Command Language Research Articles

Hierarchical planning with state abstractions for temporal task specifications

We often specify tasks for a robot using temporal language that can include different levels of abstraction. For example, the command “go to the kitchen before going to the second floor” contains spatial abstraction, given that “floor” consists of individual rooms that can also be referred to in isolation (“kitchen”, for example). There is also a temporal ordering of events, defined by the word “before”. Previous works have used syntactically co-safe Linear Temporal Logic (sc-LTL) to interpret temporal language (such as “before”), and Markov Decision Processes (AMDPs) to interpret hierarchical abstractions (such as “kitchen” and “second floor”), separately. To handle both types of commands at once, we introduce the Product Markov Decision Process (AP-MDP), a novel approach capable of representing non-Markovian reward functions at different levels of abstractions. The AP-MDP framework translates LTL into its corresponding automata, creates a product Markov Decision Process (MDP) of the LTL specification and the environment MDP, and decomposes the problem into subproblems to enable efficient planning with abstractions. AP-MDP performs faster than a non-hierarchical method of solving LTL problems in over 95 % of path planning tasks, and this number only increases as the size of the environment domain increases. In a cleanup world domain, AP-MDP performs faster in over 98% of tasks. We also present a neural sequence-to-sequence model trained to translate language commands into LTL expression, and a new corpus of non-Markovian language commands spanning different levels of abstraction. We test our framework with the collected language commands on two drones, demonstrating that our approach enables robots to efficiently solve temporal commands at different levels of abstraction in both indoor and outdoor environments.

ОНТОЛОГИЧЕСКИЙ ПОДХОД В СОЗДАНИИ РОБОТОТЕХНИЧЕСКИХ КОМПЛЕКСОВ С ПОВЫШЕННОЙ СТЕПЕНЬЮ АВТОНОМНОСТИ

The aspects necessary for the implementation of robotic complexes with an increased degree ofautonomy (RC with IDA) in practical work are considered. The distinctive features of such complexes,the needs of the corresponding intelligent information control systems (IIСS) are indicated. The requirementof situational awareness is highlighted and, as a consequence, the need for a diverse systemof knowledge representation, means of perception of the external environment and comparison of operationalinformation with models and a priori information about this environment. In addition, it is pointedout the need to automate the processes of creating RC with IDA, accessibility, and simplification of theiruse. In order to answer these questions, the paper proposes to use the concept and mechanisms of ontologiesin relation to autonomous robotics. Examples of existing solutions in this area are given. In robotics,ontologies are used to define and conceptualize knowledge accepted by the community, using aformal description that is machine-readable, shared, and contains the flexibility to justify this knowledgein order to derive additional information. Ontologies are of considerable interest for multi-agent systemsfor organizing interaction between agents and with other systems in heterogeneous environments,the possibility of reuse and support for the development of new RCs. The author describes the constructionof an ontology proposed by the author in such an applied field as information support for targetedmovements of autonomous ground vehicles based on technical vision systems. All consideration is conductedin the configuration space of the information and control systems of the RC with IDA. This spaceallows you to aggregate a large number of different technologies used in the construction of RC. Theembodiment of a particular system in this space corresponds to the "assembly point". The coordinationof the forms of knowledge representation in the IICS is ensured by the consistent consideration of planesin this space. As a connecting link – a means for automated translation of descriptions of descriptiveontologies into descriptions of functional, machine-readable ontologies, the use of the language of information-motor actions and interpretive navigation commands is proposed. In conclusion, the shorttermprospects for the development of the described approach are considered, and wishes are expressedto the domestic community of roboticists.

Impact assessment of the West African monsoon on convective precipitations over the far north region of Cameroon

Squall lines observed over the sahelo-sudanese regions are responsible for most of the annual rainfall recorded in these regions. They originate from the development of convective processes embedded in the Mesoscale Convective Systems (MCS). The impact assessment of the West African Monsoon (WAM) on the development of squall lines in the sahelo-sudanese regions, particularly the far north region of Cameroon is studied. In this study, the Tropical Rainfall Measuring Mission data (TRMM 3A12 and 3B43) and ERA5 reanalysis data from 1998 to 2008 have been used. The technique used is based on the use of the Climate Data Operator (CDO) software and the NCAR command language (NCL). Analysis of these data shows that the seasonal distribution of winds from the saharan heat-low and the Saint Helena high is the dominant atmospheric dynamics associated with the disturbances behind the development of squall lines. This distribution makes it possible to specifically draw up the evolution of the InterTropical Discontinuity (ITD) on the African continent, and thus, highlight the contribution of the WAM on precipitation in the far north region of Cameroon. This study is performed to contribute to the prediction of hydro-meteorological phenomena to improve disaster risks management associated with floods and landslides in this region, the most vulnerable in Cameroon.

Development of NCL equivalent serial and parallel python routines for meteorological data analysis

The NCAR Command Language (NCL) is a popular scripting language used in the geoscience community for weather data analysis and visualization. Hundreds of years of data are analyzed daily using NCL to make accurate weather predictions. However, due to its sequential nature of execution, it cannot properly utilize the parallel processing power provided by High-Performance Computing systems (HPCs). Until now very few techniques have been developed to make use of the multi-core functionality of modern HPC systems on these functions. In the recent trend, open-source languages are becoming highly popular because they support major functionalities required for data analysis and parallel computing. Hence, developers of NCL have decided to adopt Python as the future scripting language for analysis and visualization and to enable the geosciences community to play an active role in its development and support. This study focuses on developing some of the widely used NCL routines in Python. To deal with the analysis of large datasets, parallel versions of these routines are developed to work within a single node and make use of multi-core CPUs to achieve parallelism. Results show high accuracy between NCL and Python outputs and the parallel versions provided good scaling compared to their sequential counterparts.

Hybrid active flow induced vibration control of a circular cylinder equipped with a wake-mounted smart piezoelectric bimorph splitter plate

A two-dimensional numerical study on active flow induced vibration (FIV) suppression of an elastically suspended circular cylinder fitted with a thin smart flexural-mode (bender-type) piezoelectric bimorph splitter plate on its wake side in real-time collaboration with a conventional base force actuator is carried out in laminar cross-flow condition (Re=100) for a wide range of reduced flow velocities (4≤U∗≤40). The numerical model is based on a strongly-coupled partitioned two-way iteratively implicit Fluid–Structure Interaction (FSI) routine implemented in a multiphysics simulation framework that interactively connects a CFD-based finite volume solver with a nonlinear transient computational structural dynamics (CSD) finite-element solver. A single-input-multi-output (SIMO) direct displacement feedback control law is introduced into the coupled transient dynamic simulation framework through an internal subroutine written in APDL command language. Three distinct feedback control configurations are implemented and compared, namely, the force-actuated, the piezo-actuated, and the hybrid actuation control systems, primarily aiming at suppression of cylinder transverse displacement amplitude. Further improvements on the controller performance are achieved by incorporating two modified hybrid actuation control strategies particularly designed for mitigation of excessive temporal oscillations of the drag and lift coefficients. Extensive numerical simulations reveal the important effects of splitter plate length, reduced velocity, and controller configuration on the key structural/flow-field parameters and flow structure. The hybrid actuation control configurations are found to provide a largely better displacement response control performance than the single-alone force-actuated or piezo-actuated systems. Also, the overall success of the modified hybrid control strategies in effective alleviation of the highly erratic lift and drag forces experienced by the smart cylinder-plate assembly is demonstrated. Lastly, it is concluded that if one primarily aims at prompt and forceful suppression of the base cylinder motion regardless of lift and drag force variations, the originally designed hybrid actuation control system is sufficiently adequate, while if one is specifically concerned with the severe temporal fluctuations in the lift and drag coefficients, the modified hybrid control configurations should be employed.

Free MEDLINE Access Worldwide.

When Donald A.B. Lindberg M.D. was sworn in as Director of the National Library of Medicine (NLM) in 1984, MEDLINE, NLM's online database of citations and abstracts to biomedical journal articles, was searched primarily by librarians trained to use its command language interface. There were fees for searching, primarily to recover the cost of using commercial value-added telecommunications networks. Thirteen years later, in 1997, MEDLINE became free to anyone with an Internet connection and a Web browser. This chapter provides an insider's view of how Dr. Lindberg's vision and leadership - combined with new technology, astute handling of policy issues, and key help from political supporters and influential advocates - enabled a tremendous expansion in access to biomedical and health information for scientists, health professionals, patients, and the public.

Специфика "языка военного обихода" и ее отражение в художественном тексте (русско-чешские параллели)

In given article, the object of our attention is the cases of citing the so-called military language). The use of these textual units as one of the means of creating irony has an obvious intertextual correlation. One of the basic functions of using elements of the military language, as in any work of military subjects, is to create an effect of authenticity of what is happening. In turn, the tradition of using such elements as a vivid figurative expressive means established in Czech literature was laid by J. Hašek in his novel “The Good Soldier Švejk”. Many of his followers, in particular, the Czech writer J. Škvorecký, the Russian author V. Pukhov and many others have largely adopted this method of Hašek, developing it, having used various and heterogeneous in its character ways of playing on such elements, depending on the context. The authors “compensate” for the monotony and stylistic dryness of the language of military commands and reports with a variety of situations, most of them initially comic, where such elements can create unexpected collisions than enhance the comic effect. The main types of the citation of the elements of the military (army) language, including units of the so-called “Army folklore”, and their stylistic and pragmatic role in the structure of the work of fiction are being examined.

Basics of Bash.

Use of the Bash command shell and language is one of the fundamental skills of a bioinformatician. This language is required for accessing high performance computing (HPC) services and effectively using these resources to improve your analyses. Bash is completely text based, which is different from many graphic based operating systems, but this language is also highly powerful, allowing for significant automation and reproducibility within analysis pipelines. This chapter aims to teach the fundamentals of Bash, including how to create files and folders, how to sort and search through files, and how to use pipes and loops to automate processes. By the end of this chapter, readers should be ready to undertake their first simple bioinformatics analysis.

Simulation of the structural and force parameters of a robotic platform using co-simulation

The paper presents the methodology and results of modeling the operation of the parallel mechanism - a 6-DOF robotic platform of the Stewart-Gough type. MSC Adams and Matlab software packages were used as modeling tools, as well as a general-purpose, high-level object-oriented programming language, Python. The digital layout, which has the properties of a parameterized simulation model, is built in the MSC Adams software package. The Python programming language is used as an alternative to the Adams View internal command language for creating and iteratively modifying modeling objects in Adams. Mutual integration of Matlab Simulink and Adams View provides the implementation of joint simulation and allows to perform kinematic, dynamic and force analysis of the mechanism, taking into account its design features through the use of a virtual prototype. Simulink provides the ability to import of physical and mechanical parameters of a solid model from Adams. The proposed implementation of the Python-Adams interface in the form of special procedures and functions automates the execution of a computational experiment and allows solving the problem of optimizing structural elements and finding the optimal geometric design of the platform in accordance with the selected optimality criteria. This is implemented through conducting a series of experiments consisting in sequential multiple changes in geometric parameters, followed by simulation model and analysis of the results in order to find design options that meet the specified criteria. The technique was tested on the example of one of the design versions of the platform when moving along several characteristic types of a given trajectory. The results of a computational experiment are presented and an analysis of the force characteristics during movement along a given trajectory is carried out.

Talk2Car: Predicting Physical Trajectories for Natural Language Commands

In recent years, there has been an increased interest in giving verbal commands to self-driving cars. Even though multiple companies have showcased progress towards fully autonomous vehicles, surveys have indicated that people are wary of relinquishing total control of the vehicle to the AI. Thus, a system allowing passengers to control the vehicle’s actions would be preferable. Natural language, the most widespread form of communication among humans, presents itself as the most natural control interface, and survey results confirm that the ability to give verbal commands to self-driving vehicles would make the passengers more at ease. In this work, we propose a novel system that predicts which object is referred to by the issued command and the path the car should follow through the immediate surroundings to execute the command. We experiment with different approaches and features to predict the object of interest and show that our simple but effective approach achieves state-of-the-art performance. For predicting the trajectory, we propose a model that relies on a mixture density approach for modeling the distributions of key waypoints of the trajectory in the top-down scene layout. Additionally, we investigate the influence of the two tasks on each other and show that improvements in the prediction of the object of interest lead to improvements in the trajectory prediction task. Finally, we provide the research community with an extension to the Talk2Car dataset, with new trajectory annotations for given commands.

Building a Natural Language Query and Control Interface for IoT Platforms

The rapid development and popularity of IoT technology has reshaped the way people interact with the real world. Many researchers have attempted to build natural language interfaces for IoT platforms, but have not produced much progress in parsing natural language commands that contain multiple operations and more complex logical structures. In this paper, we propose IoT-NLI, a natural language query and control interface for popular IoT platforms, which uses hierarchical semantic parsing algorithms and directed edge-tagged graph structures to efficiently parse natural language commands input by users, enabling them to perform multiple operations contained in one complex natural language command. Experiments in three domains, agriculture, industry, and smart home, show that IoT-NLI has excellent performance and reasonable response time. Finally, a IoT-NLI application was developed on the Android platform and integrated with the AliCloud platform. It enables users to query and control devices on Android phones through chat windows similar to instant messaging software.

Compositional RL Agents That Follow Language Commands in Temporal Logic

We demonstrate how a reinforcement learning agent can use compositional recurrent neural networks to learn to carry out commands specified in linear temporal logic (LTL). Our approach takes as input an LTL formula, structures a deep network according to the parse of the formula, and determines satisfying actions. This compositional structure of the network enables zero-shot generalization to significantly more complex unseen formulas. We demonstrate this ability in multiple problem domains with both discrete and continuous state-action spaces. In a symbolic domain, the agent finds a sequence of letters that satisfy a specification. In a Minecraft-like environment, the agent finds a sequence of actions that conform to a formula. In the Fetch environment, the robot finds a sequence of arm configurations that move blocks on a table to fulfill the commands. While most prior work can learn to execute one formula reliably, we develop a novel form of multi-task learning for RL agents that allows them to learn from a diverse set of tasks and generalize to a new set of diverse tasks without any additional training. The compositional structures presented here are not specific to LTL, thus opening the path to RL agents that perform zero-shot generalization in other compositional domains.

The probabilistic model checker Storm

We present the probabilistic model checker Storm. Storm supports the analysis of discrete- and continuous-time variants of both Markov chains and Markov decision processes. Storm has three major distinguishing features. It supports multiple input languages for Markov models, including the Jani and Prism modeling languages, dynamic fault trees, generalized stochastic Petri nets, and the probabilistic guarded command language. It has a modular setup in which solvers and symbolic engines can easily be exchanged. Its Python API allows for rapid prototyping by encapsulating Storm’s fast and scalable algorithms. This paper reports on the main features of Storm and explains how to effectively use them. A description is provided of the main distinguishing functionalities of Storm. Finally, an empirical evaluation of different configurations of Storm on the QComp 2019 benchmark set is presented.

An improved multivariable integrated evaluation method and tool (MVIETool) v1.0 for multimodel intercomparison

Abstract. An evaluation of a model's overall performance in simulating multiple fields is fundamental to model intercomparison and development. A multivariable integrated evaluation (MVIE) method was proposed previously based on a vector field evaluation (VFE) diagram, which can provide quantitative and comprehensive evaluation on multiple fields. In this study, we make further improvements to this method from the following aspects. (1) We take area weighting into account in the definition of statistics in the VFE diagram and MVIE method, which is particularly important for a global evaluation. (2) We consider the combination of multiple scalar fields and vector fields against multiple scalar fields alone in the previous MVIE method. (3) A multivariable integrated skill score (MISS) is proposed as a flexible index to measure a model's ability to simulate multiple fields. Compared with the multivariable integrated evaluation index (MIEI) proposed in the previous study, MISS is a normalized index that can adjust the relative importance of different aspects of model performance. (4) A simple-to-use and straightforward tool, the Multivariable Integrated Evaluation Tool (MVIETool version 1.0), is developed to facilitate an intercomparison of the performance of various models. Users can use the tool coded either with the open-source NCAR Command Language (NCL) or Python3 to calculate the MVIE statistics and plotting. With the support of this tool, one can easily evaluate model performance in terms of each individual variable and/or multiple variables.

Conversational Neuro-Symbolic Commonsense Reasoning

In order for conversational AI systems to hold more natural and broad-ranging conversations, they will require much more commonsense, including the ability to identify unstated presumptions of their conversational partners. For example, in the command "If it snows at night then wake me up early because I don't want to be late for work" the speaker relies on commonsense reasoning of the listener to infer the implicit presumption that they wish to be woken only if it snows enough to cause traffic slowdowns. We consider here the problem of understanding such imprecisely stated natural language commands given in the form of if-(state), then-(action), because-(goal) statements. More precisely, we consider the problem of identifying the unstated presumptions of the speaker that allow the requested action to achieve the desired goal from the given state (perhaps elaborated by making the implicit presumptions explicit). We release a benchmark data set for this task, collected from humans and annotated with commonsense presumptions. We present a neuro-symbolic theorem prover that extracts multi-hop reasoning chains, and apply it to this problem. Furthermore, to accommodate the reality that current AI commonsense systems lack full coverage, we also present an interactive conversational framework built on our neuro-symbolic system, that conversationally evokes commonsense knowledge from humans to complete its reasoning chains.

Agile Tasking of Robotic Systems with Explicit Autonomy

Task agility is an increasingly desirable feature for robots in application domains such as manufacturing. The Canonical Robot Command Language (CRCL) is a lightweight information model built for agile tasking of robotic systems. CRCL replaces the underlying complex proprietary robot programming interface with a standard interface. In this paper, we exchange the automated planning component that CRCL used in the past for a rational agent in the Gwendolen agent programming language, thus providing greater possibilities for formal verification and explicit autonomy. We evaluate our approach by performing agile tasking in a kitting case study.

A computer aided drawing system evaluation with early and late blind users

ABSTRACT The present lack of suitable and efficient graphics creation techniques may place limitations on the career progression and life contentment of blind students. It is challenging for a BVI (Blind and Visually Impaired) person to draw diagrams or art, which are commonly taught in education or used in industry. The SETUP09 graphics creation system was developed to address a need for blind users to be able to create such content and consists of both navigation and computer aided drawing techniques, enabling graphics creation and manipulation through command language and intuitive, matrix-style movement. The technique can facilitate a user’s ability to produce art and scientific diagrams electronically. This paper presents a comparative system evaluation of digital versus analogue drawing techniques with early and late blind individuals. Users were tested using different graphics creation tasks to assess the accuracy and efficiency of an analogue drawing technique compared with the digital SETUP09 system. The results confirmed that the SETUP09 compass-based graphics creation technique allows greater accuracy in completing a drawing task, with a noticeable reduction in effort compared to analogue drawing techniques.

Ontology-based knowledge management with verbal interaction for command interpretation and execution by home service robots

This paper describes a system for service robots that combines ontological knowledge reasoning and human–robot interaction to interpret natural language commands and successfully perform household chores, such as finding and delivering objects. Knowledge and context reasoning is essential for providing more efficient service robots, given their diverse and continuously changing environments. Moreover, since they are in contact with humans, robots require such skills as interaction and language. Therefore, we developed a system with specific modules to manage robots’ knowledge and reasoning, command analysis, decision-making, and talking interaction. The system relies on inference methods and verbal interaction to understand commands and clarify uncertain information. We tested our system inside a simulated environment where the robot receives commands with missing or unclear information. The system’s performance was compared with the average performance of human subjects who completed the same commands in the simulation.

Design of Control Unit of Mechanical Property Test System of Tai Lake Shield

This paper focuses on the design and implementation of the detection device. This paper discusses that the control unit realizes the stepping drive by the interrupt method, realizes the force acquisition and the Modbus RTU communication by the polling method, designs the main program, the force acquisition subroutine flow, the stepping driver subroutine flow, and the Modbus slave subroutine flow, and realizes it through the Arduino IDE programming. Design the host computer interface, database association and command language programming; At last, the application effect of the test system is verified by the tensile test of water shield stem of taihu lake.

SCPI based integrated test and measurement environment using LabVIEW

Test and Measurement processes play a vital role on the quality of hardware functionality testing. Automating these processes provides a better reduction in “time to market” and is more concerned on achieving higher test coverage area when it comes to mass production. Functional testing deals with the observation on the characteristics of the hardware to determine whether it replicates the needs for which it was actually designed. This can be achieved using set of Test and Measurement Instruments which can replicate the environmental condition in which the hardware is to be deployed. This paper provides an environment to integrate set of measurement instruments in a single platform (LabVIEW) and automate the measurement control using command language know as Standard Command for Programmable Instrumentation (SCPI). Script based control commands provide an easy configuration and remote control of instruments. And also programming interface control using Virtual Instrument Software Architecture (VISA) to control instruments using Ethernet and USB protocol.