• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.192-200
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• 2012

In order for humans and robots to interact in daily life, robots need to understand human speech and link it to their actions. This paper proposes a hierarchical behavior model for robot action control using natural language commands. The model, which consists of episodes, primitive actions and atomic functions, uses a sentential cognitive system that includes multiple modules for perception, action, reasoning and memory. Human speech commands are translated to sentences with a natural language processor that are syntactically parsed. A semantic parsing procedure was applied to human speech by analyzing the verbs and phrases of the sentences and linking them to the cognitive information. The cognitive system performed according to the hierarchical behavior model, which consists of episodes, primitive actions and atomic functions, which are implemented in the system. In the experiments, a possible episode, "Water the pot," was tested and its feasibility was evaluated.

• Electronics and Telecommunications Trends
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• v.39 no.1
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• pp.95-105
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• 2024

In natural language processing, large language models such as GPT-4 have recently been in the spotlight. The performance of natural language processing has advanced dramatically driven by an increase in the number of model parameters related to the number of acceptable input tokens and model size. Research on multimodal models that can simultaneously process natural language and image data is being actively conducted. Moreover, natural-language and image-based reasoning capabilities of large language models is being explored in robot artificial intelligence technology. We discuss research and related patent trends in robot task planning and code generation for robot control using large language models.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.49-51
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• 2005

Robot control involves advance programming, scientific and high technology. The systematic and methodological aspects of robot controls often results in having superficial control design problems that can negatively affect the robot application, usability and appeal. User friendly interface of robot control is extremely advantageous and more attractive. To illustrate, the application of medical robot is usually handled by clients who have little background in advance programming language. Thus, it would be difficult if the client needs to use programming language to control the robot. It would justify better if the robot control is presented in a meaningful interface to the client. This way the robot application would be more natural and user friendly. This paper describes the method of developing the user interface for web based communication to control an internet robot named Tarou. The web based communication tasks involves three levels. The first one accommodates on the client sending commands to robot through the internet. The next communication level relates to the robot receiving the commands sent by the client. The final communication level generates on sending feedback on status of commands by the robot to the client. The methodology used here can be elaborated in four hierarchical steps; identify user needs and robot tasks, identify the enhancing tag reference used by the server, induce the tag into HTML, present the HTML in attractive user interface as the client control panel.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.603-608
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• 2003

Recently, personal robots and home robots are developing by many companies and research groups. It is considered that a general effective interface for user of those robots is speech or voice. In this paper, Japanese speech based man-machine interface system is discussed for reflecting the fuzziness of natural language on robots, by using fuzzy reasoning. The present system consists of the derivation part of action command and the modification part of the derived command. In particular, a unique problem of Japanese is solved by applying the morphological analyzer ChaSen. The proposed system is applied for the motion control of a robot manipulator. It is proved from the experimental results that the proposed system can easily modify the same voice command to the actual different levels of the command, according to the current state of the robot.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1391-1399
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• 2015

In recent times, studies sentiment analysis are being actively conducted by implementing natural language processing technologies for analyzing subjective data such as opinions and attitudes of users expressed on the Web, blogs, and social networking services (SNSs). Conventionally, to classify the sentiments in texts, most studies determine positive/negative/neutral sentiments by assigning polarity values for sentiment vocabulary using sentiment lexicons. However, in this study, sentiments are classified based on Thayer's model, which is psychologically defined, unlike the polarity classification used in opinion mining. In this paper, as a method for classifying the sentiments, sentiment categories are proposed by extracting sentiment keywords for major sentiments by using hashtags, which are essential elements of Instagram. By applying sentiment categories to user posts, sentiments can be determined through the similarity measurement between the sentiment adjective candidates and the sentiment keywords. The test results of the proposed method show that the average accuracy rate for all the sentiment categories was 90.7%, which indicates good performance. If a sentiment classification system with a large capacity is prepared using the proposed method, then it is expected that sentiment analysis in various fields will be possible, such as for determining social phenomena through SNS.