Robot Language Research Articles

An acoustic multi-frequency robot communication language

The task of robot communication based on the multi-frequency acoustic tonal language is considered. A formal model of the language is presented in which a sequence of acoustic multi-frequency signals corresponds to each language symbol and an algorithm for recognition of such characteristic sounds is considered.

Techniques for automated testing of Lola industrial robot language Parser

The accuracy of parsing execution directly affects the accuracy of semantic analysis, optimization and object code generation. Therefore, parser testing represents the basis of compiler testing. It should include tests for correct and expected, but also for unexpected and invalid cases. Techniques for testing the parser, as well as algorithms and tools for test sentences generation, are discussed in this paper. The methodology for initial testing of a newly developed compiler is proposed. Generation of negative test sentences by modifying the original language grammar is described. Positive and negative test cases generated by Grow, Purdom's algorithm with and without length control, CDRC-P algorithm and CDRC-P algorithm with length control are applied to the testing of L-IRL robot programming language. For this purpose two different tools for generation of test sentences are used. Based on the presented analysis of possible solutions, the appropriate method can be chosen for testing the parser for smaller grammars with many recursive rules.

A STEP-compliant Industrial Robot Data Model for robot off-line programming systems

Recently, various robot off-line programming systems have promoted their own robot data models, resulting in a plethora of robot representation methods and unchangeable data files among CAx and robot off-line programming systems. The current paper represents a STEP-compliant Industrial Robot Data Model (IRDM) for data exchange between CAx systems and robot off-line programming systems. Using this novel representation method, most resources involved in a robot manufacturing system can be represented. The geometric and mathematic aspects of industrial robots have been defined in IRDM, so that the robot off-line programming system could have abundant information to represent robots’ kinematic and dynamic behaviors. In order to validate the proposed models and approaches, a prototype robot off-line programming system with 3D virtual environment is presented. The functionalities of IRDM not only have significant meaning for providing a unified data platform for robot simulation systems, but also have the potential capability to represent robot language using the object-oriented concept.

The acoustic tonal robot communication language

A robot communication language is developed based on tone acoustic signals. A sequence of single-frequency acoustic signals (artificially synthesized phonemes of the language) corresponds to each character of the language. An algorithm is provided for the detection of such specific signals. The results of several experiments are given.

1A2-Q07 配電作業用ロボットのシミュレータの開発 : 工具箱のアームタイの把持(作業をするロボット(1))

We are developing a robot system for power distribution line maintenance tasks. We analyzed switching gear installation tasks among the maintenance tasks and described task instruction sheets for the installation tasks with a robot language. We have developed a CG simulator to execute robot commands in task instruction sheets. In this paper, we describe a task instruction sheet for "Gripping arm tie on a tool box", a program function for the task command, and CG simulations. The robot can generated the trajectory and move the robot arms for "Gripping arm tie on a tool box" in CG space.

Development of CAM system based on industrial robotic servo controller without using robot language

This paper describes the development of a robotic CAM system for an articulated industrial robot RV1A from the view point of robotic servo controller. It is defined here that the CAM system includes an important function which allows an industrial robot to move along cutter location data (CL data) consisting of position and orientation components. In addition, the developed CAM system has a high applicability to other industrial robots whose servo systems are technically opened to end-users. The developed robotic CAM system works as a straightforward interface between a general CAD/CAM and an industrial robot. At the present stage, the relationship between CAD/CAM and industrial robots is not well established compared to NC machine tools that are widely spread in manufacturing industries. The CAM systems for NC machine tools are already established, however, the CAM system for industrial robots has not been sufficiently considered and developed yet. A teaching pendant is generally used to obtain position and orientation data of the arm tip before an industrial robot works. Here, in order to enhance the relationship between a conventional CAD/CAM system and an industrial robot, a simple and straightforward CAM system without using any robot language is developed and implemented. The basic design of the robotic CAM system and the experimental results are presented in this paper.

High‐level robot programming based on CAD: dealing with unpredictable environments

PurposeThe purpose of this paper is to present a CAD‐based human‐robot interface that allows non‐expert users to teach a robot in a manner similar to that used by human beings to teach each other.Design/methodology/approachIntuitive robot programming is achieved by using CAD drawings to generate robot programs off‐line. Sensory feedback allows minimization of the effects of uncertainty, providing information to adjust the robot paths during robot operation.FindingsIt was found that it is possible to generate a robot program from a common CAD drawing and run it without any major concerns about calibration or CAD model accuracy.Research limitations/implicationsA limitation of the proposed system has to do with the fact that it was designed to be used for particular technological applications.Practical implicationsSince most manufacturing companies have CAD packages in their facilities today, CAD‐based robot programming may be a good option to program robots without the need for skilled robot programmers.Originality/valueThe paper proposes a new CAD‐based robot programming system. Robot programs are directly generated from a CAD drawing “running” on a commonly available 3D CAD package (Autodesk Inventor) and not from a commercial, computer aided robotics (CAR) software, making it a simple CAD integrated solution. This is a low‐cost and low‐setup time system where no advanced robot programming skills are required to operate it. In summary, robot programs are generated with a high‐level of abstraction from the robot language.

Humanoid Upper Torso Complexity for Displaying Gestures

Body language is an important part of human-to-human communication; therefore body language in humanoid robots is very important for successful communication and social interaction with humans. The number of degrees of freedom (d.o.f) necessary to achieve realistic body language in robots has been investigated. Using animation, three robots were simulated performing body language gestures; the complex model was given 25 d.o.f, the simplified model 18 d.o.f and the basic model 10 d.o.f. A subjective survey was created online using these animations, to obtain people's opinions on the realism of the gestures and to see if they could recognise the emotions portrayed. It was concluded that the basic system was the least realistic, complex system the most realistic, and the simplified system was only slightly less realistic than the human. Modular robotic joints were then fabricated so that the gestures could be implemented experimentally. The experimental results demonstrate that through simplification of the required degrees of freedom, the gestures can be experimentally reproduced.

Humanoid Upper Torso Complexity for Displaying Gestures

Body language is an important part of human-to-human communication; therefore body language in humanoid robots is very important for successful communication and social interaction with humans. The number of degrees of freedom (d.o.f) necessary to achieve realistic body language in robots has been investigated. Using animation, three robots were simulated performing body language gestures; the complex model was given 25 d.o.f, the simplified model 18 d.o.f and the basic model 10 d.o.f. A subjective survey was created online using these animations, to obtain people's opinions on the realism of the gestures and to see if they could recognise the emotions portrayed. It was concluded that the basic system was the least realistic, complex system the most realistic, and the simplified system was only slightly less realistic than the human. Modular robotic joints were then fabricated so that the gestures could be implemented experimentally. The experimental results demonstrate that through simplification of the required degrees of freedom, the gestures can be experimentally reproduced.

Are We There Yet? Grounding Temporal Concepts in Shared Journeys

An understanding of time and temporal concepts is critical for interacting with the world and with other agents in the world. What does a robot need to know to refer to the temporal aspects of events-could a robot gain a grounded understanding of “a long journey,” or “soon?” Cognitive maps constructed by individual agents from their own journey experiences have been used for grounding spatial concepts in robot languages. In this paper, we test whether a similar methodology can be applied to learning temporal concepts and an associated lexicon to answer the question “how long” did it take to complete a journey. Using evolutionary language games for specific and generic journeys, successful communication was established for concepts based on representations of time, distance, and amount of change. The studies demonstrate that a lexicon for journey duration can be grounded using a variety of concepts. Spatial and temporal terms are not identical, but the studies show that both can be learned using similar language evolution methods, and that time, distance, and change can serve as proxies for each other under noisy conditions. Effective concepts and names for duration provide a first step towards a grounded lexicon for temporal interval logic.

Mutual Gaze: Implications for Human-Robot Interaction

Mutual Gaze: Implications for Human-Robot Interaction

From symbol grounding to socially shared embodied language knowledge

Much language-related research in cognitive robotics appeals to usage-based models of language as proposed in cognitive linguistics and developmental psychology [1, 2] that emphasise the significance of learning, embodiment and general cognitive development for human language acquisition. Over and above these issues, however, what takes centre stage in these theories are social-cognitive skills of “intention-reading” that are seen as “primary in the language acquisition process” [1] – and also as difficult to incorporate into computational models of language acquisition. The present paper addresses these concerns: we describe work in progress on a series of experiments that take steps towards closing the gap between ‘solipsistic’ symbol grounding in individual robotic agents and socially framed embodied language acquisition in learners that attend to common ground [3] with changing interlocutors.

An Example of Open Robot Controller Architecture - For Power Distribution Line Maintenance Robot System -

In this paper, we propose an architecture for easily constructing a robot controller. The architecture is a multi-agent system which has eight agents: the Man-machine interface, Task planner, Task teaching editor, Motion planner, Arm controller, Vehicle controller, Vision system and CG display. The controller has three databases: the Task knowledge database, the Robot database and the Environment database. Based on this controller architecture, we are constructing an experimental power distribution line maintenance robot system and are doing the experiment for the maintenance tasks, for example, “Bolt insertion task”. Keywords—Robot controller, Software library, Maintenance robot, Robot language, Agent system.

Utilising scripting language for unmanned and automated guided vehicles operating within row crops

A flexible high-level control language is an important element in the ongoing task of introducing automated guided vehicles (AGV) to new application domains. A new application domain is row crops, where small AGV's will perform weed control around individual crop plants. This paper defines the requirements and scope of a process- and behaviour-based scripting language needed to control the weeding AGV in an agricultural row crop. The goal is to traverse and cover the whole field with no human auxiliary input during the field operation. The basis is the transparent and tactical real-time control language (CL) for small mobile robots (SMR). This SMR-CL has been modified to include some necessary motion commands and a supplemental supervisory function to monitor and record the progressive coverage of the field. The control language was then tested by applying it to a scenario representing typical field conditions for row crops. The construction of a suitable SMR-CL script for use in a field clearly demonstrates the feasibility of adapting behaviour-based control systems to field structures. The conducted case study indicated the importance of including goal-directing modules. Such a module is described here as the ‘supervisory field coverage monitor’ (SFCM), which acts to coordinate the behaviours. The applicability of this modified SMR-CL has been successfully demonstrated using a vehicle test in a specially designed artificial row crop field. The analysis of the operational performance verified that it is possible to cover all rows in a field without conducting time-consuming planning procedures.

Manipulating Deformable Linear Objects: Fuzzy-Based Active Vibration Damping Skill

Human can handle a deformable object and damp its vibration with recognized skill. However, for an industrial robot, handling a deformable object with acute vibration is often a difficult task. This paper addresses the problem of active damping skill for handling deformable linear objects (DLOs) by using a strategy inspired from human manipulation skills. The strategy is illustrated by several rules, which are explained by a fuzzy and a P controller. A proportional-integral-derivative (PID) controller is also employed to explain the rules as a comparison. The interpretations from controllers are translated into high level commands in a robotic language V+. A standard industrial robot with a force/torque sensor mounted on the wrist was employed to demonstrate the skill. Experimental results showed the fuzzy based damping skill is quite effective and stable even without any previous acknowledge of the deformable linear objects.

Temporal sequence detection with spiking neurons: towards recognizing robot language instructions

We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a new model of an integrate-and-fire neuron with active dendrites and dynamic synapses (ADDS) and its synaptic plasticity rule. The neuron employs the dynamics of the synapses and the active properties of the dendrites as an adaptive mechanism for maximizing its response to a specific spatio-temporal distribution of incoming action potentials. The learning algorithm follows recent biological evidence on synaptic plasticity. It goes beyond the current computational approaches which are based only on the relative timing between single pre- and post-synaptic spikes and implements a functional dependence based on the state of the dendritic and somatic membrane potentials around the pre- and post-synaptic action potentials. The learning algorithm is demonstrated to effectively train the neuron towards a selective response determined by the spatio-temporal pattern of the onsets of input spike trains. The model is used in the implementation of a part of a robotic system for natural language instructions. We test the model with a robot whose goal is to recognize and execute language instructions. The research in this article demonstrates the potential of spiking neurons for processing spatio-temporal patterns and the experiments present spiking neural networks as a paradigm which can be applied for modelling sequence detectors at word level for robot instructions.

Weathering MindStorms with drizzle and DIODE in CS0

We introduce Drizzle, our new simple object-oriented scripting language for programming LEGO MindStorms robots, and DIODE, the Drizzle Integrated Object-Oriented Development Environment. Drizzle and DIODE have evolved from a student project into useful resources for our CS0 course. In this work we describe Drizzle and DIODE and discuss our experiences with them in our CS0 course.We are dismayed by the low retention rates of undergraduate majors in CS1 and CS2. To attempt to alleviate this problem, we introduced a new required CS0 course in Fall 2004. Its goals are to give students a breadth-first overview of CS and to expose them to algorithmic problem solving before immersing them in Java. We decided to use the MindStorms robots to accommodate student diversity, to introduce a fun element to the course, and to force the students to focus on problem analysis instead of detailed syntax. Our approach complements [2].Drizzle is a simple object-oriented scripting language. It supports repetition, selection, simple assignment statements, logical operators, numeric variables, and predefined objects representing components of a robot, i.e., sensors, motors, and the LCD display. Drizzle is purposely minimal to be suitable for students without prior programming experience. To encourage documentation, Drizzle supports comments.DIODE is the IDE that allows a MindStorms robot to be programmed in Drizzle. To achieve this, we used the leJOS API [3] to implement method call abstractions supporting the predefined objects. The IDE includes an intuitive GUI. It allows for automatic compilation of Drizzle code, including a translator from Drizzle to Java utilizing the predefined MindStorms objects. DIODE also directly interfaces to the robot's IR device. We provided these features because our typical user was familiar with text editing but was not familiar with command-line tools.Our CS0 course is currently taught in one 120-student section and meets 3 hours per week for 14 weeks. At least 3 hours are spent on each of algorithmic thinking and concepts of programming languages before Drizzle and DIODE are formally presented. The students see an actual problem with pseudocode and the corresponding Drizzle solution. A problem is then posed as a "Drizzle Team Challenge". Students must complete individual solution plans. The instructor then forms the student groups. Next, the teams produce solution plans. Finally, they are allowed to program with the actual robot. The lab has 3 computers with DIODE installed and 6 robots with 6 tracks. During the Fall 2004 offering, the 14 teams consisted of between 5 and 8 students. The large class size and small number of robots made smaller groups infeasible. No team solved the problem totally correctly during the first lab session. Not surprisingly, the smaller groups were more effective. All teams submitted at least a partial solution to the problem; 12 completed the solution. Students were excited about working with the robots.We are using Drizzle (and DIODE) again during Spring 2005. We expect to have smaller groups. We hope to evaluate the effectiveness of Drizzle; some possible approaches are additional questions in the course evaluation, surveys at the beginning and end of CS1, and analyses of CS1/CS2 retention rates. We may also compare the usage of Drizzle with the standard MindStorms approach and Alice [1].

Post-processing methodologies for off-line robot programming within computer integrated manufacture

A robot simulation system has been used not only as a design and simulation tool, but it also serves as an off-line programming system for industrial robots and other machines with a computer integrated manufacture (CIM) system. A robot simulation system is one of the essential elements for virtual manufacturing and agile manufacturing. A post-processor is an important element of an off-line robot programming system, as it allows the commercially available robot simulation systems to be used as off-line robot programming tools. The post-processor translates output statements from a robot simulator to a target robot language. Typically, the sequence of motion and data required to drive the robot can be transmitted through the use of a serial or parallel data link, between an off-line computer and a robot controller. The design of a general post-processor capable of translating the output of multiple robot simulators to multiple robot programming languages is an extremely complex problem. There are two basic ways of describing robot movements in robot control systems; one describes the manipulator movements in terms of the manipulator end-effector location (in compound transformation or absolute); whilst the other describes the movements in terms of manipulator joint angles. The former approach is suitable for future and present generation robots with a language processor installed in their controllers, whilst the latter is only specifically linked to earlier generation robot languages. Discrepancies between a specific robot simulation system and a real robot system which should be resolved as part of the post-processing, are analysed. The feasibility of generalising the post-processor was studied. In this paper different approaches of post-processing for off-line programs and methods of downloading off-line programs to robot controller are discussed also.

Development of Motion Data Description Language for Robots Based on eXtensible Markup Language - Realization of Better Understanding and Communication via Networks

To realize a ubiquitous robot and software avatar society, we propose the concept of a MotionMedia content sharing platform. MotionMedia is defined as a physical communication medium that includes the actual motion of robots or physical end-effectors - called the ""5th medium,"" after audio, text, image, and video. MotionMedia is expected to be disseminated worldwide once its value in realizing better understanding and communication between people via broadband networks through the support of advanced communication media is recognized. To share MotionMedia content, especially motion data, a motion data modeling and formulation system for human-type robots based on eXtensible Markup Language (MotionXML) has been developed. MotionXML leads to specifications for conveying and reproducing robot motion via networks. It enables the same set of motion data to be shared by robots that have different structures and control interfaces. An application program interface (MotionAPI) has also been developed as a common access interface for MotionXML, enabling application developers to handle MotionXML easily and to develop applications more rapidly.

Introduction to robotics analysis, systems, applications

Most chapter begins with an Introduction and conclude with a Summary, References and Problems. 1. Fundamentals. What is a Robot? Classification of Robots. What is Robotics? History of Robotics. Advantages and Disadvantages of Robots. Robot Components. Robot Degrees of Freedom. Robot Joints. Robot Coordinates. Robot Reference Frames. Programming Modes. Robot Characteristics. Robot Workspace. Robot Languages. Robot Applications. Other Robots and Applications. Social Issues. 2. Robot Kinematics: Position Analysis. Robots as Mechanisms. Matrix Representation. Homogeneous Transformation Matrices. Representation of Transformations. Inverse of Transformation Matrices. Forward and Inverse Kinematics of Robots. Denavit-Hartenberg Representation of Forward Kinematic Equations of Robots. The Inverse Kinematic Solution of Robots. Inverse Kinematic Programming of Robots. Degeneracy and Dexterity. The Fundamental Problem with the Denavit-Hartenberg Representation. Design Project 1: A Three-Degree-of-Freedom Robot. 3. Differential Motions and Velocities. Differential Relationships. Jacobian. Differential Motions of a Frame. Interpretation of the Differential Change. Differential Changes Between Frames. Differential Motions of a Robot and Its Hand Frame. Calculation of the Jacobian. How to Relate the Jacobian and the Differential Operator. Inverse Jacobian. Design Project. 4. Dynamic Analysis and Forces. Lagrangian Mechanics: A Short Overview. Effective Moments of Inertia. Dynamic Equations for Multiple-Degree-of-Freedom Robots. Static Force Analysis of Robots. Transformation of Forces and Moments Between Coordinate Frames. Design Project. 5. Trajectory Planning. Path vs. Trajectory. Joint-Space vs. Cartesian-Space Descriptions. Basics of Trajectory Planning. Joint-Space Trajectory Planning. Cartesian-Space Trajectories. Continuous Trajectory Recording. Design Project. 6. Actuators. Characteristics of Actuating Systems. Comparison of Actuating Systems. Hydraulic Devices. Pneumatic Devices. Electric Motors. Microprocessor Control of Electric Motors. Magnetostrictive Actuators. Shape-Memory Type Metals. Speed Reduction. Design Project 1. Design Project 2. 7. Sensors. Sensor Characteristics. Position Sensors. Velocity Sensors. Acceleration Sensors. Force and Pressure Sensors. Torque Sensors. Microswitches. Light and Infrared Sensors. Touch and Tactile Sensors. Proximity Sensors. Range-finders. Sniff Sensors. Vision Systems. Voice Recognition Devices. Voice Synthesizers. Remote Center Compliance (RCC) Device. Design Project. 8. Image Processing and Analysis with Vision Systems. Image Processing versus Image Analysis. Two- and Three-Dimensional Image Types. What is an Image. Acquisition of Images. Digital Images. Frequency Domain vs. Spatial Domain. Fourier Transform of a Signal and its Frequency Content. Frequency Content of an Image Noise, Edges. Spatial Domain Operations: Convolution Mask. Sampling and Quantization. Sampling Theorem. Image-Processing Techniques. Histogram of Images. Thresholding. Connectivity. Noise Reduction. Edge Detection. Hough Transform. Segmentation. Segmentation by Region Growing and Region Splitting. Binary Morphology Operations. Gray Morphology Operations. Image Analysis. Object Recognition by Features. Depth Measurement with Vision Systems. Specialized Lighting. Image Data Compression. Real-Time Image Processing. Heuristics. Applications of Vision Systems. Design project. 9. Fuzzy Logic Control. Fuzzy Control: What is Needed. Crisp Values vs. Fuzzy Values. Fuzzy Sets: Degrees of Membership and Truth. Fuzzification. Fuzzy Inference Rule Base. Defuzzification. Simulation of Fuzzy Logic Controller. Applications of Fuzzy Logic in Robotics. Design Project. Appendix. Matrix Algebra and Notation: A Review. Calculation of an Angle From its Sine, Cosine, or Tangent. Problems. Index.