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

Formal verification of an autonomous personal robotic assistant

Human–robot teams are likely to be used in a variety of situations wherever humans require the assistance of robotic systems. Obvious examples include healthcare and manufacturing, in which people need the assistance of machines to perform key tasks. It is essential for robots working in close proximity to people to be both safe and trustworthy. In this paper we examine formal verification of a high-level planner/scheduler for autonomous personal robotic assistants such as Care-O-bot ™ . We describe how a model of Care-O-bot and its environment was developed using Brahms, a multiagent workflow language. Formal verification was then carried out by translating this to the input language of an existing model checker. Finally we present some formal verification results and describe how these could be complemented by simulation-based testing and realworld end-user validation in order to increase the practical and perceived safety and trustworthiness of robotic assistants

A New Prototype for Intelligent Visual Fraud Detection in Agent-Based Auditing Framework

While US. Sarbanes Oxley act has been viewed by most as an onerous and expensive requirement; it is having a positive impact on driving appropriate levels of investment in IT security, controls, and transactional systems. This paper introduces a new secure solution for auditing and accounting based on artificial intelligence technology. These days, security is a big issue among regulatory firms. Big companies are concerned about their data to be disseminated to their competitors; this high risk prevents them to provide full information to the regulatory firms. This solution not only significantly reduces the risk of unauthorized access to the company’s information but also facilitate a framework for controlling the flow of disseminating information in a risk free method. Managing security is performed by a network of mobile agents in a pyramid structure among regulatory organization like securities and exchanges commissions, stock exchanges in top of this pyramid to the companies in the button. Because of security considerations, our strategy is to delegate all fraud detection algorithms to Intelligent Mobile Auditing Agent and web service undertake all inter communicational activity. Web services can follow auditing actives in predefined framework and they can act based on permitted security allowance to auditors. The current solution is designed based on Java-based mobile agents. Such design reaps strong mobility and security benefits. This new prototyped solution could be a framework for strengthening security for future development in this area. An insider trading case study is used to demonstrate and evaluate the approach