Promise

Proceedings 2007 IEEE International Conference on Robotics and Automation, 2007

This work presents the evaluation of two mission specification and task allocation architectures. These architectures, described in part 1 of this paper, present novel means with which to integrate a case-based reasoning (CBR) mission planner with contract net protocol (CNP) based task allocation. In the first design, the CBR and runtime-CNP architecture, the case-based mission planner generates mission plans that support necessary behaviors for CNP-based task allocation and execution. In the second design, the CBR and premission-CNP architecture, task allocation takes place during mission specification. The results of an empirical evaluation of the CBR and runtime-CNP across three naval scenarios is described. Finally, we briefly describe an earlier usability evaluation of the CBR and premission-CNP architecture using goals, operators, methods, and selection rules modeling.

2021

Text-based programming remains a challenge to novice programmers in\ua0all programming domains including robotics. The use of robots is gainingconsiderable traction in several domains since robots are capable of assisting\ua0humans in repetitive and hazardous tasks. In the near future, robots willbe used in tasks of everyday life in homes, hotels, airports, museums, etc.\ua0However, robotic missions have been either predefined or programmed usinglow-level APIs, making mission specification task-specific and error-prone.\ua0To harness the full potential of robots, it must be possible to define missionsfor specific applications domains as needed. The specification of missions of\ua0robotic applications should be performed via easy-to-use, accessible ways, and\ua0at the same time, be accurate, and unambiguous. Simplicity and flexibility in\ua0programming such robots are important, since end-users come from diverse\ua0domains, not necessarily with suffcient programming knowledge.The mai...

2021

For an effective deployment in manufacturing, Col- laborative Robots should be capable of adapting their behavior to the state of the environment and to keep the user safe and engaged during the interaction. Artificial Intelligence (AI) enables robots to autonomously operate understanding the environment, planning their tasks and acting to achieve some given goals. However, the effective deployment of AI technologies in real industrial environments is not straightforward. There is a need for engineering tools facilitating communication and interaction between AI engineers and Domain experts. This paper presents a novel software tool, called TENANT (Tool fostEriNg Ai plaNning in roboTics) whose aim is to facilitate the use of AI planning technologies by providing domain experts like e.g., production engineers, with a graphical software framework to synthesize AI planning models abstracting from syntactic features of the underlying planning formalism. This work was presented during th...

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020

Robots that support humans by performing useful tasks (a.k.a., service robots) are booming worldwide. In contrast to industrial robots, the development of service robots comes with severe software engineering challenges, since they require high levels of robustness and autonomy to operate in highly heterogeneous environments. As a domain with critical safety implications, service robotics faces a need for sound software development practices. In this paper, we present the first large-scale empirical study to assess the state of the art and practice of robotics software engineering. We conducted 18 semi-structured interviews with industrial practitioners working in 15 companies from 9 different countries and a survey with 156 respondents from 26 countries from the robotics domain. Our results provide a comprehensive picture of (i) the practices applied by robotics industrial and academic practitioners, including processes, paradigms, languages, tools, frameworks, and reuse practices, (ii) the distinguishing characteristics of robotics software engineering, and (iii) recurrent challenges usually faced, together with adopted solutions. The paper concludes by discussing observations, derived hypotheses, and proposed actions for researchers and practitioners. CCS CONCEPTS • Computer systems organization → Robotics; • Software and its engineering;

Studies in Computational Intelligence, 2015

Building distributed applications for cooperative service robots systems is a very challenging task from software engineering perspective. Indeed, apart from the complexity of designing software components for the control of a single autonomous robot, cooperative multi-robot systems require additional care in the design of software components to ensure communication and coordination between the robotic agents. This chapter proposes COROS, a new multi-agent software architecture for cooperative and autonomous service robots with the objective to make easier the design and development of multi-robot applications. We present a high-level conceptual architecture for multi-agent robotics systems that represents a generic framework for cooperative multi-robot applications. Furthermore, we present an instantiation of this generic architecture with an implementation software architecture on top of the Robotic Operating System (ROS) middleware. The proposed concrete software architecture follows a component-based approach to ensure modularity, software reuse, extensibility and scalability of the multi-robot operational software. In addition, one major added value of our architecture is that it provides a tangible solution to supporting multi-robot software development for the ROS middleware, as ROS was originally designed for single-robot applications. We also demonstrate a sample of real-world case studies of cooperative and autonomous service robots applications in an office-like environment, including discovery and courier delivery applications.

IEEE Transactions on Human-Machine Systems

Collaborative robots (cobots) are being applied in areas such as healthcare, rehabilitation, agriculture and logistics, beyond the typical manufacturing setting. This is leading to a marked increase in the number of cobot stakeholders with little or no experience in traditional safety engineering. Considering the importance of human safety in collaborative robotic applications, this is currently proving to be a barrier to more widespread cobot usage. A web-based Toolkit that targets cobot end-users and manufacturers with varying levels of safety expertise was developed, helping them to understand how to consider the safety of their cobot applications. In this work, we will provide an overview of the state of the art for ensuring cobot safety, highlight the support provided by the "COVR Toolkit" and introduce three examples

Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers, 1999

Most robot software architectures focus on the problem of imitating human intelligence and thus typically refer to a single robot perceiving, navigating and acting in the environment. However, the rapid progress of communication technology has modified this reference scenario, offering the possibility of "distributing" the intelligent activity on a network of robots, computers and other general sensing and actuating devices. This allows the robot to merge with the environment it operates in and, moreover, different robots may cooperate as a single entity in order to carry out a specific task more efficiently. This paper tackles this "extended" problem, presenting ETHNOS-II, a programming environment for the design of a system composed of different robots integrated with the environment they operate in. ETHNOS-II provides support from two main point of views: from the software engineering perspective it provides support for platform independence, software integration and re-use, computation distribution; from the runtime perspective it provides support for real-time execution and event handling, inter-robot communication, and intra-robot resource allocation.

arXiv (Cornell University), 2023

RPA (Robotic Process Automation) helps automate repetitive tasks performed by users, often across different software solutions. Regardless of the RPA tool chosen, the key problem in automation is analyzing the steps of these tasks. This is usually done by an analyst with the possible participation of the person responsible for the given activity. However, currently there exists no one-size-fits-all description language, which would allow to record, process, and easily automate steps of specific tasks. Every RPA solution uses a different notation, which is not easily human-readable, editable, and which cannot be applied to a different automation platform. Therefore, in this paper, we propose a new eXtensible Robotic Language (XRL) that can be understood by both programmers and non-programmers to automate repetitive business processes.

2021

Temporal flexible planning enables Collaborative Robots to autonomously operate understanding the environment, dynamically planning their tasks and acting to achieve some given goals. The introduction of tools to facilitate the integration of Planning and Robotics is crucial but entails different kind of expertise to address a wide variety of control issues and the design of integrated solutions. Namely, Domain experts, Planning specialists and Roboticists are to configure a set of proper control solutions to enable an effective and safe production. This paper presents a novel software tool, called TENANT (Tool fostEriNg Ai plaNning in roboTics), that facilitates domain experts in defining goals, tasks and a set operational constraints enabling the automatic generation of planning models for robot control. TENANT is validated in an industrial collaborative scenario derived from a EU-funded research project demonstrating its effectiveness in generating automated planning models to co...

IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2004

MissionLab is a mission specification system that implements a hybrid deliberative and reactive control architecture for autonomous mobile robots. The user creates and executes the robot mission plans through its graphical user interface. As robot deployments become more common in highly stressful situations, such as in dealing with explosives or biohazards, the usability of their mission specification system becomes critical. To address this need, a mission-planning "wizard" has been recently integrated into MissionLab. By retrieving and adapting past successful mission plans stored in its database, this new feature is designed to simplify the user's planning process. The latest formal usability experiments, reported in this paper, testing for usability improvements in terms of speed of the mission planning process, accuracy of the produced mission plans, and ease of use is conducted. This paper introduces the mission-planning wizard, describes the usability experiments (including design), and discusses the results in detail.