1. A voice-controlled robotic hand system, comprising: a 3D-printed robotic hand having multiple degrees of freedom; a microcontroller programmed to interpret voice commands and control servo motors; servo motors operatively connected to the fingers of the robotic hand; an adaptive multi-rate (AMR) voice recognition module configured to receive voice commands; and a communication module, wherein the said communication module facilitates communication between the voice recognition module and the microcontroller.

2. The system of claim 1, wherein the 3D-printed robotic hand is fabricated using a combination of Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modelling (FDM) 3D printing technologies.

3. The system of claim 1, wherein the AMR voice recognition module is capable of recognizing voice commands in multiple languages, including Hindi and English.

4. The system of claim 1, wherein each servo motor is capable of a revolution up to 120º, facilitating gestures corresponding to the voice commands received.

5. The system of claim 1, wherein the system is adapted for interfacing with an Android gadget running the AMR voice recognition application, said interfacing accomplished through the communication module.

6. A method for controlling a robotic hand system, comprising the steps of: receiving a voice command via an AMR voice recognition module; transmitting said voice command to a microcontroller via a communication module; interpreting the received voice command using programmed logic in the microcontroller; and actuating the appropriate servo motors to achieve the desired hand gesture.

7. The method of claim 6, further comprising the step of: selecting the operational language for the AMR voice recognition module from a set comprising Hindi and English.

8. The method of claim 6, wherein the 3D-printed robotic hand used in the method is fabricated using a combination of SLA, DLP, and FDM 3D printing technologies.

9. The method of claim 6, wherein the servo motors are actuated to a maximum rotation of 120º based on the voice command, allowing for a variety of hand gestures.

10. The method of claim 6, wherein the system is remotely interfaced with an Android gadget that runs the AMR voice recognition application, facilitating the initial receipt of the voice command. Voice Controlled Robotic Hand Abstract Disclosed herein, a voice-controlled robotic hand system designed for versatile applications including assistive technologies and human-machine interface systems. The system comprises a 3D-printed robotic hand with multiple degrees of freedom, controlled by servo motors operatively connected to each finger. A microcontroller, programmed to interpret voice commands, controls these servo motors. The system features an Adaptive Multi-Rate (AMR) voice recognition module that is configured to receive and process voice commands. A communication module facilitates the seamless transmission of these voice commands between the voice recognition module and the microcontroller, enabling the robotic hand to execute complex gestures and movements based on user-issued vocal instructions. , C , Claims:Claims :

1. A voice-controlled robotic hand system, comprising: a 3D-printed robotic hand having multiple degrees of freedom; a microcontroller programmed to interpret voice commands and control servo motors; servo motors operatively connected to the fingers of the robotic hand; an adaptive multi-rate (AMR) voice recognition module configured to receive voice commands; and a communication module, wherein the said communication module facilitates communication between the voice recognition module and the microcontroller.

2. The system of claim 1, wherein the 3D-printed robotic hand is fabricated using a combination of Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modelling (FDM) 3D printing technologies.

3. The system of claim 1, wherein the AMR voice recognition module is capable of recognizing voice commands in multiple languages, including Hindi and English.

4. The system of claim 1, wherein each servo motor is capable of a revolution up to 120º, facilitating gestures corresponding to the voice commands received.

5. The system of claim 1, wherein the system is adapted for interfacing with an Android gadget running the AMR voice recognition application, said interfacing accomplished through the communication module.

6. A method for controlling a robotic hand system, comprising the steps of: receiving a voice command via an AMR voice recognition module; transmitting said voice command to a microcontroller via a communication module; interpreting the received voice command using programmed logic in the microcontroller; and actuating the appropriate servo motors to achieve the desired hand gesture.

7. The method of claim 6, further comprising the step of: selecting the operational language for the AMR voice recognition module from a set comprising Hindi and English.

8. The method of claim 6, wherein the 3D-printed robotic hand used in the method is fabricated using a combination of SLA, DLP, and FDM 3D printing technologies.

9. The method of claim 6, wherein the servo motors are actuated to a maximum rotation of 120º based on the voice command, allowing for a variety of hand gestures.

10. The method of claim 6, wherein the system is remotely interfaced with an Android gadget that runs the AMR voice recognition application, facilitating the initial receipt of the voice command.

Description:Voice Controlled Robotic Hand
Field of the Invention
[0001] The present disclosure relates generally to robotic systems and, more specifically, to a voice-controlled robotic hand designed for a range of applications including assistive technologies and human-machine interface systems. The disclosure offers particular utility in enabling individuals with motor impairments, sensory impairments, or communication barriers to perform daily activities, interact with digital interfaces, and communicate using sign language interpreted from voice commands.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] In recent years, robotic systems have seen a remarkable uptick in technological advancements and adoption across various sectors. One of the most compelling applications of robotics is in the development of prosthetic limbs and assistive devices. Traditional prosthetics are often limited in their functionality and can require complex, unintuitive control systems. The advent of more sophisticated control systems, such as myoelectric sensors, has broadened the scope and utility of prosthetics. However, said advanced systems are not devoid of limitations. For instance, myoelectric systems often require a series of muscle contractions, which may be cumbersome and tiring for the user.
[0004] Simultaneously, voice recognition technology has also undergone significant evolution, finding applications from smartphones to home automation systems. Early voice recognition systems, like IBM's Shoebox and Harpy from Carnegie Mellon, laid the groundwork for today's increasingly accurate and responsive systems, such as Apple's Siri and Google's Assistant. However, said advances in voice recognition are only beginning to be incorporated into robotic control systems.
[0005] There have been some attempts to blend voice recognition technology with prosthetics and robotic arms. For instance, an example describes a robotic arm controlled by a variety of inputs, including voice commands. Another example, discloses a voice-controlled manipulator that includes a plurality of joints and links corresponding to the anatomical structure of a human arm. Said systems, although advance, often employ voice control as just one of multiple control inputs and do not focus solely on a system optimized for voice control. Additionally, most of said systems are not designed for widespread, economical adoption, often requiring specialized hardware or software.
[0006] Moreover, the existing technologies have largely been designed for English or other widely spoken languages and are not optimized for multilingual or dialect-specific use. Multilingual or dialect-specific use is particularly significant in countries with diverse linguistic backgrounds where voice-controlled systems might find significant application in overcoming not just physical but also linguistic barriers.
[0007] Thus, there is a need in the art which seeks to advance the field by focusing on a voice-controlled robotic hand that is not only versatile due to its multiple degrees of freedom but also economically feasible and linguistically adaptable. Further, there is a need in the art for a system which aims to capitalize on the advances in both robotics and voice recognition, providing an integrated, user-friendly approach that could bring a wide range of benefits to individuals with different types of impairments or special needs. Utilizing 3D printing technology for the robotic hand ensures a level of customization and scalability that traditional manufacturing methods cannot easily match. Meanwhile, the adaptive multi-rate (AMR) voice recognition module provides a robust platform capable of understanding multiple languages, offering a unique and valuable feature that sets it apart from the existing technologies. The background aims to fill the gap between two rapidly evolving fields of robotics and voice recognition, offering a unified system that leverages the strengths of both to provide a versatile, efficient, and accessible solution.
[0008] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.
[0009] It also shall be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. This invention can be achieved by means of hardware including several different elements or by means of a suitably programmed computer. In the unit claims that list several means, several ones among these means can be specifically embodied in the same hardware item. The use of such words as first, second, third does not represent any order, which can be simply explained as names.
Summary
[00010] Various objects, features, and advantages of the disclosed subject matter can be more fully appreciated with reference to the following detailed description of the disclosed subject matter when considered in connection with the following drawings, in which like reference numerals identify like elements.
[00011] The present disclosure relates generally to robotic systems and, more specifically, to a voice-controlled robotic hand designed for a range of applications including assistive technologies and human-machine interface systems. The disclosure offers particular utility in enabling individuals with motor impairments, sensory impairments, or communication barriers to perform daily activities, interact with digital interfaces, and communicate using sign language interpreted from voice commands.
[00012] The present disclosure pertains to a voice-controlled robotic hand system that integrates advancements in 3D printing, microcontroller technology, voice recognition, and servo motor functionality to create a highly versatile and user-friendly device. At the core of the system is a 3D-printed robotic hand featuring multiple degrees of freedom, which allows for a range of complex movements and gestures. The hand is fabricated using a blend of advanced 3D printing technologies, including Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modelling (FDM), ensuring a durable and precise structure.
[00013] Control over the robotic hand is facilitated by a microcontroller that is programmed to interpret voice commands. Said commands control servo motors that are operatively connected to the fingers of the robotic hand. Each servo motor has a revolution capability of up to 120º, allowing for intricate gestures in response to the voice commands. The microcontroller and servo motors work in tandem to execute the movements, ensuring that the hand performs actions accurately and effectively.
[00014] The system incorporates an Adaptive Multi-Rate (AMR) voice recognition module, configured to receive and process voice commands. Unique to the system is the module's multilingual capabilities, allowing for voice command recognition in multiple languages, including Hindi and English. Multilingual capabilities of the system can be employed for use in diverse linguistic settings, making accessible to a broader range of users.
[00015] Communication between the AMR voice recognition module and the microcontroller is accomplished through a specialized communication module, ensuring seamless transmission of voice commands for real-time control of the robotic hand. Furthermore, the system is adapted to interface with Android gadgets running the AMR voice recognition application, allowing users to operate the system through their smartphones or other Android devices. The interfacing is made possible through the communication module, creating a unified and streamlined control system.
[00016] Hence, the voice-controlled robotic hand system is a technology that leverages state-of-the-art technologies across multiple domains. Significant features such as 3D-printed construction, voice command functionality, multi-language support, and Android compatibility make a robust and flexible solution for various applications, including assistive technologies for differently-abled individuals and advanced human-machine interface systems, are included.
[00017] The present disclosure describes a comprehensive method for controlling a robotic hand system through voice commands, incorporating cutting-edge technologies across various domains including voice recognition, microcontrollers, and mechanical actuation. At the outset, the method involves receiving a voice command through an Adaptive Multi-Rate (AMR) voice recognition module. The module is not merely language-agnostic but can be specifically configured to recognize commands in either Hindi or English, thus broadening the accessibility and utility across diverse linguistic settings.
[00018] Upon receipt of the voice command, the method employs a specialized communication module to transmit the command to a microcontroller. Within the microcontroller, pre-programmed logic interprets the received voice command to determine the subsequent actions. Once the command is understood, the method actuates the corresponding servo motors that are operatively linked to the fingers of a 3D-printed robotic hand. The robotic hand is fabricated using an amalgamation of leading 3D printing technologies—Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modeling (FDM), resulting in a high-quality, durable structure capable of complex movements.
[00019] Notably, the servo motors in the system have a maximum rotation capability of up to 120º, thus enabling a variety of hand gestures ranging from simple to complex based on the voice command received. The high degree of freedom facilitated by said motors allows for nuanced movements and gestures, potentially serving multiple applications from assistive technology to advanced robotics.
[00020] Finally, the method allows for remote interfacing through Android gadgets that run the AMR voice recognition application. The method offers the flexibility of operating the system remotely, while also facilitating the initial receipt and subsequent transmission of voice commands. The feature not only enhances the user experience but also opens up possibilities for tele-operated or automated tasks.
[00021] Thus, the method for controlling a robotic hand system through voice commands offers a nuanced and highly versatile approach to human-machine interaction. The method leverages state-of-the-art technologies in voice recognition, 3D printing, and mechanical actuation to create a user-friendly, adaptable, and highly functional system that can be applied in various fields such as healthcare, automation, and assistive technologies.
Brief Description of the Drawings
[00022] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00023] FIG. 1 showcases a skeletal overview of voice-controlled robotic hand system, according to some embodiments of the present disclosure.
[00024] FIG. 2 portrays a detailed schematic flow chart of a method for controlling a robotic hand system, according to some embodiments of the present disclosure.
[00025] FIG. 3 pictorially depicts a 3D-printed robotic hand having multiple degrees of freedom.
Detailed Description
[00026] The following is a detailed description of exemplary embodiments to illustrate the principles of the invention. The embodiments are provided to illustrate aspects of the invention, but the invention is not limited to any embodiment. The scope of the invention encompasses numerous alternatives, modifications and equivalent; it is limited only by the claims.
[00027] In view of the many possible embodiments to which the principles of the present discussion may be applied, it should be recognized that the embodiments described herein with respect to the drawing figures are meant to be illustrative only and should not be taken as limiting the scope of the claims. Therefore, the techniques as described herein contemplate all such embodiments as may come within the scope of the following claims and equivalents thereof.
[00028] Throughout the present disclosure, the term “network” relates to an arrangement of interconnected programmable and/or non-programmable components that are configured to facilitate data communication between one or more electronic devices and/or databases, whether available or known at the time of filing or as later developed. Furthermore, the network may include, but is not limited to, one or more peer-to-peer network, a hybrid peer-to-peer network, local area networks (LANs), radio access networks (RANs), metropolitan area networks (MANS), wide area networks (WANs), all or a portion of a public network such as the global computer network known as the Internet, a private network, a cellular network and any other communication system or systems at one or more locations.
[00029] Throughout the present disclosure, the term “process”* relates to any collection or set of instructions executable by a computer or other digital system so as to configure the computer or the digital system to perform a task that is the intent of the process.
[00030] Throughout the present disclosure, the term ‘Artificial intelligence (AI)’ as used herein relates to any mechanism or computationally intelligent system that combines knowledge, techniques, and methodologies for controlling a bot or other element within a computing environment. Furthermore, the artificial intelligence (AI) is configured to apply knowledge and that can adapt it-self and learn to do better in changing environments. Additionally, employing any computationally intelligent technique, the artificial intelligence (AI) is operable to adapt to unknown or changing environment for better performance. The artificial intelligence (AI) includes fuzzy logic engines, decision-making engines, preset targeting accuracy levels, and/or programmatically intelligent software.
[00031] The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different instances in the description and the figures may indicate similar or identical items.
[00032] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00033] The present disclosure relates generally to robotic systems and, more specifically, to a voice-controlled robotic hand designed for a range of applications including assistive technologies and human-machine interface systems. The disclosure offers particular utility in enabling individuals with motor impairments, sensory impairments, or communication barriers to perform daily activities, interact with digital interfaces, and communicate using sign language interpreted from voice commands.
[00034] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00035] A voice-controlled robotic hand system 100 represents a remarkable fusion of cutting-edge technologies, seamlessly integrating mechanical engineering, microcontroller programming, voice recognition, and communication modules to create a versatile and interactive device. The system 100 opens up a world of possibilities for human-robot interaction, offering a glimpse into the potential of artificial intelligence and robotics in enhancing our daily lives. Diagrammatic depiction of FIG. 1, illustrates an architectural setup of the system 100 comprising a 3D-printed robotic hand 102, a microcontroller 104, servo motors 106, an adaptive multi-rate (AMR) voice recognition module 108 and a communication module 110, wherein the said communication module facilitates communication between the voice recognition module and the microcontroller.
[00036] In an embodiment, at the core of the system 100 lies a meticulously designed 3D-printed robotic hand, endowed with multiple degrees of freedom. The intricate mechanical structure comprises fingers that can articulate in a manner reminiscent of the human hand's dexterity. Through the combined power of Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modelling (FDM) 3D printing technologies, the robotic hand is brought to life with precision and accuracy. The synergy of said additive manufacturing methods results in a resilient and detailed robotic hand, capable of replicating complex human-like gestures.
[00037] Driving the functionality of the robotic hand is a microcontroller, an intelligent hub programmed to decipher and act upon voice commands. The microcontroller serves as the neural center of the system, orchestrating the movements of the robotic hand's servo motors based on the received voice instructions. By deciphering vocal cues and converting them into actionable commands, the microcontroller acts as the bridge between human intention and machine motion. For instance, an Arduino UNO microcontroller can be employed to cater functionalities of the robotic hand.
[00038] The system's servo motors form the musculature of the robotic hand, intricately connected to the fingers. Each servo motor has the capacity to perform a full revolution of up to 120 degrees. The extensive range of motion allows the robotic hand to replicate a myriad of gestures, closely mirroring the diversity of actions that human hands can execute. When the microcontroller translates voice commands into servo motor actions, the robotic hand elegantly imitates gestures, providing a tangible connection

between human speech and mechanical motion. For instance, instructing the robotic hand to close fingers could signify the act of grasping an object, and vice versa. MG995 servo motor can be deployed for performing a full revolution of up to 120 degrees, enabling the robotic hand to replicate a myriad of gestures.
[00039] The true marvel of the system 100 lies in the adaptive multi-rate (AMR) voice recognition module. The module has been meticulously engineered to comprehend and process human speech across multiple languages, including languages as distinct as Hindi and English. The versatility in language recognition makes the system accessible and usable for a broader user base, transcending linguistic barriers. By harnessing advanced machine learning algorithms, the AMR voice recognition module transforms spoken words into digital signals, allowing the microcontroller to accurately interpret and translate said signals into actionable tasks for the robotic hand. The proficiency in recognizing various languages empowers the user to communicate with the robotic hand in their preferred tongue, thereby making the interaction more intuitive and natural.
[00040] To facilitate seamless communication between the various components of the system, a dedicated communication module is integrated. The module functions as a conduit, enabling smooth data exchange between the AMR voice recognition module and the microcontroller. The communication module ensures that the voice commands recognized by the AMR module are promptly relayed to the microcontroller, enabling rapid and precise execution of corresponding actions by the robotic hand. The real-time interaction underscores the system's responsiveness and enhances the user experience, as the robotic hand seems to effortlessly follow vocal directives. For instance, Bluetooth module HC-05 can act as the communication module, enabling smooth data exchange between the AMR voice recognition module and the microcontroller.
[00041] Furthermore, the system 100 is designed with an eye toward integration and compatibility. The system can be seamlessly interfaced with Android gadgets running the AMR voice recognition application. The integration is facilitated through the communication module, effectively connecting the Android device to the robotic hand. The integration adds an extra layer of convenience, allowing users to control the robotic hand from their familiar Android devices, leveraging the power of modern smartphones and tablets as control interfaces.
[00042] Referring to one or more preceding embodiments, the voice-controlled robotic hand system 100 represents a remarkable convergence of engineering, technology, and human interaction. With the 3D-printed mechanical intricacy, microcontroller intelligence, language-adaptive voice recognition, and seamless communication capabilities, system 100 stands as a testament to the boundless potential of constructive research. The system not only showcases the rapid advancements in robotics but also highlights the exciting possibilities for human-robot collaboration, where a simple vocal command can seamlessly translate into intricate robotic gestures. As technology continues to evolve, systems like the voice-controlled robotic hand will likely be the catalysts for revolutionizing the way we interact with and harness the capabilities of machines.
[00043] In the realm of robotics, where comprehensive explorative and human ingenuity intersect, a method 200 for controlling a robotic hand system stands as a testament to the strides made in merging technology with human communication. The method 200 offers an intricate dance of hardware and software, where voice commands metamorphose into graceful hand gestures through the synergy of an adaptive multi-rate (AMR) voice recognition module, a microcontroller, servo motors, and a communication module. The seamless fusion of components demonstrates the intricacy of controlling a robotic hand system and reflects the boundless possibilities of human-robot interaction.
[00044] Pictorial portrayal of FIG. 2, represents a flow diagram of the method 200 for controlling a robotic hand system, comprising the steps of (at step 202) receiving a voice command via an AMR voice recognition module, (at step 204) transmitting said voice command to a microcontroller via a communication module, (at step 206) interpreting the received voice command using programmed logic in the microcontroller, and (at step 208) actuating the appropriate servo motors to achieve the desired hand gesture.
[00045] At the heart of the method 200 lies the AMR voice recognition module, a module designed to decipher and interpret the subtleties of human speech. The process commences with the receipt of a voice command such as an audible instruction that holds the potential to translate human intention into machine action. For instance, a user could verbally express the desire for the robotic hand to 'grab an object' or 'wave hello.' The voice command, laden with the nuances of tone and inflection, is the gateway to unlocking the robotic hand's potential.
[00046] The AMR voice recognition module, through advanced algorithms and neural networks, analyses the received voice command. Notably, the method is capable of recognizing voice commands in various languages, including the complex tonal shifts of languages like Hindi and the nuanced articulation of English. Consider a scenario where a user, fluent in Hindi, instructs the robotic hand to 'uthao', a Hindi term for 'lift.' The AMR module deciphers the command, a linguistic representation of the user's intent, thereby acting as a universal translator between human speech and machine execution.
[00047] Following the successful recognition of the voice command, the next step in the method is the transmission of the command to the microcontroller. The microcontroller serves as the intelligence hub, orchestrating the subsequent sequence of actions. Imagine the voice command 'greet', the microcontroller receives the linguistic prompt and begins deciphering semantics. The microcontroller's programmed logic parses the voice command, determining the appropriate hand gesture to fulfil the user's intent.
[00048] Drawing from the repository of pre-programmed instructions, the microcontroller identifies the specific servo motors required to enact the desired gesture. Each servo motor is a vital cog in the intricate machinery of the robotic hand, responsible for the movement of individual fingers. The microcontroller seamlessly coordinates the rotation of said servo motors, ensuring they collectively articulate in a manner that mimics human-like gestures. The orchestration happens within fractions of a second, showcasing the microcontroller's real-time processing capabilities. For example, upon receiving the voice command 'fist,' the microcontroller engages the servo motors to close the fingers into a fist-like configuration, demonstrating the direct translation of voice into motion.
[00049] The servo motors are the mechanical embodiment of the method's finesse. As the microcontroller deciphers the voice command's intention, triggers said servo motors to move, each capable of rotation up to 120 degrees. The extensive range of motion endows the robotic hand with the ability to replicate a diverse array of gestures, from simple clenches to complex handshakes. Consider the voice command 'thumbs up', the microcontroller activates the servo motors responsible for the thumb's movement, directing them to perform the requisite rotation, resulting in the iconic thumbs-up gesture.
[00050] The culmination of said intricate steps is the robotic hand's graceful execution of the desired hand gesture. Through the AMR voice recognition module, the microcontroller, and the meticulously coordinated servo motor actions, the robotic hand flawlessly mirrors the user's vocalized intent. The culmination is a tangible testament to the symbiosis between human cognition and machine precision. An example can be the voice command 'open,' causing the robotic hand to extend fingers and reveal an open-palmed gesture.
[00051] Moreover, the method 200 extends the prowess to linguistic adaptability. The step of selecting the operational language for the AMR voice recognition module further emphasizes the system's user-centric approach. By permitting users to choose from a set of languages, including Hindi and English, the method accommodates linguistic diversity. Consider a scenario where a user fluent in Hindi instructs the robotic hand to 'shake hands.' The AMR module, having been set to Hindi as the operational language, accurately recognizes the command and initiates the corresponding handshake gesture, illustrating the method's language-savvy functionality.
[00052] The method's versatility extends beyond linguistic adaptability, delving into the realm of additive manufacturing. The robotic hand's fabrication through a combination of Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modelling (FDM) 3D printing technologies attests to the fusion of craftsmanship and technology. The amalgamation ensures that the robotic hand exhibits not only aesthetic finesse but also the mechanical robustness needed for intricate gestures. Imagine the voice command 'point', the robotic hand swiftly extends the index finger, replicating the subtle motion of pointing towards an object of interest.
[00053] Furthermore, the method's integration with an Android gadget adds an additional layer of convenience. The integration capitalizes on the Android platform's ubiquity and user-friendliness, enabling remote interfacing through the AMR voice recognition application. A user, comfortably situated with their Android device, issues a voice command. The command is relayed to the robotic hand system through the communication module, marking the initiation of the method's journey. The Android gadget acts as the conduit through which the user's voice command traverses into the microcontroller's domain, showcasing the method's ability to seamlessly bridge user devices with robotic action. According to an illustration made in FIG. 3, pictorially depicts the 3D-printed robotic hand having multiple degrees of freedom. The 3D-printed robotic hand with multiple degrees of freedom (DoF) can be considered as a mechanical assembly designed to mimic the movements and capabilities of a human hand. The term "degrees of freedom," can refer to, yet not limited to the number of ways in which the robotic hand can move or articulate. In the case of a hand, could include flexing and extending the fingers, rotating the wrist, and perhaps even abducting and adducting the fingers (spreading them apart or bringing them together). For instance, the robotic hand would have 5 fingers. Each finger may have multiple joints to provide flexion and extension.
[00054] Referring to the preceding embodiment, the thumb might have additional DoF for rotation to enable grasping. Wrist part may rotate and bend to further enhance the hand's dexterity. Base part that connects the robotic hand to an arm or a fixed surface. Actuators/Servos are the "muscles" allowing the hand to move, and they are usually hidden inside the structure or sometimes external to the hand. Additionally, sensors can be configured to provide feedback on the hand’s position or the force being applied.
[00055] Referring to the preceding embodiment, circles or dots may represent joints where movement can occur. Arrows could be used to indicate the directions in which each joint can move. Numbers/Text may be added to indicate the number of DoFs at each joint or to label components. Wiring and Electronics could be sketched to show connections to actuators or sensors. Different colors might denote different materials used in the 3D printing process.
[00056] Referring to the preceding embodiment, if each finger has 3 DoF, they may be depicted with arrows showing the possible directions of movement at each joint. An additional circular arrow could depict rotation around its base. Arrows could show wrist rotation and flexion/extension. A separate picture could show the hand in a grasping posture, indicating how the DoFs contribute to this function. Thus, the pictorial depiction would aim to illustrate said elements in a clear, informative way, helping the viewer understand both the construction and capabilities of the robotic hand.
[00057] Referring to one or more preceding embodiments, the method 200 for controlling a robotic hand system encapsulates the quintessence of human ingenuity and technological advancement. Through the harmonious interplay of the AMR voice recognition module, the microcontroller, servo motors, and the communication module, the method stands as a testament to the potential of voice-controlled robotics. The voice command, laden with the user's intent and linguistic nuances, transforms into a meticulously choreographed hand gesture, bridging the divide between human expression and mechanical response. As the method 200 continues to evolve and intertwine with the ever-progressing landscape of robotics, the method 200 showcases the transformative power of technology in augmenting human-robot interaction.
[00058] The above description is intended to be illustrative, and not restrictive. Although the present disclosure has been described with references to specific illustrative examples and implementations, it will be recognized that the present disclosure is not limited to the examples and implementations described. The scope of the disclosure should be determined with reference to the following claims, along with the full scope of equivalents to which the claims are entitled.
[00059] Modifications, additions, or omissions may be made to the systems and apparatuses described herein without departing from the scope of the disclosure. The components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses may be performed by more, fewer, or other components. Additionally, operations of the systems and apparatuses may be performed using any suitable logic comprising software, hardware, and/or other logic. As used in this document, “each” refers to each member of a set or each member of a subset of a set.
[00060] The term “memory,” as used herein relates to a volatile or persistent medium, such as a magnetic disk, or optical disk, in which a computer can store data or software for any duration. Optionally, the memory is non-volatile mass storage such as physical storage media. Furthermore, a single memory may encompass and in a scenario wherein computing system is distributed, the processing, memory and/or storage capability may be distributed as well.
[00061] Throughout the present disclosure, the term ‘server’ relates to a structure and/or module that include programmable and/or non-programmable components configured to store, process and/or share information. Optionally, the server includes any arrangement of physical or virtual computational entities capable of enhancing information to perform various computational tasks.

Claims
I/We Claim:
1. A voice-controlled robotic hand system, comprising:
a 3D-printed robotic hand having multiple degrees of freedom;
a microcontroller programmed to interpret voice commands and control servo motors;
servo motors operatively connected to the fingers of the robotic hand;
an adaptive multi-rate (AMR) voice recognition module configured to receive voice commands; and
a communication module, wherein the said communication module facilitates communication between the voice recognition module and the microcontroller.
2. The system of claim 1, wherein the 3D-printed robotic hand is fabricated using a combination of Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modelling (FDM) 3D printing technologies.
3. The system of claim 1, wherein the AMR voice recognition module is capable of recognizing voice commands in multiple languages, including Hindi and English.
4. The system of claim 1, wherein each servo motor is capable of a revolution up to 120º, facilitating gestures corresponding to the voice commands received.
5. The system of claim 1, wherein the system is adapted for interfacing with an Android gadget running the AMR voice recognition application, said interfacing accomplished through the communication module.
6. A method for controlling a robotic hand system, comprising the steps of:
receiving a voice command via an AMR voice recognition module;
transmitting said voice command to a microcontroller via a communication module;
interpreting the received voice command using programmed logic in the microcontroller; and
actuating the appropriate servo motors to achieve the desired hand gesture.
7. The method of claim 6, further comprising the step of:
selecting the operational language for the AMR voice recognition module from a set comprising Hindi and English.
8. The method of claim 6, wherein the 3D-printed robotic hand used in the method is fabricated using a combination of SLA, DLP, and FDM 3D printing technologies.
9. The method of claim 6, wherein the servo motors are actuated to a maximum rotation of 120º based on the voice command, allowing for a variety of hand gestures.
10. The method of claim 6, wherein the system is remotely interfaced with an Android gadget that runs the AMR voice recognition application, facilitating the initial receipt of the voice command.

Voice Controlled Robotic Hand
Abstract
Disclosed herein, a voice-controlled robotic hand system designed for versatile applications including assistive technologies and human-machine interface systems. The system comprises a 3D-printed robotic hand with multiple degrees of freedom, controlled by servo motors operatively connected to each finger. A microcontroller, programmed to interpret voice commands, controls these servo motors. The system features an Adaptive Multi-Rate (AMR) voice recognition module that is configured to receive and process voice commands. A communication module facilitates the seamless transmission of these voice commands between the voice recognition module and the microcontroller, enabling the robotic hand to execute complex gestures and movements based on user-issued vocal instructions. , C , Claims:Claims
I/We Claim:
1. A voice-controlled robotic hand system, comprising:
a 3D-printed robotic hand having multiple degrees of freedom;
a microcontroller programmed to interpret voice commands and control servo motors;
servo motors operatively connected to the fingers of the robotic hand;
an adaptive multi-rate (AMR) voice recognition module configured to receive voice commands; and
a communication module, wherein the said communication module facilitates communication between the voice recognition module and the microcontroller.
2. The system of claim 1, wherein the 3D-printed robotic hand is fabricated using a combination of Stereo Lithography (SLA), Digital Light Processing (DLP), and Fused Deposition Modelling (FDM) 3D printing technologies.
3. The system of claim 1, wherein the AMR voice recognition module is capable of recognizing voice commands in multiple languages, including Hindi and English.
4. The system of claim 1, wherein each servo motor is capable of a revolution up to 120º, facilitating gestures corresponding to the voice commands received.
5. The system of claim 1, wherein the system is adapted for interfacing with an Android gadget running the AMR voice recognition application, said interfacing accomplished through the communication module.
6. A method for controlling a robotic hand system, comprising the steps of:
receiving a voice command via an AMR voice recognition module;
transmitting said voice command to a microcontroller via a communication module;
interpreting the received voice command using programmed logic in the microcontroller; and
actuating the appropriate servo motors to achieve the desired hand gesture.
7. The method of claim 6, further comprising the step of:
selecting the operational language for the AMR voice recognition module from a set comprising Hindi and English.
8. The method of claim 6, wherein the 3D-printed robotic hand used in the method is fabricated using a combination of SLA, DLP, and FDM 3D printing technologies.
9. The method of claim 6, wherein the servo motors are actuated to a maximum rotation of 120º based on the voice command, allowing for a variety of hand gestures.
10. The method of claim 6, wherein the system is remotely interfaced with an Android gadget that runs the AMR voice recognition application, facilitating the initial receipt of the voice command.