Robotic system testing with AMSA framework

2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), 2013

Models are used in control domains for early validation of system properties, using simulation or formal verification, and for the automatic generation of a software implementation. We propose an approach in which a functional model of the controls is matched to a model of the execution platform through an intermediate mapping model, that represents the software tasks and communication messages. The functional model is (partly) developed in Simulink and code is generated for each subsystem. Next, an abstract view of the functional model is imported in SysML. Using SysML, a model of the execution platform is created, and an implementation of the subsystems as a set of tasks and messages is defined and evaluated. The M2T Acceleo tool processes the mapping model and generates the Orocos-compliant task code executing the C/C++ functions generated from Simulink, and the inter-task communication. This paper outlines the proposed flow and provides the description of a robotic car testbench used to show the application of the methodology. The testbench has enough functional complexity and a distributed implementation to justify the creation of architecture models, while requiring a moderate cost and effort for its construction by the interested researchers.

The aim of this paper is to convey our experience using the ESA's 3DROV planetary rover simulator as a visualization and validation tool through a dynamic analysis on the performance of an advanced autonomous control architecture: a power-aware, model-based control system with applications in rover-based mission operations which integrates advanced constraint-based reasoning within a flexible control execution management process. The analysis focuses on the validation of the main capabilities of the control system through three representative simulation examples executed upon an integrated testbed platform with 3DROV. More concretely, the target of the simulation tests is twofold: (i) to demonstrate the main capabilities of the controller; and (ii) to evaluate its performance on overcoming specific anomalous situations which might threaten the whole mission execution success.

SDL 2017: Model-Driven Engineering for Future Internet, 2017

Testing is a common technique to assess quality of systems. Regression testing comes into view, when changes are introduced to the system under test and re-running all tests is not practical. Numerous techniques have been introduced to select tests only relevant to a given set of changes. These are typically based on source code, however, modelbased development projects use models as primary artifacts described in various domain-specific languages. Thus, regression test selection should be performed directly on these models. We present a method and a case study on how model-based regression testing can be achieved in the context of autonomous robots. The method uses information from several domain-specific languages for modeling the robot's context and configuration. Our approach is implemented in a prototype tool, and its scalability is evaluated on models from the case study.

This paper presents the lessons learned from six years of experiments with planetary rover prototypes running the Service Oriented Robotic Architecture (SORA) devel-oped by the Intelligent Robotics Group (IRG) at NASA Ames Research Center. SORA relies on proven software methods and technologies applied to the robotic world. Based on a Service Oriented Architecture and robust mid-dleware, SORA extends its reach beyond the on-board robot controller and supports the full suite of software tools used during mission scenarios from ground control to remote robotic sites. SORA has been field tested in numerous scenarios of robotic lunar and planetary explo-ration. The results of these high fidelity experiments are illustrated through concrete examples that have shown the benefits of using SORA as well as its limitations.

2015 IEEE Aerospace Conference, 2015

To implement fault tolerant autonomy in future space systems, it will be necessary to integrate planning, adaptive control, and state estimation subsystems. However, integrating these subsystems is difficult, time-consuming, and error-prone. This paper describes Intelliface/ADAPT, a software testbed that helps researchers develop and test alternative strategies for integrating planning, execution, and diagnosis subsystems more quickly and easily. The testbed's architecture, graphical data displays, and implementations of the integrated subsystems support easy plug and play of alternate components to support research and development in fault-tolerant control of autonomous vehicles and operations support systems. Intelliface/ADAPT controls NASA's Advanced Diagnostics and Prognostics Testbed (ADAPT), which comprises batteries, electrical loads (fans, pumps, and lights), relays, circuit breakers, invertors, and sensors. During plan execution, an experimentor can inject faults into the ADAPT testbed by tripping circuit breakers, changing fan speed settings, and closing valves to restrict fluid flow. The diagnostic subsystem, based on NASA's Hybrid Diagnosis Engine (HyDE), detects and isolates these faults to determine the new state of the plant, ADAPT. Intelliface/ADAPT then updates its model of the ADAPT system's resources and determines whether the current plan can be executed using the reduced resources. If not, the planning subsystem generates a new plan that reschedules tasks, reconfigures ADAPT, and reassigns the use of ADAPT resources as needed to work around the fault. The resource model, planning domain model, and planning goals are expressed using NASA's Action Notation Modeling Language (ANML). Parts of the ANML model are generated automatically, and other parts are constructed by hand using the Planning Model Integrated Development Environment, a visual Eclipse-based IDE that accelerates ANML model development. Because native ANML planners are currently under development and not yet sufficiently capable, the ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA's EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to select and sequence actions based on the state of the ADAPT system. Real-time sensor data, commands, and plans are displayed in information-dense arrays of timelines and graphs that zoom and scroll in unison. A dynamic schematic display uses color to show the real-time fault state and utilization of the system components and resources. An execution manager coordinates the activities of the other subsystems. The subsystems are integrated using the Internet Communications Engine (ICE), an object-oriented toolkit for building distributed applications.

Software and Systems Modeling, 2021

Model-driven engineering (MDE) addresses central aspects of robotics software development. MDE could enable domain experts to leverage the expressiveness of models, while implementation details on different hardware platforms would be handled by automatic code generation. Today, despite strong MDE efforts in the robotics research community, most evidence points to manual code development being the norm. A possible reason for MDE not being accepted by robot software developers could be the wide range of applications and target platforms, which make all-encompassing MDE IDEs hard to develop and maintain. Therefore, we chose to leverage a large corpus of open-source software widely adopted by the robotics community to extract common structures and gain insight on how and where MDE can support the developers to work more efficiently. We pursue modeling as a complement, rather than imposing MDE as separate solution. Our previous work introduced metamodels to describe components, their in...

Volume 3: 28th Computers and Information in Engineering Conference, Parts A and B, 2008

In order to expedite the research and development of robotic systems and foster development of novel robot configuration, it is essential to develop tools and standards that allow researchers to rapidly develop, communicate, and compare experimental results. This paper describes the Mobility Open Architecture Simulation and Tools Framework (MOAST). The MOAST framework is designed to aid in the development, testing, and analysis of robotic software by providing developers with a wide range of open source robotic algorithms and interfaces. The framework provides a physics-based virtual development environment for initial testing and allows for the seamless transition of algorithms to real hardware. This paper details the design approach, software architecture and specific module-to-module interfaces.

Software and Systems Modeling

Multi-robot systems are increasingly deployed to provide services and accomplish missions whose complexity or cost is too high for a single robot to achieve on its own. Although multi-robot systems offer increased reliability via redundancy and enable the execution of more challenging missions, engineering these systems is very complex. This complexity affects not only the architecture modelling of the robotic team but also the modelling and analysis of the collaborative intelligence enabling the team to complete its mission. Existing approaches for the development of multi-robot applications do not provide a systematic mechanism for capturing these aspects and assessing the robustness of multi-robot systems. We address this gap by introducing ATLAS, a novel model-driven approach supporting the systematic design space exploration and robustness analysis of multi-robot systems in simulation. The ATLAS domain-specific language enables modelling the architecture of the robotic team and...

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST), 2020

Robotic systems are increasingly a part of everyday life. Characteristics of robotic systems such as interaction with the physical world, and integration of hardware and software components, differentiate robotic systems from conventional software systems. Although numerous studies have investigated the challenges of software testing in practice, no such study has focused on testing of robotic systems. In this paper, we conduct a qualitative study to better understand the testing practices used by the robotics community, and identify the challenges faced by practitioners when testing their systems. We identify a total of 12 testing practices and 9 testing challenges from our participants' responses. We group these challenges into 3 major themes: Real-world complexities, Community and standards, and Component integration. We believe that further research on addressing challenges described with these three major themes can result in higher adoption of robotics testing practices, more testing automation, and higher-quality robotic systems. Index Terms-robotics testing; testing challenges; qualitative study;

Procedia Computer Science, 2019

Robotic technology helps humans in different areas such as manufacturing, health care and education. Due to the ubiquitous revolution, today's focus is on mobile robots and their applications in a variety of cyber-physical systems. ROS is a wll-known and powerful middleware that facilitates software development for mobile robots. However, this middleware does not support assuring properties such as timeliness and safety of ROS-based software. In this paper we present an integration of Timed Rebeca modeling language with ROS to synthesize verified robotic software. First, a conceptual model of robotic programs is developed using Timed Rebeca. After verifying a set of user-defined correctness properties on this model, it is translated to a ROS program automatically. Experiments on some small-scale case studies illustrates the applicability of the proposed integration method.