naturellement avec l'homme, il est important d'étudier dans un premier temps comment les hommes agissent entre eux. Cette thèse commence donc par un état de l'art sur l'action conjointe en psychologie et philosophie avant d'aborder la mise en application des principes tirés de cette étude à l'action conjointe homme-robot. Nous décrirons ensuite le module de supervision pour l'interaction homme-robot développé durant la thèse. Une partie des travaux présentés dans cette thèse porte sur la gestion de ce que l'on appelle un plan partagé. Ici un plan partagé est une séquence d'actions partiellement ordonnées à effectuer par l'homme et/ou le robot afin d'atteindre un but donné. Dans un premier temps, nous présenterons comment le robot estime l'état des connaissances des hommes avec qui il collabore concernant le plan partagé (appelées états mentaux) et les prend en compte pendant l'exécution du plan. Cela permet au robot de communiquer de manière pertinente sur les potentielles divergences entre ses croyances et celles des hommes. Puis, dans un second temps, nous présenterons l'abstraction de ces plan partagés et le report de certaines décisions. En effet, dans les précédents travaux, le robot prenait en avance toutes les décisions concernant le plan partagé (qui va effectuer quelle action, quels objets utiliser...) ce qui pouvait être contraignant et perçu comme non naturel par l'homme lors de l'exécution car cela pouvait lui imposer une solution par rapport à une autre. Ces travaux vise à permettre au robot d'identifier quelles décisions peuvent être reportées à l'exécution et de gérer leur résolutions suivant le comportement de l'homme afin d'obtenir un comportement du robot plus fluide et naturel. Le système complet de gestions des plan partagés à été évalué en simulation et en situation réelle lors d'une étude utilisateur. Par la suite, nous présenterons nos travaux portant sur la communication non-verbale nécessaire lors de de l'action conjointe homme-robot. Ces travaux sont ici focalisés sur l'usage de la tête du robot, cette dernière permettant de transmettre des informations concernant ce que fait le robot et ce qu'il comprend de ce que fait l'homme, ainsi que des signaux de coordination. Finalement, il sera présenté comment coupler planification et apprentissage afin de permettre au robot d'être plus efficace lors de sa prise de décision. L'idée, inspirée par des études de neurosciences, est de limiter l'utilisation de la planification (adaptée au contexte de l'interaction homme-robot mais coûteuse) en laissant la main au module d'apprentissage lorsque le robot se trouve en situation "connue". Les premiers résultats obtenus démontrent sur le principe l'efficacité de la solution proposée. / In the future, robots will become our companions and co-workers. They will gradually appear in our environment, to help elderly or disabled people or to perform repetitive or unsafe tasks. However, we are still far from a real autonomous robot, which would be able to act in a natural, efficient and secure manner with humans. To endow robots with the capacity to act naturally with human, it is important to study, first, how humans act together. Consequently, this manuscript starts with a state of the art on joint action in psychology and philosophy before presenting the implementation of the principles gained from this study to human-robot joint action. We will then describe the supervision module for human-robot interaction developed during the thesis. Part of the work presented in this manuscript concerns the management of what we call a shared plan. Here, a shared plan is a a partially ordered set of actions to be performed by humans and/or the robot for the purpose of achieving a given goal. First, we present how the robot estimates the beliefs of its humans partners concerning the shared plan (called mental states) and how it takes these mental states into account during shared plan execution. It allows it to be able to communicate in a clever way about the potential divergent beliefs between the robot and the humans knowledge. Second, we present the abstraction of the shared plans and the postponing of some decisions. Indeed, in previous works, the robot took all decisions at planning time (who should perform which action, which object to use…) which could be perceived as unnatural by the human during execution as it imposes a solution preferentially to any other. This work allows us to endow the robot with the capacity to identify which decisions can be postponed to execution time and to take the right decision according to the human behavior in order to get a fluent and natural robot behavior. The complete system of shared plans management has been evaluated in simulation and with real robots in the context of a user study. Thereafter, we present our work concerning the non-verbal communication needed for human-robot joint action. This work is here focused on how to manage the robot head, which allows to transmit information concerning what the robot's activity and what it understands of the human actions, as well as coordination signals. Finally, we present how to mix planning and learning in order to allow the robot to be more efficient during its decision process. The idea, inspired from neuroscience studies, is to limit the use of planning (which is adapted to the human-aware context but costly) by letting the learning module made the choices when the robot is in a "known" situation. The first obtained results demonstrate the potential interest of the proposed solution.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第17928号 / 情博第510号 / 新制||情||90(附属図書館) / 30748 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 奥乃 博, 教授 河原 達也, 教授 山本 章博 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

No description available.

No description available.

No description available.

A close collaboration between humans and robots is one approach to achieve flexible production flows and a high degree of automation at the same time. In human-robot collaboration, both entities work alongside each other in a fenceless, shared environment. These workstations combine human flexibility, tactile sense and intelligence with robotic speed, endurance, and accuracy. This leads to improved ergonomic working conditions for the operator, better quality and higher efficiency. However, the widespread adoption of human-robot collaboration is limited by the current safety legislation. Robots are powerful machines and without spatial separation to the operator the risks drastically increase. The technical specification ISO/TS 15066 serves as a guideline for collaborative operations and supplements the international standard ISO 10218 for industrial robots. Because ISO/TS 15066 represents the first draft for a coming standard, companies have to gain knowledge in applying ISO/TS 15066. Currently, the guideline prohibits a collision with the head in transient contact. In this thesis work, a safety system is designed which is in compliance with ISO/TS 15066 and where certified safety technologies are used. Four theoretical safety system designs with a laser scanner as a presence sensing device and a collaborative robot, the KUKA lbr iiwa, are proposed. The system either stops the robot motion, reduces the robot’s speed and then triggers a stop or only activates a stop after a collision between the robot and the human occurred. In system 3 the size of the stop zone is decreased by combining the speed and separation monitoring principle with the power- and force-limiting safeguarding mode. The safety zones are static and are calculated according to the protective separation distance in ISO/TS 15066. A risk assessment is performed to reduce all risks to an acceptable level and lead to the final safety system design after three iterations. As a proof of concept the final safety system design is implemented for a demonstrator in a laboratory environment at Scania. With a feasibility study, the implementation differences between theory and praxis for the four proposed designs are identified and a feasible safety system behavior is developed. The robot reaction is realized through the safety configuration of the robot. There three ESM states are defined to use the internal safety functions of the robot and to integrate the laser scanner signal. The laser scanner is connected as a digital input to the discrete safety interface of the robot controller. To sum up, this thesis work describes the safety system design with all implementation details. / Ett nära samarbete mellan människor och robotar är ett sätt att uppnå flexibla produktionsflöden och en hög grad av automatisering samtidigt. I människa-robotsamarbeten arbetar båda enheterna tillsammans med varandra i en gemensam miljö utan skyddsstaket. Dessa arbetsstationer kombinerar mänsklig flexibilitet, taktil känsla och intelligens med robothastighet, uthållighet och noggrannhet. Detta leder till förbättrade ergonomiska arbetsförhållanden för operatören, bättre kvalitet och högre effektivitet. Det breda antagandet av människarobotsamarbeten är emellertid begränsat av den nuvarande säkerhetslagstiftningen. Robotar är kraftfulla maskiner och utan rymdseparation till operatören riskerna drastiskt ökar. Den tekniska specifikationen ISO / TS 15066 fungerar som riktlinje för samverkan och kompletterar den internationella standarden ISO 10218 för industrirobotar. Eftersom ISO / TS 15066 representerar det första utkastet för en kommande standard, måste företagen få kunskap om att tillämpa ISO / TS 15066. För närvarande förbjuder riktlinjen en kollision med huvudet i övergående kontakt. I detta avhandlingar är ett säkerhetssystem utformat som överensstämmer med ISO / TS 15066 och där certifierad säkerhetsteknik används. Fyra teoretiska säkerhetssystemdesigner med en laserskanner som närvarosensor och en samarbetsrobot, KUKA lbr iiwa, föreslås. Systemet stoppar antingen robotrörelsen, reducerar robotens hastighet och triggar sedan ett stopp eller aktiverar bara ett stopp efter en kollision mellan roboten och människan inträffade. I system 3 minskas storleken på stoppzonen genom att kombinera hastighets- och separationsövervakningsprincipen med det kraft- och kraftbegränsande skyddsläget. Säkerhetszoner är statiska och beräknas enligt skyddsavståndet i ISO / TS 15066. En riskbedömning görs för att minska alla risker till en acceptabel nivå och leda till den slutliga säkerhetssystemdesignen efter tre iterationer. Som ett bevis på konceptet är den slutliga säkerhetssystemdesignen implementerad för en demonstrant i en laboratoriemiljö hos Scania. Genom en genomförbarhetsstudie identifieras implementeringsskillnaderna mellan teori och praxis för de fyra föreslagna mönster och ett genomförbart säkerhetssystem beteende utvecklas. Robotreaktionen realiseras genom robotens säkerhetskonfiguration. Där definieras tre ESM-tillstånd för att använda robotens interna säkerhetsfunktioner och för att integrera laserscannersignalen. Laserskannern är ansluten som en digital ingång till robotkontrollens diskreta säkerhetsgränssnitt. Sammanfattningsvis beskriver detta avhandlingar säkerhetssystemdesignen med alla implementeringsdetaljer.

Bio-inspired swarming behaviors provide an effective decentralized way of coordinating robot teams. However, as robot swarms increase in size, bandwidth and time constraints limit the number of agents a human can communicate with and control. To facilitate scalable human interaction with large robot swarms it is desirable to monitor and influence the collective behavior of the entire swarm through limited interactions with a small subset of agents. However, it is also desirable to avoid situations where a small number of agent failures can adversely affect the collective behavior of the swarm. We present a bio-inspired model of swarming that exhibits distinct collective behaviors and affords limited human interaction to estimate and influence these collective behaviors. Using a simple naive Bayes classifier, we show that the global behavior of a swarm can be detected with high accuracy by sampling local information from a small number of agents. We also show that adding a bio-inspired form of quorum sensing to a swarm increases the scalability of human-swarm interactions and also provides an adjustable threshold on the swarm's vulnerability to agent failures.

In this thesis we propose methods and metrics for human interaction with bio-inspired robot teams. We refine the concept of a stakeholder and demonstrate how a human can use stakeholders to lead a swarm as well as switch the swarm between different collective behaviors. We extend the human interaction metrics of interaction time and interaction effort presented in [1] to swarm systems and introduce the concept of interaction effort. These metrics allow us to understand how well the system performs under human influence. We employ systems theory to estimate these metrics, which is useful because this can be done without performing user studies.

When working with a complex AI or robotics system in a specific application, users often need to incorporate their special domain knowledge into the autonomous system. Such needs call for the ability to manage autonomy. However, managing autonomy can be a difficult task because the internal mechanisms and algorithms of the autonomous components may be beyond the users' understanding. We propose an approach where users manage autonomy indirectly by managing information provided to the intelligent system hierarchically at three different temporal scales: strategic, between-episodes, and within-episode. Information management tools at multiple temporal scales allow users to influence the autonomous behaviors of the system without the need for tedious direct/manual control. Information fed to the system can be in the forms of areas of focus, representations of task difficulty, and the amount of autonomy desired. We apply this approach to using an Unmanned Aerial Vehicle (UAV) to support Wilderness Search and Rescue (WiSAR). This dissertation presents autonomous algorithms/components and autonomy management tools/interfaces we designed at different temporal scales, and provides evidence that the approach improves the performance of the human-robot team and the experience of the human partner.

When humans and remote robots work together on a team, the robots always interact with a human supervisor, even if the interaction is limited to occasional reports. Distracting a human with robotic interactions doesn't pose a problem so long as the inclusion of robots increases the team's overall effectiveness. Unfortunately, increasing the supervisor's cognitive load may decrease the team's sustainable performance to the point where robotic agents are more a liability than an asset. Present approaches resolve this problem with adaptive autonomy, where a robot changes its level of autonomy based on the supervisor's cognitive load. This thesis proposes to augment adaptive autonomy by modeling temporal latency and using this model to optimally select the temporal interval between when a supervisor is informed of a pending change and when the robot makes the change. This enables robotic team members to time their actions in response to the supervisor's cognitive load. The hypothesis is confirmed in a user-study where 26 participants interacted with a simulated search-and-rescue scenario.