Towards the Safety of Human-in-the-Loop Robotics: Challenges and Opportunities for Safety Assurance of Robotic Co-Workers

The success of the human-robot co-worker team in a flexible manufacturing environment where robots learn from demonstration heavily relies on the correct and safe operation of the robot. How this can be achieved is a challenge that requires addressing both technical as well as human-centric research questions. In this paper we discuss the state of the art in safety assurance, existing as well as emerging standards in this area, and the need for new approaches to safety assurance in the context of learning machines. We then focus on robotic learning from demonstration, the challenges these techniques pose to safety assurance and indicate opportunities to integrate safety considerations into algorithms "by design". Finally, from a human-centric perspective, we stipulate that, to achieve high levels of safety and ultimately trust, the robotic co-worker must meet the innate expectations of the humans it works with. It is our aim to stimulate a discussion focused on the safety aspects of human-in-the-loop robotics, and to foster multidisciplinary collaboration to address the research challenges identified

Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search

In principle, reinforcement learning and policy search methods can enable robots to learn highly complex and general skills that may allow them to function amid the complexity and diversity of the real world. However, training a policy that generalizes well across a wide range of real-world conditions requires far greater quantity and diversity of experience than is practical to collect with a single robot. Fortunately, it is possible for multiple robots to share their experience with one another, and thereby, learn a policy collectively. In this work, we explore distributed and asynchronous policy learning as a means to achieve generalization and improved training times on challenging, real-world manipulation tasks. We propose a distributed and asynchronous version of Guided Policy Search and use it to demonstrate collective policy learning on a vision-based door opening task using four robots. We show that it achieves better generalization, utilization, and training times than the single robot alternative.Comment: Submitted to the IEEE International Conference on Robotics and Automation 201

CORBYS cognitive control architecture for robotic follower

In this paper the novel generic cognitive robot control architecture CORBYS is presented. The objective of the CORBYS architecture is the integration of high-level cognitive modules to support robot functioning in dynamic environments including interacting with humans. This paper presents the preliminary integration of the CORBYS architecture to support a robotic follower. Experimental results on high-level empowerment-based trajectory planning have demonstrated the effectiveness of ROS-based communication between distributed modules developed in a multi-site research environment as typical for distributed collaborative projects such as CORBYS

Information-theoretic measures as a generic approach to human-robot interaction : Application in CORBYS project

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/AuthorThe objective of the CORBYS project is to design and implement a robot control architecture that allows the integration of high-level cognitive control modules, such as a semantically-driven self-awareness module and a cognitive framework for anticipation of, and synergy with, human behaviour based on biologically-inspired information-theoretic principles. CORBYS aims to provide a generic control architecture to benefit a wide range of applications where robots work in synergy with humans, ranging from mobile robots such as robotic followers to gait rehabilitation robots. The behaviour of the two demonstrators, used for validating this architecture, will each be driven by a combination of task specific algorithms and generic cognitive algorithms. In this paper we focus on the generic algorithms based on information theoryFinal Accepted Versio

Hospital robot at work: something alien or an intelligent colleague?

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Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a human viewer or counterpart present, a system will automatically be interpreted within context, style of movement, and form factor by human beings as animate elements of their environment. The interpretation by this human counterpart is critical to the success of the system's integration: knobs on the system need to make sense to a human counterpart; an artificial agent should have a way of notifying a human counterpart of a change in system state, possibly through motion profiles; and the motion of a human counterpart may have important contextual clues for task completion. Thus, professional choreographers, dance practitioners, and movement analysts are critical to research in robotics. They have design methods for movement that align with human audience perception, can identify simplified features of movement for human-robot interaction goals, and have detailed knowledge of the capacity of human movement. This article provides approaches employed by one research lab, specific impacts on technical and artistic projects within, and principles that may guide future such work. The background section reports on choreography, somatic perspectives, improvisation, the Laban/Bartenieff Movement System, and robotics. From this context methods including embodied exercises, writing prompts, and community building activities have been developed to facilitate interdisciplinary research. The results of this work is presented as an overview of a smattering of projects in areas like high-level motion planning, software development for rapid prototyping of movement, artistic output, and user studies that help understand how people interpret movement. Finally, guiding principles for other groups to adopt are posited.Comment: Under review at MDPI Arts Special Issue "The Machine as Artist (for the 21st Century)" http://www.mdpi.com/journal/arts/special_issues/Machine_Artis

Human-automation collaboration in manufacturing: identifying key implementation factors

Human-automation collaboration refers to the concept of human operators and intelligent automation working together interactively within the same workspace without conventional physical separation. This concept has commanded significant attention in manufacturing because of the potential applications, such as the installation of large sub-assemblies. However, the key human factors relevant to human-automation collaboration have not yet been fully investigated. To maximise effective implementation and reduce development costs for future projects these factors need to be examined. In this paper, a collection of human factors likely to influence human-automation collaboration are identified from current literature. To test the validity of these and explore further factors associated with implementation success, different types of production processes in terms of stage of maturity are being explored via industrial case studies from the project’s stakeholders. Data was collected through a series of semi-structured interviews with shop floor operators, engineers, system designers and management personnel

Dynamic Graphical Signage Improves Response Time and Decreases Negative Attitudes towards Robots in Human-Robot Co-working

Collaborative robots, or ‘co-bots’, are a transformational technology that bridge traditionally segregated manual and automated manufacturing processes. However, to realize its full potential, human operators need confidence in robotic co-worker technologies and their capabilities. In this experiment we investigate the impact of screen-based dynamic instructional signage on 39 participants from a manufacturing assembly line. The results provide evidence that dynamic signage helps to improve response time for the experimental group with task-relevant signage compared to the control group with no signage. Furthermore, the experimental group’s negative attitudes towards robots decreased significantly with increasing accuracy on the task