Fusion method of flexible joint mechanism and touch sensor of intelligent accompanying humanoid robot

Abstract

The invention relates to the technical field of robots, in particular to a method for fusing a flexible joint mechanism and a touch sensor of an intelligent accompanying human-type robot, by constructing the flexible joint mechanism based on a composite material, robot joints can generate controllable deformation under the action of external force, and higher degree of freedom and smaller motion resistance are provided. The tactile sensor unit is integrated in the flexible joint, can sense the change of contact force between the joint part and an external object in real time, and cooperates with a robot action model through a data fusion algorithm, so that the robot action path is optimized, and tactile feedback is enhanced. In addition, a force control and position control self-adaptive switching mechanism is further introduced, the driving force of robot joints is automatically adjusted, and the stability and high efficiency of the robot in a complex environment are ensured. According to the method, the performance of the robot in a dynamic interaction scene can be remarkably improved, and more accurate and natural tactile interaction capability is provided for the robot.

Description

Technical Field

[0001] The present invention relates to the technical field of robots, and particularly to a method for integrating a flexible joint mechanism and a tactile sensor of an intelligent companion humanoid robot. Background Art

[0002] With the continuous development of artificial intelligence technology and robot technology, humanoid robots, especially intelligent companion robots, have played an increasingly important role in multiple fields such as medical care, education, and family. Intelligent companion robots not only need to complete basic movement and manipulation tasks, but also need to have flexible human-computer interaction capabilities and high adaptability. To achieve natural and smooth human-computer interaction, robots not only need to be able to perceive the external environment, but also need to be able to provide real-time feedback on the tactile interaction feelings with users.

[0003] Most of the joints of existing robots adopt rigid structures. Although this design can provide strong support force and precise control, it shows low adaptability and flexibility when contacting external objects, easily generating excessive contact forces, which may lead to joint wear or object damage. In addition, traditional force sensors usually adopt a single sensing method, such as strain sensors or pressure sensors, which limits the robot's ability to perceive contact forces and makes it unable to comprehensively and accurately identify various characteristics of the object surface (such as hardness, temperature, roughness, etc.). Although some advanced robot systems have adopted tactile sensors, these systems often lack powerful data fusion algorithms and real-time feedback mechanisms, making it difficult to accurately adjust the robot's motion trajectory and force output. Especially in complex human-computer interaction scenarios, problems such as joint overload, conflicts between force and position control, and delays in tactile feedback still commonly exist, affecting the stability and reliability of the robot's task execution. Summary of the Invention

[0004] The present invention provides a method for integrating a flexible joint mechanism and a tactile sensor of an intelligent companion humanoid robot.

[0005] The method for integrating a flexible joint mechanism and a tactile sensor of an intelligent companion humanoid robot includes the following steps:

[0006] S1: Construct a flexible joint mechanism based on composite materials, wherein the joint part is made of a flexible composite material with high elasticity and durability, and the composite material is a combination of polyurethane and carbon fiber;

[0007] S2: Integrate a set of retractable tactile sensor units in the inner cavity structure of the flexible joint. The tactile sensor units are composed of multiple embedded piezoelectric sensors, which can sense the contact force and pressure change between the joint part and external objects in real time and generate sensing signals;

[0008] S3: Design and implement a data fusion algorithm to fuse the joint angle data with the perception signals collected by the tactile sensors through the data fusion algorithm, and generate a robot interaction action model;

[0009] S4: Embed the robot interaction action model into the robot control system, and through collaborative work with the vision system and the inertial navigation system, adjust the motion trajectory of the robot joints in real time to meet the interaction requirements with the external environment;

[0010] S5: Integrate a tactile enhancement module on the robot hand. The tactile enhancement module works in collaboration with the flexible joints and the tactile sensor unit to realize the perception of the surface features of external objects (such as hardness, temperature, roughness, etc.), and generate corresponding tactile feedback to improve the interaction experience of human users;

[0011] S6: Introduce an adaptive switching mechanism between force control and position control during the robot's movement. According to the force feedback information provided by the tactile sensors, when the joint is overloaded or touches an immovable object, automatically adjust the joint driving force to achieve precise force control actions, and at the same time maintain the stability and coherence of the actions through position control to prevent accidental injuries or slow actions caused by excessive actions.

[0012] Optionally, the S1 includes:

[0013] S11: Select a composite material with high elasticity and durability, and the composite material is composed of a combination of polyurethane and carbon fiber;

[0014] S12: Design the laminated structure of the composite material according to the working load, service life, and flexibility requirements of the robot joints. Among them, the polyurethane layer serves as the external coating layer to provide elasticity, while the carbon fiber layer serves as the reinforcement layer to provide strength and rigidity, ensuring that the joints have good durability and toughness during repeated movements;

[0015] S13: Through numerical simulation analysis (such as finite element analysis), optimize the stress distribution of the designed joint composite material to ensure that the joint produces the expected controllable deformation under force, and the maximum stress does not exceed the yield strength of the material;

[0016] S14: Use a precision mold to form and process the polyurethane and carbon fiber composite material, and control the temperature and pressure during the forming process to make the various hierarchical structures of the composite material uniformly combined, thereby ensuring the stable performance of the joints;

[0017] S15: Perform surface treatment on the formed composite material joints to improve the wear resistance and corrosion resistance of the material;

[0018] S16: Integrate appropriate motion limiting devices in the joint structure to ensure that the joint does not undergo excessive deformation during movement, and avoid structural damage or movement instability caused by the joint exceeding the predetermined range of motion. The motion limiting devices include mechanical limit devices or electronic sensor control devices;

[0019] S17: Conduct physical tests to verify the performance of the selected composite materials and structural designs under various working environments.

[0020] Optionally, the S2 includes:

[0021] S21: Reserve installation positions in the inner cavity structure of the flexible joint and embed multiple piezoelectric sensors;

[0022] S22: Design and manufacture an array of multiple piezoelectric sensors, and each piezoelectric sensor is evenly distributed on the inner cavity wall of the flexible joint.

[0023] S23: Connect a signal amplification circuit to the output end of the piezoelectric sensor, and amplify the weak charge signal generated by the piezoelectric sensor through the signal amplifier.

[0024] S24: Convert the amplified charge signal into a digital signal through an analog-to-digital converter and transmit it to the robot control system for subsequent data processing.

[0025] S25: Perform real-time processing on the digital signal, remove noise and extract effective contact force information, and use a low-pass filtering algorithm to remove high-frequency noise;

[0026] S26: According to the extracted contact force information, calculate the pressure distribution and change trend of the contacted object, and feedback the pressure distribution and change trend to the robot control system to adjust the motion strategy of the robot joint in real time.

[0027] Optionally, the S3 includes:

[0028] S31: Obtain the real-time angle data of each joint of the robot;

[0029] S32: Obtain the real-time contact force signal collected by the tactile sensor unit;

[0030] S33: Synchronously fuse the joint angle data and the contact force signal through the Kalman filtering algorithm;

[0031] S34: Establish a robot interaction action model based on the fused joint angle data and contact force signal.

[0032] Optionally, the S4 includes:

[0033] S41: Embed the robot interaction action model into the central processing unit of the robot control system;

[0034] S42: In the control system, a motion trajectory planning module is established. By working in coordination with the preset vision system and inertial navigation system, it adjusts the joint motion trajectory of the robot according to changes in the external environment.

[0035] Optionally, S4 further includes:

[0036] S43: The motion trajectory planning module optimizes the joint motion trajectory of the robot in real time, ensuring that the robot can effectively interact with the external environment adaptively during task execution. Especially when encountering sudden external forces or unexpected objects, it can promptly adjust its posture and path to ensure safety and stability during the operation process.

[0037] S44: The robot control system continuously adjusts the joint motion through a real-time feedback loop to ensure the smoothness and stability of the robot's actions.

[0038] S45: By working in coordination with the vision system and inertial navigation system, the robot control system responds to changes in the external environment in real time, automatically adjusts the motion trajectory of the robot joints, optimizes the interaction efficiency and accuracy between the robot and external objects, and ensures that the robot can smoothly and safely complete the predetermined tasks in a complex environment.

[0039] Optionally, S5 includes:

[0040] S51: Integrate a tactile enhancement module on the robot's hand. By working in coordination with the flexible joints and tactile sensor units, it can accurately sense the surface features of external objects (such as hardness, temperature, roughness, etc.) and generate corresponding tactile feedback.

[0041] S52: Through the coordinated work with the flexible joints and tactile sensor units, the tactile enhancement module automatically adjusts the actions and feedback methods of the robot's hand according to the surface features of the object (such as hardness, temperature, roughness).

[0042] S53: By perceiving the surface features of external objects (such as hardness, temperature, roughness, etc.), the tactile enhancement module generates corresponding tactile feedback.

[0043] S54: By processing the signals from the sensor unit in real time, the control system generates corresponding tactile feedback signals and drives the actuator to output.

[0044] Optionally, S6 includes:

[0045] S61: During the robot's operation, design and introduce an adaptive switching mechanism between force control and position control.

[0046] S62: According to the real-time contact force signals provided by the tactile sensors, when the joints are overloaded or touch an immovable object, automatically switch to the force control mode.

[0047] S63: Through the adaptive switching mechanism, when the robot performs force control operations, the robot control system continuously monitors the joint positions to ensure that the movement trajectories of the joints do not deviate from the predetermined paths.

[0048] S64: During the actual operation process, the robot adjusts the switching between force control and position control in real time according to the joint contact feedback information.

[0049] Advantages of the present invention:

[0050] In the present invention, by adopting composite materials to construct the flexible joint mechanism, the robot can exhibit higher degrees of freedom and smaller resistance when performing tasks. Compared with traditional rigid joints, the flexible joints in the present invention can generate controllable deformations when stressed, significantly improving the adaptability of the robot. Especially when interacting with external objects complexly, the robot can flexibly adjust the joint positions and shapes to avoid damaging the objects or itself. The flexible joints with high elasticity and durability, combined with the high-performance tactile sensor unit, significantly enhance the human-robot interaction ability of the robot, enabling the robot to more accurately perceive and respond to environmental changes in different task scenarios.

[0051] In the present invention, the tactile sensor unit can continuously sense the contact forces and pressure changes between the robot joints and external objects through multiple embedded piezoelectric sensors, generate high-precision contact force signals, and work in coordination with the robot motion model through data fusion algorithms to provide accurate tactile feedback. This method can not only accurately sense the surface characteristics of objects (such as hardness, temperature, roughness, etc.), but also generate tactile feedback signals matching the object characteristics according to different contact situations, such as temperature changes, friction changes, etc. This enables the robot to provide a more realistic tactile experience when performing tasks, improving the interaction effect between the user and the robot and being able to simulate more natural tactile feedback.

[0052] In the present invention, the introduced adaptive switching mechanism between force control and position control enables the robot to intelligently switch the control mode according to the real-time feedback provided by the tactile sensor to ensure the stability and accuracy of the robot's actions. When the joints are overloaded or collide with immovable objects, the system can automatically switch to the force control mode and dynamically adjust the driving force of the joints to avoid joint damage. At the same time, during the execution of the robot task, the system continuously performs position control to ensure that the movement trajectory of the robot is smooth and coherent, preventing slowness or instability caused by excessive actions. This adaptive switching mechanism enhances the stability, response speed and execution ability of the robot, enabling the robot to always maintain high-efficiency and accurate task execution ability in complex dynamic environments, especially suitable for scenarios requiring high-precision control. Description of the Drawings

[0053] To more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0054] Figure 1 It is a schematic flowchart of the method of an embodiment of the present invention. Specific embodiments

[0055] The present invention will be described in detail below in conjunction with the drawings and specific embodiments. At the same time, it should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; moreover, the drawings are only for a more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0056] It should be noted that in the specification, when referring to "an embodiment", "embodiment", "exemplary embodiment", "some embodiments", etc., it indicates that the described embodiment may include specific features, structures or characteristics, but not necessarily every embodiment includes such specific features, structures or characteristics. Additionally, when combining an embodiment to describe a specific feature, structure or characteristic, implementing such feature, structure or characteristic in combination with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the relevant art.

[0057] Generally, terms can be understood at least in part from their use in the context. For example, at least in part depending on the context, the term "one or more" used herein can be used to describe any feature, structure or characteristic in a singular sense, or can be used to describe a combination of features, structures or characteristics in a plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey a set of exclusive factors, but instead, at least in part depending on the context, allowing for the existence of other factors that may not be explicitly described.

[0058] As Figure 1 shown, the method for fusing the flexible joint mechanism and the tactile sensor of the intelligent companion humanoid robot includes the following steps:

[0059] S1: Construct a flexible joint mechanism based on composite materials, where the joint part is made of a flexible composite material with high elasticity and durability. The composite material is a combination of polyurethane and carbon fiber, which can produce controllable deformation when stressed, providing higher degrees of freedom and smaller resistance than traditional rigid joints.

[0060] S2: A set of retractable tactile sensor units is integrated into the inner cavity structure of the flexible joint. The tactile sensor unit is composed of multiple embedded piezoelectric sensors, which can sense the contact force and pressure changes between the joint and external objects in real time and generate perception signals.

[0061] S3: Design and implement a data fusion algorithm to fuse the joint angle data with the perception signals collected by the tactile sensor and generate a robot interaction action model.

[0062] S4: The robot interaction action model is embedded into the robot control system, and the motion trajectory of the robot joints is adjusted in real time through collaboration with the visual system and inertial navigation system to adapt to the interaction requirements with the external environment;

[0063] S5: A tactile enhancement module is integrated into the robot hand. The tactile enhancement module works in conjunction with the flexible joints and tactile sensor units to perceive the surface characteristics of external objects (such as hardness, temperature, roughness, etc.) and generate corresponding tactile feedback to enhance the interactive experience of human users.

[0064] S6: An adaptive switching mechanism between force control and position control is introduced during the robot's motion process. Based on the force feedback information provided by the tactile sensor, the joint drive force is automatically adjusted to achieve precise force-controlled motion when the joint is overloaded or touches an immovable object. At the same time, the stability and continuity of the motion are maintained through position control to prevent accidental injuries or slow movements caused by excessive movements.

[0065] S1 includes:

[0066] S11: Choose a composite material with high elasticity and durability. The composite material is composed of polyurethane and carbon fiber. The hardness of the polyurethane ranges from 50 to 80 Shore A, and the reinforcement ratio of the carbon fiber is 30% to 50%. This allows the joint to produce controllable deformation when subjected to external force and has a high elastic recovery ability.

[0067] S12: According to the workload, service life and flexibility requirements of the robot joint, the laminated structure of the composite material is designed, in which the polyurethane layer as the outer coating provides elasticity, and the carbon fiber layer as the reinforcement layer provides strength and rigidity to ensure that the joint has good durability and toughness in repetitive movements;

[0068] S13: Optimize the stress distribution of the designed joint composite material through numerical simulation analysis (such as finite element analysis) to ensure that the joint produces the expected controllable deformation under stress and the maximum stress does not exceed the yield strength of the material;

[0069] S14: Use a precision mold to perform forming processing on the polyurethane and carbon fiber composite material. Control the temperature and pressure during the forming process to ensure uniform bonding of the various hierarchical structures of the composite material, thereby ensuring stable performance of the joint.

[0070] S15: Perform surface treatment on the formed composite joint to improve the wear resistance and corrosion resistance of the material, ensuring that the performance of the joint is not affected by the external environment during long-term use. The surface treatment includes coating treatment, plasma treatment, or other surface enhancement processes.

[0071] S16: Integrate appropriate motion limiting devices into the joint structure to ensure that the joint does not undergo excessive deformation during movement, avoiding structural damage or unstable movement caused by the joint exceeding the predetermined motion range. The motion limiting devices include mechanical limit devices or electronic sensor control devices.

[0072] S17: Conduct physical tests to verify the performance of the selected composite material and structural design under various working environments, including fatigue resistance, impact resistance, and elastic recovery ability after long-term use, ensuring the reliability and stability of the joint in practical applications.

[0073] S2 includes:

[0074] S21: Reserve installation positions in the inner cavity structure of the flexible joint and embed multiple piezoelectric sensors. The sensors can generate electric charges under the action of external forces and have a response frequency range of 100 Hz to 1 kHz, capable of accurately sensing the contact force and pressure changes between the joint part and external objects.

[0075] Select a suitable piezoelectric material. The piezoelectric material has good piezoelectric effect and high sensitivity, ensuring accurate induction of external contact forces under low load conditions. The piezoelectric material is lead zirconate titanate or polymer-based piezoelectric material with high elasticity.

[0076] S22: Design and manufacture an array of multiple piezoelectric sensors. Each piezoelectric sensor is evenly distributed on the inner cavity wall of the flexible joint to improve the spatial resolution of the contact points. The layout of the array ensures that the sensors can comprehensively cover the force-bearing area of the joint and collect joint force information in real time.

[0077] S23: Connect a signal amplification circuit to the output end of the piezoelectric sensor. Amplify the weak charge signal generated by the piezoelectric sensor through the signal amplifier to improve the effectiveness and processing accuracy of the signal. The gain of the amplification circuit is set between 10 times and 1000 times to ensure that the signal can be adapted to subsequent digital processing.

[0078] S24: Convert the amplified charge signal into a digital signal through an analog-to-digital converter and transmit it to the robot control system for subsequent data processing. To ensure the accuracy of signal conversion, select an analog-to-digital converter with 16-bit or higher precision for data sampling.

[0079] S25: Perform real-time processing on the digital signal, remove noise, and extract effective contact force information. Use a low-pass filtering algorithm to remove high-frequency noise.

[0080] S26: According to the extracted contact force information, calculate the pressure distribution and change trend of the contacted object, and feedback the pressure distribution and change trend to the robot control system to adjust the motion strategy of the robot joints in real time.

[0081] S3 includes:

[0082] S31: Obtain the real-time angle data of each joint of the robot. The real-time angle data of each joint is collected by an encoder inside the joint to ensure that the robot joints can accurately track and feedback when performing actions.

[0083] The joint angle data is represented as θ(t), where θ(t) is the angle of the joint at time t.

[0084] S32: Obtain the real-time contact force signal collected by the tactile sensor unit. The contact force signal is a charge signal generated through the piezoelectric effect and converted into a digital signal through an analog-to-digital converter. After signal processing, effective contact force information such as the magnitude, direction, and change trend of the force is extracted.

[0085] Contact force signal F t (t) represents the contact force applied when an external object contacts the joint.

[0086] S33: Through the Kalman filtering algorithm, synchronously fuse the joint angle data θ(t) and the contact force signal F t (t) to improve the real-time performance and accuracy of the data.

[0087] Set the system state vector as x(t), which includes data such as joint angle and speed. Let the system state equation be:

[0088] x(t) = Ax(t - 1) + Bu(t) + w(t);

[0089] Among them, A is the state transition matrix, which describes the state change from time t - 1 to t. u(t) is the control input, which may include externally applied forces or sensor data. w(t) is the process noise, usually assumed to be zero-mean Gaussian noise.

[0090] The measurement equation is:

[0091] z(t) = Hx(t) + v(t);

[0092] where z(t) is the measurement vector (including the joint angle θ(t) and the contact force F t (t)), H is the observation matrix that describes how the measurements are calculated from the system state, and v(t) is the measurement noise;

[0093] Through Kalman filtering, the current state of the robot (such as the change trends of speed and contact force) can be estimated in real time based on the contact force signal and joint angle data;

[0094] S34: Based on the fused joint angle data and contact force signal, establish a robot interaction action model. The robot interaction action model describes the dynamic behavior of the robot under external contact forces. In particular, considering the dynamic characteristics of the robot when using flexible joints, the robot interaction action model needs to be modeled according to the physical characteristics of the flexible joints, the deformation characteristics of the joints, and the influence of external contact forces, including:

[0095] (1) Dynamics modeling of flexible joints: For flexible joints, the dynamic response of the joint is not only described by the angle and speed, but also involves the elastic deformation of the joint and the contact force with external objects. Therefore, the robot interaction action model needs to introduce the following factors:

[0096] Joint angle (θ(t)), joint speed Joint acceleration Joint stiffness (K(θ)) and contact torque (F t (t));

[0097] In the model of flexible joints, the dynamic equation comprehensively considers the stiffness matrix, damping matrix, and inertia matrix. Suppose the dynamic response of the robot joint is described by the following equation:

[0098]

[0099] where M(θ) is the inertia matrix of the joint, is the damping matrix, and τ(t) is the driving torque applied to the joint;

[0100] (2) Stiffness and non - linear elastic characteristics: The stiffness of flexible joints is not fixed, but is closely related to the joint angle or deformation degree. A non - linear elastic model is used to describe the stiffness of the joint. For example, use the following non - linear stiffness model:

[0101] K(θ) = K 0 (1 + αθ 2 );

[0102] where K 0is the initial stiffness constant, representing the stiffness of the joint during small deformations. α is the non - linear coefficient, describing the change in stiffness of the joint during large - angle deformations. θ is the angle of the joint;

[0103] The non - linear model can reflect the change in stiffness of the flexible joint under large - deformation conditions and can more realistically simulate the response of the flexible joint;

[0104] (3) External contact torque: The contact torque F t (t) reflects the torque generated when the robot joint comes into contact with an external object. The contact force usually causes joint deformation and torque changes. To model this torque, according to the relationship between the contact force and torque, the following integral formula can be used:

[0105] F t (t) = ∫σ(θ)·S dx;

[0106] where σ(θ) is the stress applied to the joint surface, which is the distribution of the contact force on the joint surface, S is the contact area, and d x is the infinitesimal change;

[0107] (4) Comprehensive expression of the robot interaction action model: After comprehensively considering factors such as the inertia, stiffness, damping, and external contact torque of the flexible joint, the robot interaction action model is expressed as:

[0108]

[0109] S4 includes:

[0110] S41: Embed the robot interaction action model into the central processing unit of the robot control system. The robot control system also includes a motion control unit, a sensor processing unit, and a communication interface unit to ensure that the robot can automatically adjust its motion behavior according to real - time sensor data and task requirements.

[0111] In this step, the interaction action model is calculated in real - time through the central processing unit of the control system to generate specific motion instructions. The central processing unit has strong data - processing capabilities and can quickly process data inputs from sensors (such as tactile sensors, vision sensors, and inertial sensors) and output motion instructions;

[0112] S42: In the control system, set up a motion trajectory planning module. By working in coordination with the preset vision system and inertial navigation system, adjust the joint motion trajectory of the robot according to changes in the external environment;

[0113] Vision system: This system consists of a camera, an image processing unit, and a target detection algorithm. It can acquire image data of the robot and its surrounding environment in real time and identify the target object and its position through an image recognition algorithm. By working in coordination with the trajectory planning module in the robot control system, the vision system provides environmental information to assist in calculating the relative position, attitude, and path planning between the robot and the target object.

[0114] Inertial navigation system: The inertial navigation system consists of sensors such as accelerometers and gyroscopes, which can sense the displacement, speed, and angular changes of the robot itself in real time. The function of this system is to provide accurate attitude estimation during the movement of the robot, assist the control system in adjusting the robot's motion trajectory, and compensate for possible errors in the vision system. Especially in low-light or obstacle occlusion situations, the inertial navigation system can provide continuous and stable position information.

[0115] S4 also includes:

[0116] S43: The motion trajectory planning module optimizes the joint motion trajectory of the robot in real time to ensure that the robot can interact effectively with the external environment adaptively during task execution. Especially when encountering sudden external forces or unexpected objects, it can adjust the attitude and path in a timely manner to ensure safety and stability during the operation process.

[0117] The motion trajectory planning module not only considers the changes in the external environment but also needs to consider the dynamic characteristics of the robot itself, such as the deformation of flexible joints and contact feedback. Based on the interaction action model, visual data, inertial data, and real-time sensed contact force information, the robot can adjust its motion trajectory in real time, avoid collisions with external obstacles, and optimize the execution path to achieve more precise task execution.

[0118] S44: The robot control system continuously adjusts the joint motion through a real-time feedback loop to ensure the smoothness and stability of the robot's actions. In the system, all sensed data, including visual data, inertial data, and tactile sensor feedback, is processed through a closed-loop control mechanism to generate real-time control instructions to adjust the joint motion and attitude of the robot, enabling the robot to accurately respond to the dynamically changing environment.

[0119] The closed-loop feedback mechanism of the control system enables the robot to correct its motion trajectory in real time according to the changes in sensor data. For example, when the vision system identifies an obstacle or a change in the target position, the robot will automatically adjust its motion path. Correspondingly, the real-time feedback provided by the inertial navigation system and tactile sensors will be used to dynamically adjust the angle and force of the joints, thereby achieving precise control.

[0120] S45: By working in collaboration with the visual system and inertial navigation system, the robot control system responds to changes in the external environment in real time, automatically adjusts the motion trajectory of the robot's joints, optimizes the efficiency and accuracy of the robot's interaction with external objects, and ensures that the robot can complete the intended tasks smoothly and safely in a complex environment.

[0121] At this stage, the control system intelligently adjusts the robot behavior by fusing data from multiple sensors (such as vision, inertia, and tactile feedback), taking into account the flexible deformation of the joints, external contact forces, and real-time changes in the target environment.

[0122] S5 includes:

[0123] S51: A tactile enhancement module is integrated in the robot hand. By working in conjunction with the flexible joint and the tactile sensor unit, the tactile enhancement module can accurately sense the surface characteristics of external objects (such as hardness, temperature, roughness, etc.) and generate corresponding tactile feedback. The working principle of the tactile enhancement module is to sense the tiny force changes between the robot hand and the object in real time and output tactile signals based on the sensed results. The tactile enhancement module includes:

[0124] Sensor unit: The tactile enhancement module includes multiple tactile sensor units (such as piezoelectric sensors, thermoelectric sensors, friction sensors, etc.). These sensors can collect information such as contact force, temperature change, surface roughness, etc. in real time, and transmit the perception signals to the control system.

[0125] Actuator unit: The actuator unit mainly includes force feedback devices (such as servo motors, vibration motors, shape memory alloys, etc.), which are used to generate corresponding tactile feedback. The actuator converts the signal of the control system into physical feedback that the user can perceive, such as temperature, vibration or force perception.

[0126] S52: By working in collaboration with the flexible joints and tactile sensor units, the tactile enhancement module automatically adjusts the robot's hand movements and feedback methods according to the surface characteristics of the object (such as hardness, temperature, and roughness), thereby achieving a precise interactive experience.

[0127] Collaboration with flexible joints: The coordination between the tactile enhancement module and the flexible joints enables the robot hand to adjust the joint's motion trajectory or force output according to different contact feedback (such as contact force, contact angle, etc.) when it contacts external objects. The robot makes soft contact with external objects through the deformation response of the flexible joints, thereby sensing the hardness or surface characteristics of the object without causing damage.

[0128] Collaborative work with tactile sensors: The tactile enhancement module combines the feedback of the tactile sensor unit, enabling real-time detection of minute changes on the object surface and adjusting the actions of the robot's hand. For example, when the object surface becomes rougher or harder, the control system will automatically increase the contact force or adjust the joint position to ensure the accuracy of tactile feedback.

[0129] S53: By perceiving the surface characteristics of external objects (such as hardness, temperature, roughness, etc.), the tactile enhancement module generates corresponding tactile feedback. Specifically, when the robot's hand touches different objects, the control system will output corresponding feedback signals according to the surface characteristics of the object, enabling the user to perceive different attributes of the object.

[0130] Hardness perception: Through the cooperation of force sensors and flexible joints, the tactile enhancement module can perceive the hardness of an object. For example, when the robot's hand touches a harder object, the increased contact force is fed back to the control system through the tactile sensor, and then vibration or pressure feedback related to hardness is output through the actuator.

[0131] Temperature perception: The tactile enhancement module includes thermoelectric sensors that can measure the temperature difference change at the contact point with the object in real time. When the robot's hand touches the object surface, the temperature sensor will sense the object's temperature and transmit the data to the control system. The system provides corresponding thermal feedback to the user by adjusting the feedback frequency and intensity of the vibration motor or servo motor.

[0132] Roughness perception: Through friction sensors, the tactile enhancement module can perceive the roughness of the object surface. When touching a rough object, the sensor can detect the change in friction force, and then adjust the way of tactile feedback. For example, by changing the vibration frequency or intensity, the user can clearly perceive the subtle differences on the object surface.

[0133] S54: By processing the signals from the sensor unit in real time, the control system generates corresponding tactile feedback signals and drives the actuator to output. According to the control signal, the actuator produces appropriate tactile feedback (such as vibration, force sensation, or temperature perception), thereby enhancing the interaction experience between the user and the robot.

[0134] Feedback signal generation: The control system uses signal processing algorithms (such as weighted average, filters, etc.) to generate the final feedback signals based on the data of force, temperature, roughness, etc. output by the tactile sensor. These feedback signals instruct the actuator (such as a vibration motor or shape memory alloy) to perform precise actions;

[0135] Actuator feedback: The actuator acts according to the feedback signal, such as adjusting the pressure of the hand, generating slight vibrations, heating or cooling certain areas, etc. Through these physical feedbacks, the user can perceive the hardness, temperature, and roughness of the object, thereby enhancing the realism and immersion of human-machine interaction;

[0136] The design of the tactile enhancement module can adjust the feedback method in real time according to the surface characteristics of the object, so as to achieve a highly sensitive physical interaction experience. This not only enhances the robot's perception ability of external objects, but also improves the user's operation experience, ensuring that the robot can interact with the external environment more effectively in complex tasks.

[0137] S6 includes:

[0138] S61: During the robot's movement, design and introduce an adaptive switching mechanism between force control and position control, which can judge the working state of the robot joints in real time according to the force feedback information provided by the tactile sensors, ensuring that the robot can flexibly switch between the force control mode and the position control mode when performing tasks to meet different interaction requirements;

[0139] Force control mode: In this mode, the control system adjusts the driving force of the robot joints in real time according to the contact force signal provided by the tactile sensors to precisely control the contact force. This mode is suitable for task scenarios that require delicate force control, such as precise operations when the robot contacts the object surface, ensuring that the robot can perform gentle and precise operations according to the characteristics of the object;

[0140] Position control mode: When the contact force of the robot joints is low or there is no contact, the control system adopts the position control mode to achieve the robot's movement through precise positioning control of the joints. This mode is suitable for most standard movements to ensure that the robot moves stably along the predetermined trajectory;

[0141] S62: According to the real-time contact force signal provided by the tactile sensors, when the joint is overloaded or touches an immovable object, automatically switch to the force control mode, and avoid joint damage by dynamically adjusting the driving force, and ensure the stability and accuracy of the robot's movement;

[0142] Collection of force feedback signals: The tactile sensor unit (such as piezoelectric sensors, strain sensors, etc.) collects contact force information in real time and transmits these signals to the control system. Through the force feedback information, the control system can detect whether the joint is in an overloaded state or whether a collision with an immovable object has occurred.

[0143] Overload detection and switching mechanism: When the tactile sensor detects an excessive contact force (for example, when the joint is subjected to excessive external force or collides with a hard object), the control system will switch the control mode from position control to force control mode through an adaptive algorithm. In this mode, the control system automatically adjusts the output of the joint drive system according to the feedback of the force sensor to reduce the driving force to avoid joint overload or damage;

[0144] Avoid accidental damage: In force control mode, the movement of the robot joints will be adjusted based on real-time feedback to ensure that even in the event of a strong collision or unexpected situation, the robot can avoid damage caused by excessive driving force. The control system monitors the real-time contact force signal to ensure that the joints operate within an appropriate force range, thereby reducing the occurrence of mechanical failures;

[0145] S63: Through an adaptive switching mechanism, when the robot performs force control operations, the robot control system continuously monitors the joint positions to ensure that the movement trajectories of the joints do not deviate from the predetermined paths, while preventing sluggishness or instability caused by excessive movements;

[0146] Position monitoring: Even in force control mode, the robot control system still continuously monitors the positions of the robot joints, obtaining accurate position data of the joints through position sensors (such as encoders, gyroscopes, etc.). The system adjusts the drive commands based on the error between the current position and the predetermined target position to ensure that the robot joints do not show position offsets;

[0147] Prevent sluggish movement: To prevent the robot from becoming sluggish due to excessive reduction of driving force, the control system adjusts the position control gain parameters when performing force control to ensure that the joints maintain appropriate movement speeds and smoothness while precisely controlling the force, avoiding the impact of excessive force limitations on the efficiency of task execution;

[0148] S64: During actual operation, the robot adjusts the switching between force control and position control in real time based on joint contact feedback information to ensure that the robot always maintains precise and stable movement performance when performing complex tasks, especially being able to handle different types of object contacts, external force impacts, and environmental changes in a dynamic environment;

[0149] Real-time adjustment and closed-loop control: Through real-time sensor data, the control system continuously adjusts the switching point between force control and position control modes. For example, in the case of a soft or irregular object surface, the system preferentially uses the force control mode to precisely adjust the joint movements by sensing the contact force; while in a relatively stable environment, the system switches to the position control mode to maintain the smooth movement of the robot through precise positioning control.

[0150] Multi-sensor collaborative work: This switching mechanism is based on the information fusion from different sensors (such as tactile sensors, vision sensors, position sensors, etc.), and determines the optimal control strategy through algorithms to ensure the accuracy and coherence of the robot's movements. During the switching process, the system also makes a smooth transition to avoid vibrations or jerky movements during mode switching, ensuring the smoothness of the user experience;

[0151] Through this adaptive switching mechanism, the robot can flexibly adjust its action strategy according to real-time tactile feedback, adapt to different task requirements and operating environments, improve the robot's performance in complex human-robot interactions, and ensure stable and efficient task execution capabilities in various environments.

[0152] This invention covers any alternatives, modifications, equivalent methods, and solutions made within the essence and scope of this invention. To enable the public to have a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments of this invention. However, those skilled in the art can fully understand this invention without the description of these details. Additionally, well-known methods, processes, procedures, components, and circuits, etc., are not described in detail to avoid unnecessary confusion to the essence of this invention.

[0153] The above are only the preferred embodiments of this invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of this invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of this invention.

Claims

1. A method for fusing a flexible joint mechanism and a tactile sensor of an intelligent companion humanoid robot, characterized in that: The following steps are involved: S1: Construct a composite-based flexible joint mechanism, wherein the joint part is made of a flexible composite material with high elasticity and durability, and the composite material is a combination of polyurethane and carbon fiber; S2: Integrate a set of retractable tactile sensor units in the inner cavity structure of the flexible joint, wherein the tactile sensor unit is composed of a plurality of embedded piezoelectric sensors, and senses the contact force and pressure changes between the joint and the external object in real time to generate a sensing signal; S3: Design and implement a data fusion algorithm to fuse the joint angle data with the perception signals collected by the tactile sensor and generate a robot interaction action model; S4: embedding the robot interactive action model into the robot control system, and adjusting the motion trajectory of the robot joints in real time through collaboration with the visual system and the inertial navigation system to adapt to the interaction requirements with the external environment; S5: Integrate a tactile enhancement module in the robot hand. The tactile enhancement module works in conjunction with the flexible joints and tactile sensor units to perceive the surface features of external objects and generate corresponding tactile feedback to improve the interactive experience of human users. S6: An adaptive switching mechanism between force control and position control is introduced during the robot's motion process. Based on the force feedback information provided by the tactile sensor, the joint driving force is automatically adjusted when the joint is overloaded or touches an immovable object. At the same time, the stability and continuity of the movement are maintained through position control to prevent accidental injuries or slow movements caused by excessive movements.

2. The method for fusing the flexible joint mechanism and tactile sensor of the intelligent companion humanoid robot according to claim 1, characterized in that: The S1 includes: S11: Select a composite material with high elasticity and durability, wherein the composite material is a combination of polyurethane and carbon fiber; S12: Design a composite laminate structure based on the workload, service life, and flexibility requirements of the robot joint, where the polyurethane layer as the outer covering layer provides elasticity and the carbon fiber layer as the reinforcement layer provides strength and rigidity; S13: Optimize the stress distribution of the designed joint composite material through numerical simulation analysis; S14: Use precision molds to mold polyurethane and carbon fiber composite materials, and control temperature and pressure during the molding process to ensure that the various layers of the composite material are evenly combined; S15: Surface treatment is performed on the formed composite joints to improve the wear resistance and corrosion resistance of the materials; S16: Integrate a motion limiting device into the joint structure to avoid structural damage or unstable movement due to the joint exceeding the predetermined range of motion. The motion limiting device includes a mechanical limit device or an electronic sensor control device; S17: Conduct physical tests to verify the performance of the selected composite materials and structural designs in various working environments.

3. The method for fusing the flexible joint mechanism and tactile sensor of the intelligent companion humanoid robot according to claim 2, characterized in that: The S2 includes: S21: A mounting position is reserved in the inner cavity structure of the flexible joint and a plurality of piezoelectric sensors are embedded; S22: Design and manufacture an array of multiple piezoelectric sensors, each of which is evenly distributed on the inner cavity wall of the flexible joint; S23: Connecting a signal amplifying circuit to the output end of the piezoelectric sensor, and amplifying the charge signal generated by the piezoelectric sensor through the signal amplifier; S24: converting the amplified charge signal into a digital signal through an analog-to-digital converter, and transmitting the digital signal to the robot control system for subsequent data processing; S25: Process the digital signal in real time to remove noise and extract contact force information; S26: Based on the extracted contact force information, the pressure distribution and change trend of the contact object are calculated, and the pressure distribution and change trend are fed back to the robot control system to adjust the movement strategy of the robot joint in real time.

4. The method for fusing the flexible joint mechanism and tactile sensor of the intelligent companion humanoid robot according to claim 3 is characterized in that: The S3 includes: S31: Obtain the real-time angle data of each joint of the robot; S32: Acquire a real-time contact force signal collected by the tactile sensor unit; S33: The joint angle data and contact force signal are synchronously fused through the Kalman filter algorithm; S34: Establish a robot interaction action model based on the fused joint angle data and contact force signals.

5. The method for fusing the flexible joint mechanism and tactile sensor of the intelligent companion humanoid robot according to claim 4, characterized in that: The S4 includes: S41: embedding the robot interaction action model into the central processing unit of the robot control system; S42: In the control system, a motion trajectory planning module is set up to adjust the joint motion trajectory of the robot according to changes in the external environment by working in collaboration with the preset visual system and inertial navigation system.

6. The method for fusing the flexible joint mechanism and tactile sensor of the intelligent companion humanoid robot according to claim 5, characterized in that: The S4 further comprises: S43: Real-time optimization of the robot's joint motion trajectory through the motion trajectory planning module; S44: The robot control system continuously adjusts joint motion through a real-time feedback loop; S45: By working in collaboration with the visual system and inertial navigation system, the robot control system responds to changes in the external environment in real time, automatically adjusts the motion trajectory of the robot joints, and optimizes the efficiency and accuracy of the robot's interaction with external objects.

7. The method for fusing the flexible joint mechanism and tactile sensor of the intelligent companion humanoid robot according to claim 6, characterized in that: The S5 includes: S51: Integrate a tactile enhancement module in the robot hand to sense the surface features of external objects and generate corresponding tactile feedback by working together with the flexible joints and tactile sensor units; S52: By working in conjunction with the flexible joint and the tactile sensor unit, the tactile enhancement module automatically adjusts the movement and feedback mode of the robot hand according to the surface characteristics of the object; S53: The tactile enhancement module generates corresponding tactile feedback by sensing the surface features of the external object; S54: By processing the signal from the sensor unit in real time, the control system generates a corresponding tactile feedback signal and drives the actuator output.

8. The method for fusing the flexible joint mechanism and tactile sensor of the intelligent companion humanoid robot according to claim 7, characterized in that: The S6 includes: S61: Design and introduce an adaptive switching mechanism between force control and position control during robot motion; S62: According to the real-time contact force signal provided by the tactile sensor, when the joint is overloaded or touches an immovable object, it automatically switches to the force control mode; S63: Through the adaptive switching mechanism, the robot control system maintains continuous monitoring of the joint position when the robot performs force control operations; S64: During actual operation, the robot adjusts the switching between force control and position control in real time based on the joint contact feedback information.

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