Programming Robots for Activities of Everyday Life

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 main objective of this licentiate thesis is to empirically understand the\ua0state-of-the-art in languages and tools used for specifying robot missions byend-users. The findings will form the basis for interventions in developing\ua0future languages for end-user robot programming.During the empirical study, DSLs for robot mission specification were\ua0analyzed through published literature, their websites, user manuals, samplemissions and using the languages to specify missions for supported robots.After extracting data from 30 environments, 133 features were identified.\ua0A feature matrix mapping the features to the environments was developedwith a feature model for robotic mission specification DSLs.Our results show that most end-user facing environments exist in the\ua0education domain for teaching novice programmers and STEM subjects. Mostof the visual languages are developed using Blockly and Scratch libraries.\ua0The end-user domain abstraction needs more work since most of the visualenvironments abstract robotic and programming language concepts but not\ua0end-user concepts. In future works, it is important to focus on the development\ua0of reusable libraries for end-user concepts; and further, explore how end-user\ua0facing environments can be adapted for novice programmers to learn\ua0general programming skills and robot programming in low resource settings\ua0in developing countries, like Uganda

A survey on the design space of end-user-oriented languages for specifying robotic missions

Mobile robots are becoming increasingly important in society. Fulfilling complex missions in different contexts and environments,robots are promising instruments to support our everyday live. As such, the task of defining the robot’s missionis moving from professional developers and roboticists to the end-users. However, with the current state-of-the-art, definingmissions is non-trivial and typically requires dedicated programming skills. Since end-users usually lack such skills, manycommercial robots are nowadays equipped with environments and domain-specific languages tailored for end-users. As such,the software support for defining missions is becoming an increasingly relevant criterion when buying or choosing robots.Improving these environments and languages for specifying missions toward simplicity and flexibility is crucial. To this end,we need to improve our empirical understanding of the current state-of-the-art of such languages and their environments. Inthis paper, we contribute in this direction. We present a survey of 30 mission specification environments for mobile robots thatcome with a visual and end-user-oriented language. We explore the design space of these languages and their environments,identify their concepts, and organize them as features in a feature model. We believe that our results are valuable to practitionersand researchers designing the next generation of mission specification languages in the vibrant domain of mobilerobots

EUD-MARS: End-User Development of Model-Driven Adaptive Robotics Software Systems

Empowering end-users to program robots is becoming more significant. Introducing software engineering principles into end-user programming could improve the quality of the developed software applications. For example, model-driven development improves technology independence and adaptive systems act upon changes in their context of use. However, end-users need to apply such principles in a non-daunting manner and without incurring a steep learning curve. This paper presents EUD-MARS that aims to provide end-users with a simple approach for developing model-driven adaptive robotics software. End-users include people like hobbyists and students who are not professional programmers but are interested in programming robots. EUD-MARS supports robots like hobby drones and educational humanoids that are available for end-users. It offers a tool for software developers and another one for end-users. We evaluated EUD-MARS from three perspectives. First, we used EUD-MARS to program different types of robots and assessed its visual programming language against existing design principles. Second, we asked software developers to use EUD-MARS to configure robots and obtained their feedback on strengths and points for improvement. Third, we observed how end-users explain and develop EUD-MARS programs, and obtained their feedback mainly on understandability, ease of programming, and desirability. These evaluations yielded positive indications of EUD-MARS

A generated property specification language for resilient multirobot missions

The use of robots is gaining considerable traction in several domains, since they are capable of assisting and replacing humans for everyday tasks. To harvest the full potential of robots, it must be possible to define missions for robots that are domain-specific, resilient, and collaborative. Currently, robot vendors provide low-level APIs to program such missions, making mission definition a task-specific and error-prone activity. There is a need for quick definition of new missions, by users that lack programming expertise, such as farmers and emergency workers. In this paper, we extend the existing FLYAQ platform to support the high-level specification of adaptive and highly-resilient missions. We present an extensible specification language that allows users to declaratively specify domain-specific constraints as properties of missions, thus complementing the existing FLYAQ mission language. This permits to move at runtime, the actual generation of low-level operations to satisfy the declaratively specified mission. We show how this specification language can be automatically generated from a domain-specific FLYAQ mission language by using the generative ProMoBox approach. Next, we show how mission goals are achieved taking mission properties into account, and how missions may change due to unexpected circumstances

Behavior Trees and State Machines in Robotics Applications

Autonomous robots combine skills to form increasingly complex behaviors, called missions. While skills are often programmed at a relatively low abstraction level, their coordination is architecturally separated and often expressed in higher-level languages or frameworks. State machines have been the go-to language to model behavior for decades, but recently, behavior trees have gained attention among roboticists. Originally designed to model autonomous actors in computer games, behavior trees offer an extensible tree-based representation of missions and are claimed to support modular design and code reuse. Although several implementations of behavior trees are in use, little is known about their usage and scope in the real world. How do concepts offered by behavior trees relate to traditional languages, such as state machines? How are concepts in behavior trees and state machines used in actual applications? This paper is a study of the key language concepts in behavior trees as realized in domain-specific languages (DSLs), internal and external DSLs offered as libraries, and their use in open-source robotic applications supported by the Robot Operating System (ROS). We analyze behavior-tree DSLs and compare them to the standard language for behavior models in robotics: state machines. We identify DSLs for both behavior-modeling languages, and we analyze five in-depth. We mine open-source repositories for robotic applications that use the analyzed DSLs and analyze their usage. We identify similarities between behavior trees and state machines in terms of language design and the concepts offered to accommodate the needs of the robotics domain. We observed that the usage of behavior-tree DSLs in open-source projects is increasing rapidly. We observed similar usage patterns at model structure and at code reuse in the behavior-tree and state-machine models within the mined open-source projects. We contribute all extracted models as a dataset, hoping to inspire the community to use and further develop behavior trees, associated tools, and analysis techniques