Description:Field of the Invention
This invention relates to a system of Shape identification Robot with voice command and NLP.
Background of the Invention
The natural language processing (NLP) algorithms driven by artificial intelligence (AI) are employed by our mobile robot platform for interpreting voice commands. This ensures precise translation regardless of speech rhythm, dialect, or background noise, which minimizes misinterpreting instructions and taking unauthorized actions that previous technologies might have carried out.
By interpreting keywords and context, AI systems translate spoken commands into guidelines that empower robots comprehend and carry out user intentions. This contextual awareness assists in eliminating the constrained and laborious command methods that exist in traditional voice command systems. AI models may adapt to diverse command words, creating a more natural and user-friendly interface. Real-time command processing by the system reduces wait times and increases the robot's effectiveness in completing duties on time. AI-driven systems can also learn from interactions, which helps them perform better over time and handle a greater variety of requests with greater precision. Because of its elasticity and capacity for ongoing learning, the system is more scalable and accessible without the need for expensive, specialist software. Overall, voice command processing with AI makes the robot a more responsive, intelligent, and economical instrument, greatly increasing its usefulness and efficacy in practical applications.
CN105127984B-A kind of industrial robot and its control method, industrial robot has the arm of multiple arms including being connected to relatively rotate, it can make industrial robot emergent stopping in such a way that the posture of arm is in designated state if even if the control method of industrial robot is when industrial robot includes multiple motors for making multiple arm rotations. Industrial robot has the arm of multiple arms including being connected to relatively rotate, and includes: Multiple motors, for making multiple arms rotate; Multiple motor drivers carry out drive control to multiple motors respectively; Power supply powers to multiple motor drivers; Charge and discharge portion is connect with multiple motor drivers, and can be charged by the regenerative current generated by multiple motors; and control enforcement division, control multiple motor drivers. It in industrial robot emergent stopping, cuts off the power, and controls enforcement division and the electric power supplied from charge and discharge portion is used to stop multiple motors when controlling multiple motor drivers.
CN104802166B- A kind of robot control system, including: shooting image acquiring unit, it obtains shooting image; and control portion, it controls robot according to shooting image, shooting image acquiring unit obtains to reflect the assembling object of assembling operation and in assembled object, the shooting image of the most assembled object, control portion is according to shooting image, the characteristic quantity detection carrying out assembled object processes, and according to the characteristic quantity of assembled object, make assembling object move.
CN104802161B- The present invention provides a kind of robot, robot has pedestal, an articulated robotic arm with the fuselage of pedestal connection, rotatably linked with fuselage and the elevating mechanism that fuselage can be made to become lower position and the high position higher than the lower position, when the front end of an articulated robotic arm being made to move predetermined distance when fuselage is lower position compared with the time it takes, the time it takes is longer fuselage makes the front end of an articulated robotic arm move predetermined distance when being high position when.
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. This invention relates to Shape identification Robot with voice command and NLP.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
Before being used in the field, industrial robots are usually put through extensive training procedures. Teach pendants and specialized software are used to ensure that the robots can do repeated jobs accurately. On the other hand, real-world scenarios and practical obstacles are frequently used to train mobile robots, particularly in non-industrial settings. Our project's goal is to build a mobile robot platform that can draw particular geometric shapes—like squares, circles, and rectangles—when given vocal instructions. Bypassing costly software solutions or pre-coded instructions, this strategy differs from conventional approaches. Instead, our novel approach hears vocal instructions, does the required math, and directs the robot to replicate the shapes that are requested.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
FIGURE 2 VOICE COMMAND CAPTURING PROCESS
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Before being used in the field, industrial robots are usually put through extensive training procedures. Teach pendants and specialized software are used to ensure that the robots can do repeated jobs accurately. On the other hand, real-world scenarios and practical obstacles are frequently used to train mobile robots, particularly in non-industrial settings. Our project's goal is to build a mobile robot platform that can draw particular geometric shapes—like squares, circles, and rectangles—when given vocal instructions. Bypassing costly software solutions or pre-coded instructions, this strategy differs from conventional approaches. Instead, our novel approach hears vocal instructions, does the required math, and directs the robot to replicate the shapes that are requested.
The fig1 depicts a multi-component integrated system for a regulated environment. Both visual and audio data are recorded by a vision camera and relayed to a central processing unit via a microphone. This computer, which is powered by a 12V, 7Ah battery, processes all data and accepts input from a keyboard and mouse as well. The microcontroller, which connects with motor drivers and controls four motors with the labels M1, M2, M3, and M4, is in communication with the computing unit. In addition, a Bluetooth modem is connected to the microcontroller, enabling wireless communication with a control room. The control room enables users to communicate with the system by acknowledging commands and data.
Voice input devices are utilized by users to visualize shapes with the help of an Arduino microcontroller, Bluetooth module, gyroscope sensor, sketching tool, and voice input device for command processing. The robot is instructed by the gyroscope sensor, which also interprets commands and determines the path to complete shapes.
An Arduino voice control module is employed to comprehend directives and generate accurate drawings. The robot has been trained to carry out precise tasks such as "Draw a Square". While more complicated shapes, like circles, examine the system's capacity to handle complex instructions, the initial tests evaluate the system's fundamental performance. To enhance performance, corrections are executed.
The shape database of the system can be upgraded to support more intricate shapes, augment speech recognition, and add more sensors for increased efficacy and security. The robot's decisions will be easier to operate and determine through the assistance of a graphical user interface (GUI). This novel approach to train a robot demonstrates how human-robot interaction could potentially be made more intuitive and approachable.
NLP is a significant advancement in the field of voice command processing in mobile robots. In order to provide reliable interpretation in a variety of speech patterns and settings, AI-powered algorithms recognize keywords and contextual elements, manage accents, voice alterations, and background noise, and effectively comprehend spoken instructions. In voice command processing, speech-to-text conversion is the first step, when spoken words are appropriately reproduced by AI models. Trained on massive datasets, machine learning systems are able to recognize spoken language in noisy settings. Classifying instructions, determining actions, and extracting important data are all done by NLP algorithms.
A system of Shape identification Robot with voice command and NLP comprises of Computing Unit (10) for processing data and accepting input from a keyboard and mouse, Vision Camera (11) for capturing visual data, Mike (12), Keyboard and Mouse (13), Battery 12V, 7Ah (14), Microcontroller (23) for communicating with motor drivers and controlling robot movements, Control Room (24), a plurality of Motor Driver 1 (24, 25) and Bluetooth Modem (26) for wireless communication with a control room; wherein the microcontroller is configured to control four motors labeled M1, M2, M3, and M4 to enable the robot to move and perform actions; and voice input device is configured to capture voice commands from a user and transmit them to the Arduino voice control module.
In another embodiment gyroscope sensor is used for interpreting voice commands and determining robot movements; and an Arduino voice control module is attached for processing voice commands and generating robot actions; and a shape database is used for storing information about shapes to be drawn.
In another embodiment the Arduino voice control module is configured to process voice commands and generate corresponding actions for the robot.
In another embodiment the gyroscope sensor is configured to interpret voice commands and determine the direction and speed of the robot's movements.
In another embodiment the shape database is configured to store information about various shapes, including simple shapes like squares and circles, as well as more complex shapes.
In another embodiment the system is configured to use natural language processing (NLP) algorithms to understand and interpret voice commands.
In another embodiment the system is configured to use speech-to-text conversion to convert spoken words into text.
In another embodiment the system is configured to use machine learning algorithms to recognize spoken language in noisy environments.
In another embodiment the system is configured to use a graphical user interface (GUI) to provide a visual representation of the robot's actions and allow the user to interact with the system.
ADVANTAGES OF THE INVENTION
1. Through the application of contextual awareness, AI algorithms are able to translate spoken commands into meaningful instructions by identifying terms and their context.
2. AI-driven NLP is employed to improve voice command interpretation accuracy including handling background noise and different accents.
3. Natural and intuitive interactions are made possible by AI's ability to learn and adapt to various linguistic styles.
4. By enabling speedier command execution, shorter delays, and more system efficiency through real-time processing, AI optimizes system effectiveness.
5. AI systems constantly acquire expertise and skills over time, allowing them to interpret a broader range of instructions.
, Claims:1. A system of Shape identification Robot with voice command and NLP comprises of Computing Unit (10) for processing data and accepting input from a keyboard and mouse, Vision Camera (11) for capturing visual data, Mike (12), Keyboard and Mouse (13), Battery 12V, 7Ah (14), Microcontroller (23) for communicating with motor drivers and controlling robot movements, Control Room (24), a plurality of Motor Driver 1 (24, 25) and Bluetooth Modem (26) for wireless communication with a control room; wherein the microcontroller is configured to control four motors labeled M1, M2, M3, and M4 to enable the robot to move and perform actions; and voice input device is configured to capture voice commands from a user and transmit them to the Arduino voice control module
Wherein a gyroscope sensor is used for interpreting voice commands and determining robot movements; and an Arduino voice control module is attached for processing voice commands and generating robot actions; and a shape database is used for storing information about shapes to be drawn.
2. The system as claimed in claim 1, wherein the Arduino voice control module is configured to process voice commands and generate corresponding actions for the robot.
3. The system as claimed in claim 1, wherein the gyroscope sensor is configured to interpret voice commands and determine the direction and speed of the robot's movements.
4. The system as claimed in claim 1, wherein the shape database is configured to store information about various shapes, including simple shapes like squares and circles, as well as more complex shapes.
5. The system as claimed in claim 1, wherein the system is configured to use natural language processing (NLP) algorithms to understand and interpret voice commands.
6. The system as claimed in claim 1, wherein the system is configured to use speech-to-text conversion to convert spoken words into text.
7. The system as claimed in claim 1, wherein the system is configured to use machine learning algorithms to recognize spoken language in noisy environments.
8. The system as claimed in claim 1, wherein the system is configured to use a graphical user interface (GUI) to provide a visual representation of the robot's actions and allow the user to interact with the system.