Intelligent Autonomous Robot Module System Based on On-Device Artificial Intelligence and Multi-Sensor Fusion Technology

Abstract

The present invention relates to an intelligent autonomous driving robot module system based on on-device artificial intelligence and multi-sensor fusion technology, comprising the steps of: collecting sensor data to recognize and analyze an environment; designing an autonomous driving path based on said data; moving along said designed path and avoiding obstacles; and adapting to various environments and working conditions through a modular design.

Description

Technology Field

[0001] The present invention relates to intelligent autonomous driving robot technology, and more specifically, to an intelligent autonomous driving robot module system based on on-device artificial intelligence and multi-sensor fusion technology that analyzes the surrounding environment in real time based on sensor fusion and computer vision and performs tasks through autonomous driving path design and tracking algorithms. Background Technology

[0003] Autonomous driving robot technology is utilized in various industries such as military, agriculture, and logistics, and recently, there has been an increasing demand for service robots for the aging society and vulnerable groups, including the disabled. Existing autonomous driving technologies have suffered from poor flexibility due to designs primarily specialized for specific tasks, and their adaptability to environmental changes has been limited because they fail to comprehensively process sensor data. This invention overcomes these limitations of existing technology to provide a solution capable of operating flexibly in diverse environments through an installable / attachable module. Prior art literature

[0005] Korean Registered Patent No. 10-0882920, Korean Registered Patent No. 10-1353532, Korean Registered Patent No. 10-2196483, Korean Registered Patent No. 10-2216824 The problem to be solved

[0006] The objective of the present invention is to provide an intelligent service robot for supporting the daily lives of the elderly and people with disabilities.

[0007] The objective of the present invention is to reduce production costs and improve resource utilization efficiency by introducing a modularized robot system in industrial sites.

[0008] The objective of the present invention is to overcome the limitations of existing robots by providing an adaptive robot structure capable of flexibly responding to environmental changes.

[0009] The problems that the present invention aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by a person skilled in the art from the description below. means of solving the problem

[0011] A first aspect of the present invention for achieving the above objective comprises the steps of: collecting sensor data to recognize and analyze an environment; designing an autonomous driving path based on the data; moving along the designed path and avoiding obstacles; and being adaptable to various environments and working conditions through a modular design.

[0012] Preferably, the method may include the step of generating accurate environmental information by integrating multiple sensor data (e.g., LiDAR, camera, ultrasonic sensor) through sensor fusion, and the step of identifying fixed obstacles and moving obstacles based on the environmental information and generating a path plan that can respond thereto.

[0013] Preferably, the path planning stage may include a step of optimizing the path according to environmental characteristics to adapt to indoor and outdoor environments, and a step of generating a new path in real time when an obstacle is detected. Effects of the invention

[0014] As described above, according to the present invention, by integrally applying sensor fusion technology and computer vision technology, the robot can operate stably and efficiently even in complex and dynamic environments.

[0015] In addition, the modular design of the present invention allows for the flexible customization of robot functions according to various user requirements, thereby providing expandability in application fields.

[0016] In addition, the present invention can significantly improve the safety and work performance quality of service robots by applying an advanced obstacle avoidance algorithm and an autonomous driving system.

[0017] In addition, the present invention is designed to enable easy installation and maintenance while maintaining compatibility with existing industrial facilities, thereby ensuring practicality and economic efficiency in industrial sites. Brief explanation of the drawing

[0019] FIG. 1 is a drawing of an intelligent autonomous driving robot module system according to a preferred embodiment of the present invention. FIG. 2 is a drawing of an intelligent autonomous driving robot module system according to one embodiment. FIG. 3 is a drawing of an intelligent autonomous driving robot module system according to one embodiment. FIGS. 4 to 6 are block diagrams of an intelligent autonomous driving robot module system according to one embodiment. FIG. 7 is a drawing of an intelligent autonomous driving robot module system according to one embodiment. FIGS. 8 and 9 are exemplary diagrams illustrating an extended intelligent autonomous driving robot module system according to one embodiment. FIG. 10 is an illustrative diagram for explaining an intelligent autonomous driving robot module system according to one embodiment. Specific details for implementing the invention

[0020] The advantages and features of the present invention and the methods for achieving them will become clear from the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components. "And / or" includes each of the mentioned items and all combinations of one or more.

[0021] Although terms such as "first," "second," etc. are used to describe various elements, components, and / or sections, it goes without saying that these elements, components, and / or sections are not limited by these terms. These terms are used merely to distinguish one element, component, or section from another. Accordingly, it goes without saying that the first element, first component, or first section mentioned below may be a second element, second component, or second section within the technical scope of the present invention.

[0022] Furthermore, the identifiers (e.g., a, b, c, etc.) for each step are used for convenience of explanation and do not describe the order of the steps; the steps may occur differently from the specified order unless a specific order is clearly indicated in the context. That is, the steps may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

[0023] The terms used herein are for describing the embodiments and are not intended to limit the invention. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used herein, “comprises” and / or “comprising” do not exclude the presence or addition of one or more other components, steps, actions, and / or elements to the mentioned components, steps, actions, and / or elements.

[0024] Unless otherwise defined, all terms used in this specification (including technical and scientific terms) may be used in a meaning that is commonly understood by those skilled in the art to which the present invention pertains. Additionally, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise.

[0025] Furthermore, in describing the embodiments of the present invention, if it is determined that a detailed description of known functions or configurations could unnecessarily obscure the essence of the invention, such detailed description will be omitted. Additionally, the terms described below are defined considering the functions in the embodiments of the present invention, and these may vary depending on the intentions or conventions of the user or operator. Therefore, such definitions should be based on the content throughout this specification.

[0027] FIG. 1 is a drawing of an intelligent autonomous driving robot module system according to a preferred embodiment of the present invention.

[0028] Referring to FIG. 1, an intelligent autonomous driving robot module system relates to an autonomous driving robot that utilizes sensor fusion and computer vision to understand the surrounding environment, designs a path based on the information, and then follows it through a driving module. The robot has a modular design that can adapt to various work environments and requirements, and is a highly compatible, installable intelligent robot capable of flexibly responding to environmental changes.

[0029] Figure 1 is a diagram illustrating the module configuration and interaction of an autonomous driving robot. Figure 1 explains the connectivity and data flow between major modules and highlights the structural flexibility of the modular design.

[0031] FIG. 2 is a drawing of an intelligent autonomous driving robot module system according to one embodiment.

[0032] An autonomous driving robot according to one embodiment of the present invention is equipped with an on-device AI system to analyze the surrounding environment in real time and design an optimal driving path. The on-device AI system is implemented by utilizing edge computing technology to enable immediate decision-making without communication delay with a cloud server.

[0033] In addition, the present invention generates a high-precision environment map by fusing data collected from multiple sensors, such as LiDAR sensors, ultrasonic sensors, and cameras, in real time. Based on the generated environment map, a dynamic obstacle avoidance algorithm is executed, and an optimal movement path is designed through a path planning technique such as the A* algorithm.

[0034] As another feature of the present invention, the mechanical structure of the robot is designed to be modular. Each module is interconnected through a standardized interface, and necessary modules can be added or replaced depending on the work environment or industrial requirements. For example, a gripper module for logistics tasks, a brush module for cleaning tasks, etc., can be mounted as needed.

[0035] Through this configuration, the autonomous driving robot of the present invention can perform tasks efficiently and stably in various industrial sites.

[0037] FIG. 3 is a drawing of an intelligent autonomous driving robot module system according to one embodiment.

[0038] The autonomous driving robot of the present invention comprises a sensor fusion module, an on-device AI module, a modular design platform, a driving module, and a communication module.

[0039] The sensor fusion module integrates and processes data collected from various sensors, such as cameras, ultrasonic sensors, and infrared sensors, in real time. Data collected from each sensor is fused through algorithms such as Kalman filters to generate accurate and reliable environmental information.

[0041] The on-device AI module directly processes sensor data using a processor mounted inside the robot and performs autonomous decision-making based on pre-trained AI models. This enables immediate response without communication delays with external servers.

[0042] The modular design platform consists of the robot's computing, drive, and power supply units as independent modules, allowing each part to be replaced or upgraded individually. Standardized interfaces enable various module combinations according to user requirements, which enhances the robot's scalability and maintainability.

[0043] The drive module moves the robot along a path designed by the on-device AI module and controls it to avoid obstacles detected in real time. Precise position control is possible through motor controllers and encoders.

[0044] The communication module supports various wireless communication protocols such as Wi-Fi and Bluetooth, and enables remote monitoring and control, particularly through integration with smartphone applications.

[0045] Through such a configuration, the autonomous driving robot of the present invention enables efficient and stable operation and can satisfy various user requirements.

[0046] FIGS. 4 to 6 are block diagrams of an intelligent autonomous driving robot module system according to one embodiment.

[0047] FIG. 4 is a flowchart showing the main operation steps of an autonomous driving robot according to an embodiment of the present invention.

[0048] The autonomous driving robot of the present invention is an intelligent robot that analyzes the environment and performs autonomous driving by utilizing on-device AI and sensor fusion technology, and the operation of each step is described in detail below.

[0049] First, autonomous robots collect surrounding environment data through various sensors, such as cameras, ultrasonic sensors, and infrared sensors. The collected sensor data is integrated and processed through sensor fusion algorithms to accurately recognize and analyze the environment. At this time, algorithms such as Kalman filters are applied to remove noise and generate reliable environmental information.

[0050] Next, the on-device AI system designs the optimal autonomous driving path based on the analyzed environmental data. In the path design phase, path planning techniques such as the A* algorithm are utilized to generate an efficient route to the destination. During this process, the locations of static obstacles and traversable areas are considered.

[0051] Based on the designed path, the robot performs actual movement and ensures safe driving by utilizing a real-time avoidance algorithm for dynamic obstacles detected during movement. At this time, the robot's drive system performs precise position control through motor controllers and encoders to accurately follow the designed path.

[0052] As a characteristic feature of the present invention, the robot adopts a modular design to flexibly respond to various environments and working conditions. Each module is connected through a standardized interface, and necessary modules can be added or replaced according to changes in the working environment or requirements. This modular structure significantly enhances the scalability and adaptability of the robot.

[0053] Through such step-by-step processing, the autonomous driving robot of the present invention performs efficient and stable autonomous driving and can be utilized in various environments.

[0054] FIG. 5 is a conceptual diagram illustrating the process of sensor fusion-based obstacle recognition and path design according to an embodiment of the present invention.

[0055] The present invention provides a method for implementing accurate environmental recognition through the fusion of multi-sensor data and performing efficient path planning based thereon. The specific processing steps are described in detail below.

[0056] The present invention first collects data from various sensors, such as LiDAR, cameras, and ultrasonic sensors. LiDAR sensors provide 3D point cloud data, enabling precise distance measurement, while cameras capture the visual features of objects through RGB images. Ultrasonic sensors are used for detecting obstacles at close range. This multi-sensor data is integrated and processed through a sensor fusion algorithm.

[0057] In the sensor fusion process, weight-based fusion is performed considering the characteristics and reliability of each sensor. For example, high weight is assigned to LiDAR data for long-distance obstacle detection, while camera data is primarily used for object recognition. Through this fusion process, the strengths of each sensor can be maximized while compensating for the limitations of a single sensor.

[0058] Based on fused sensor data, the system classifies obstacles in the environment into stationary and mobile obstacles. Stationary obstacles refer to objects whose positions do not change, such as walls or pillars, while mobile obstacles include objects whose positions change dynamically, such as pedestrians or other moving entities.

[0059] Based on identified obstacle information, the system plans a safe and efficient path. During the path planning phase, a basic path is first established to avoid fixed obstacles, and a flexible plan is formulated for moving obstacles to enable real-time path modifications. At this stage, various factors such as safety distance from obstacles, energy efficiency, and path smoothness are comprehensively considered.

[0060] Through this sensor fusion-based environment perception and path planning method, the present invention can achieve stable and efficient autonomous driving even in complex environments.

[0061] FIG. 6 is a conceptual diagram illustrating an environment-adaptive path planning and obstacle avoidance process according to an embodiment of the present invention.

[0062] The present invention relates to a method for providing path optimization and real-time obstacle avoidance functions that consider the characteristics of indoor and outdoor environments, and each processing step is described in detail below.

[0063] In the path planning phase, it is first determined whether the current environment is indoors or outdoors. In indoor environments, where narrow spaces and standardized structures predominate, precise position control and maneuverability within confined spaces are critical. To this end, the system calculates the minimum turning radius by considering the structural characteristics of the indoor space and generates a path while maintaining a safety distance aligned with the passageway width.

[0064] In outdoor environments, route planning is performed by considering various environmental factors such as weather changes, terrain characteristics, and illumination variations. The system derives a safe and efficient route by analyzing information such as terrain slope, road surface conditions, and ambient brightness. In particular, for outdoor use, a combination of approximate route planning utilizing GPS signals and precise route generation using local sensors is employed.

[0065] The obstacle avoidance function operates in real-time to respond to unexpected obstacles. The system continuously monitors the surrounding environment and immediately re-evaluates the current path when an obstacle is detected. The following factors are considered when generating a new path:

[0066] First, calculate a path that can efficiently reach the target point while maintaining a minimum safe distance from obstacles.

[0067] Second, it predicts the direction and speed of obstacles to prevent potential future collisions in advance.

[0068] Third, when switching to a new path, the robot's current motion state is taken into account to ensure a smooth path transition.

[0069] Through such environment-adaptive path planning and real-time avoidance functions, the present invention can implement stable and efficient autonomous driving in various environments.

[0070] FIG. 7 is a drawing of an intelligent autonomous driving robot module system according to one embodiment.

[0071] The present invention provides a modular design method that allows for flexible configuration according to user requirements by modularizing the main components of a robot. The configuration and connection method of each module are described in detail below.

[0072] The computation module handles the core calculations required for autonomous driving, and processors of various performance levels can be selectively installed depending on the usage environment and required computational capabilities. Optimal configurations tailored to the situation are possible, such as using a low-power processor for basic autonomous driving or a high-performance processor for advanced real-time image processing.

[0073] The drive module is the part responsible for the robot's actual movement and consists of a motor and a drive mechanism. It offers a variety of options, ranging from small wheeled drive modules for indoor use to large drive modules capable of driving on rough terrain outdoors. Each drive module is connected to the robot body via a standardized mechanical interface, and the connectors for electrical connection are also standardized.

[0074] The power supply module is directly related to the robot's operating time, allowing for the selection of battery capacity and charging methods. It enables the optimal power configuration tailored to operating conditions, such as selecting a high-capacity battery when long-term operation is required or a small battery when weight reduction is important.

[0075] Connections between modules are established through standardized interfaces. Since fastening structures for mechanical coupling and connectors for electrical signal and power transmission are designed to consistent specifications, users can replace modules without special tools or expertise.

[0076] Through this modular design, users can gain the following benefits:

[0077] First, you can optimize costs by selecting only the necessary features during the initial purchase.

[0078] Second, if performance improvement is required during operation, only the relevant module can be upgraded.

[0079] Third, maintenance is easy because only the problematic module is replaced in the event of a failure.

[0080] Through such a modular design method, the present invention provides a flexible robot platform that can effectively meet the diverse requirements of users.

[0081] FIGS. 8 and 9 are exemplary diagrams illustrating an extended intelligent autonomous driving robot module system according to one embodiment.

[0082] Referring to FIG. 8, an autonomous driving robot can be configured by combining various functional modules on a base platform that performs basic autonomous driving functions. Through this modular configuration, necessary functions can be selectively added or removed to meet the specific requirements of each industrial sector, such as agriculture, logistics, and medical care.

[0083] For example, in the agricultural sector, it can be utilized as a smart farm robot by adding modules such as crop monitoring sensors, pesticide sprayers, and harvesting equipment. In the logistics sector, it can perform logistics transport tasks in warehouses or factories by equipping it with item loading / unloading modules, barcode scanners, and gripping devices. In the medical field, it can be used for transporting supplies and disease prevention tasks within hospitals by combining modules for transporting medical devices, disinfection devices, and patient monitoring sensors.

[0084] As such, the autonomous driving robot of the present invention has the advantage of being able to provide optimized functions tailored to the requirements of various industrial sites through a modular structure, and to flexibly change its configuration according to the purpose of use.

[0085] Referring to FIG. 9, the autonomous driving robot of the present invention is equipped with on-device AI technology, thereby minimizing dependence on communication with an external server or cloud. Since the AI ​​model mounted on the robot performs data processing and decision-making directly within the robot, stable operation is possible even in environments where network connectivity is unstable or impossible.

[0086] One of the major advantages of on-device AI technology is enhanced data security. Since all data collected and processed by robots is handled directly within the device rather than being transmitted externally, security threats that may occur during data transmission can be fundamentally blocked. In particular, this minimizes the risk of personal information leaks or corporate secrets in environments handling sensitive information, such as medical institutions or manufacturing sites.

[0087] This on-device AI technology enhances robot autonomy and strengthens security, while also providing additional benefits such as reducing cloud server operating costs and preventing performance degradation caused by network latency.

[0088] FIG. 10 is an exemplary diagram illustrating an intelligent autonomous driving robot module system according to one embodiment.

[0089] The autonomous driving robot of the present invention is designed with a structure capable of operating independently of a communication network. The robot can perform all functions necessary for autonomous driving, such as recognizing the surrounding environment, planning a path, and avoiding obstacles, through its own sensors, processor, and storage device.

[0090] In particular, the robot's autonomous driving function remains operational even when the network connection is unstable or completely severed. This is because the robot can determine its location and calculate the optimal path by utilizing its own map data and real-time sensor information. Furthermore, it can respond independently in the event of an emergency according to pre-programmed safety protocols.

[0091] This network-independent operation method enables the provision of stable services even in environments where communication infrastructure is insufficient or in the event of network failures, and can significantly expand the scope of robot utilization.

[0092] Meanwhile, the steps of the method or algorithm described in connection with the embodiments of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or implemented by a combination thereof. The software module may reside in RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, a hard disk, a removable disk, a CD-ROM, or any form of computer-readable recording medium well known in the art to which the present invention belongs.

[0093] The components of the present invention may be implemented as a program (or application) and stored on a medium to be executed in combination with a computer, which is hardware. The components of the present invention may be implemented as software programming or software elements, and similarly, embodiments may be implemented in programming or scripting languages ​​such as C, C++, Java, assembler, etc., including various algorithms implemented as combinations of data structures, processes, routines, or other programming configurations. Functional aspects may be implemented as algorithms executed on one or more processors.

[0095] Although preferred embodiments of the livestock disease prediction method and apparatus according to the present invention have been described above, the present invention is not limited thereto and can be implemented with various modifications within the scope of the claims, the detailed description of the invention, and the attached drawings, and such modifications are also included in the present invention.

Claims

Claim 1 An intelligent robot module that utilizes on-device AI and sensor fusion to analyze an environment, design an autonomous driving path, and follow it, characterized by a step of collecting sensor data to recognize and analyze the environment, a step of designing an autonomous driving path based on the analyzed data, a step of moving along the designed path and avoiding obstacles, and an intelligent autonomous driving robot module system capable of adapting to various environments and working conditions through a modular design. Claim 2 An intelligent autonomous driving robot module system according to claim 1, characterized by integrating multiple sensor data (e.g., LiDAR, camera, ultrasonic sensor) through sensor fusion to generate accurate environmental information, and including a path plan capable of identifying fixed obstacles and moving obstacles and responding thereto based on said information. Claim 3 An intelligent autonomous driving robot module system according to paragraph 2, characterized by including a step of optimizing a path according to environmental characteristics to adapt to indoor and outdoor environments during the path planning stage, and generating a new path in real time when an obstacle is detected. Claim 4 An intelligent autonomous driving robot module system according to paragraph 2, characterized by providing a structure that allows the computational unit, driving unit, and power supply unit of the robot to be independently replaced or upgraded through a modular design, and enabling customized combinations according to user requirements. Claim 5 An intelligent autonomous driving robot module system according to claim 4, characterized in that the autonomous driving robot can be applied to various industrial fields such as agriculture, logistics, and medical through various module combinations, and functions can be added or removed according to the specific requirements of each industry. Claim 6 An intelligent autonomous driving robot module system according to claim 1, characterized in that the robot's on-device AI technology can eliminate communication dependency, enhance data security, and minimize the risk of personal information leakage. Claim 7 An intelligent autonomous driving robot module system according to claim 6, characterized in that the autonomous driving robot operates independently of a communication network and enables stable autonomous driving even when the network connection is disconnected. Claim 8 An intelligent autonomous driving robot module system according to claim 6, characterized in that the robot can perform tasks in complex environments through not only obstacle avoidance but also precise path following, and supports efficient autonomous driving through software algorithms combined with high-precision sensors. Claim 9 An intelligent autonomous driving robot module system according to claim 1, characterized in that the autonomous driving robot provides a voice control function in accordance with user commands and can be operated remotely via a smartphone application. Claim 10 An intelligent autonomous driving robot module system according to claim 1, characterized in that the autonomous driving robot responds robustly to changes in indoor and outdoor environments and is manufactured with highly durable materials and design, enabling operation even in various weather conditions.

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