In recent years there has been a concerted effort to address many of the safety issues associated with physical human–robot interaction (pHRI). However, a number of challenges remain. For personal robots, and those intended to operate in unstructured environments, the problem of safety is compounded. In this paper we argue that traditional system design techniques fail to capture the complexities associated with dynamic environments. We present an overview of our safety-driven control system and its implementation methodology. The methodology builds on traditional functional hazard analysis, with the addition of processes aimed at improving the safety of autonomous personal robots. This will be achieved with the use of a safety system developed during the hazard analysis stage. This safety system, called the safety protection system, will initially be used to verify that safety constraints, identified during hazard analysis, have been implemented appropriately. Subsequently it will serve as a high-level safety enforcer, by governing the actions of the robot and preventing the control layer from performing unsafe operations. To demonstrate the effectiveness of the design, a series of experiments have been conducted using a MobileRobots PeopleBot. Finally, results are presented demonstrating how faults injected into a controller can be consistently identified and handled by the safety protection system.
Abstract-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 outline 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.
Graduate education can be utilized by working professionals as an advancement to their careers. This paper presents the results of a Delphi survey sent to 31experts in the construction industry. A survey questionnaire was developed to ask the participants about their perceptions of the relevance of the current graduate-level construction management courses in developing senior-level construction managers. A curriculum analysis of 34 graduate CM programs in the United States was conducted. The resulting data from the curriculum analysis is utilized in developing the survey questionnaire. The study is part of a larger research Delphi study that aimed at identifying the Knowledge, Skills, and Abilities required for senior-level managers in the construction industry. Two phases of the survey were sent to participants in this Delphi study. The results of the study indicate that the current graduate programs in construction management across the United States of America are not adequately focused on developing senior-level construction managers.
A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP url' above for details on accessing the published version and note that access may require a subscription. Abstract. This paper presents a novel approach for designing robotic systems. The methodology aims to build on traditional functional hazard analysis, with the addition of processes aimed to improve the safety of autonomous personal robots. This will be achieved with the use of a safety protection system, developed during the hazard analysis stage. This protection system will serve dual purposes. Firstly, it will be used to verify that safety constraints, identified during hazard analysis, have been implemented appropriately. Secondly, it will serve as a high-level safety enforcer, by governing the actions of the robot, preventing the control system from performing unsafe operations. This research is particularly focused on the safety of human-robot interaction.
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