17,879 research outputs found
Specification Patterns for Robotic Missions
Mobile and general-purpose robots increasingly support our everyday life,
requiring dependable robotics control software. Creating such software mainly
amounts to implementing their complex behaviors known as missions. Recognizing
the need, a large number of domain-specific specification languages has been
proposed. These, in addition to traditional logical languages, allow the use of
formally specified missions for synthesis, verification, simulation, or guiding
the implementation. For instance, the logical language LTL is commonly used by
experts to specify missions, as an input for planners, which synthesize the
behavior a robot should have. Unfortunately, domain-specific languages are
usually tied to specific robot models, while logical languages such as LTL are
difficult to use by non-experts. We present a catalog of 22 mission
specification patterns for mobile robots, together with tooling for
instantiating, composing, and compiling the patterns to create mission
specifications. The patterns provide solutions for recurrent specification
problems, each of which detailing the usage intent, known uses, relationships
to other patterns, and---most importantly---a template mission specification in
temporal logic. Our tooling produces specifications expressed in the LTL and
CTL temporal logics to be used by planners, simulators, or model checkers. The
patterns originate from 245 realistic textual mission requirements extracted
from the robotics literature, and they are evaluated upon a total of 441
real-world mission requirements and 1251 mission specifications. Five of these
reflect scenarios we defined with two well-known industrial partners developing
human-size robots. We validated our patterns' correctness with simulators and
two real robots
Model-driven engineering approach to design and implementation of robot control system
In this paper we apply a model-driven engineering approach to designing
domain-specific solutions for robot control system development. We present a
case study of the complete process, including identification of the domain
meta-model, graphical notation definition and source code generation for
subsumption architecture -- a well-known example of robot control architecture.
Our goal is to show that both the definition of the robot-control architecture
and its supporting tools fits well into the typical workflow of model-driven
engineering development.Comment: Presented at DSLRob 2011 (arXiv:cs/1212.3308
A Platform-independent Programming Environment for Robot Control
The development of robot control programs is a complex task. Many robots are
different in their electrical and mechanical structure which is also reflected
in the software. Specific robot software environments support the program
development, but are mainly text-based and usually applied by experts in the
field with profound knowledge of the target robot. This paper presents a
graphical programming environment which aims to ease the development of robot
control programs. In contrast to existing graphical robot programming
environments, our approach focuses on the composition of parallel action
sequences. The developed environment allows to schedule independent robot
actions on parallel execution lines and provides mechanism to avoid
side-effects of parallel actions. The developed environment is
platform-independent and based on the model-driven paradigm. The feasibility of
our approach is shown by the application of the sequencer to a simulated
service robot and a robot for educational purpose
Towards a Domain Specific Language for a Scene Graph based Robotic World Model
Robot world model representations are a vital part of robotic applications.
However, there is no support for such representations in model-driven
engineering tool chains. This work proposes a novel Domain Specific Language
(DSL) for robotic world models that are based on the Robot Scene Graph (RSG)
approach. The RSG-DSL can express (a) application specific scene
configurations, (b) semantic scene structures and (c) inputs and outputs for
the computational entities that are loaded into an instance of a world model.Comment: Presented at DSLRob 2013 (arXiv:cs/1312.5952
Collaborative Verification-Driven Engineering of Hybrid Systems
Hybrid systems with both discrete and continuous dynamics are an important
model for real-world cyber-physical systems. The key challenge is to ensure
their correct functioning w.r.t. safety requirements. Promising techniques to
ensure safety seem to be model-driven engineering to develop hybrid systems in
a well-defined and traceable manner, and formal verification to prove their
correctness. Their combination forms the vision of verification-driven
engineering. Often, hybrid systems are rather complex in that they require
expertise from many domains (e.g., robotics, control systems, computer science,
software engineering, and mechanical engineering). Moreover, despite the
remarkable progress in automating formal verification of hybrid systems, the
construction of proofs of complex systems often requires nontrivial human
guidance, since hybrid systems verification tools solve undecidable problems.
It is, thus, not uncommon for development and verification teams to consist of
many players with diverse expertise. This paper introduces a
verification-driven engineering toolset that extends our previous work on
hybrid and arithmetic verification with tools for (i) graphical (UML) and
textual modeling of hybrid systems, (ii) exchanging and comparing models and
proofs, and (iii) managing verification tasks. This toolset makes it easier to
tackle large-scale verification tasks
NASA space station automation: AI-based technology review
Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures
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