Charging method of intelligent robot

Abstract

The invention discloses a charging method of an intelligent robot, and relates to the technical field of intelligent robotics.The charging method comprises the specific steps that S100, an energy collection framework is built, specifically, by means of mechanical analysis and actual working condition monitoring means, through refined layout and installation of an energy collection device, the energy collection framework is built; efficient conversion and utilization of mechanical energy in the movement process of the intelligent robot are achieved, piezoelectric materials with different characteristics are adopted for different parts, the piezoelectric materials are designed to be of a wave-shaped or honeycomb-shaped or bent or stretched structure, a cantilever beam type piezoelectric crystal structure is selected, and an electromagnetic induction type vibration energy collecting device is optimized. The energy collection efficiency and range are improved, the energy collection frequency band and working condition range are widened, the intelligent robot can autonomously collect energy in various complex environments, dependence on an external power source is reduced, and the autonomous operation capacity and cruising ability of the intelligent robot are improved.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent robots, and in particular to a charging method for an intelligent robot. Background Art

[0002] With the rapid development of science and technology, intelligent robot technology has made great progress and has shown broad application prospects in many fields such as industrial automation, service industry, medical health, and military reconnaissance. Intelligent robots, with their high efficiency, precision, and tirelessness, are gradually replacing humans to complete various complex, dangerous or repetitive tasks. However, the continuous operation and efficient operation of intelligent robots are inseparable from a stable energy supply. At present, most intelligent robots on the market use batteries as the main energy supply method, but battery life and charging efficiency have become key factors restricting the further development of intelligent robots. Therefore, it is particularly important to explore a new, efficient and sustainable charging method for intelligent robots.

[0003] Traditional intelligent robot charging methods mainly rely on manual battery replacement or external power charging. These methods have many shortcomings. On the one hand, manual battery replacement requires a lot of time and manpower, and cannot be achieved under special circumstances. On the other hand, although external power charging can provide continuous power supply, it is limited by the carrying and access of charging equipment and power supply, and the charging efficiency and flexibility are greatly reduced. In addition, traditional charging methods also have safety hazards, such as overcharging and over-discharging of batteries, which may cause battery damage or even fire. Therefore, traditional intelligent robot charging methods can no longer meet the efficient, safe and autonomous operation requirements of modern intelligent robots.

[0004] Therefore, developing a charging method for an intelligent robot not only improves the endurance and charging efficiency of the intelligent robot, but also reduces safety hazards, providing strong technical support for the further development of the intelligent robot. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and to provide a charging method for an intelligent robot. The method first selects suitable piezoelectric materials to make energy collection devices through mechanical analysis and actual working condition monitoring, and installs electromagnetic induction vibration energy collection devices to convert the mechanical energy generated by the robot movement into electrical energy. Then, the piezoelectric effect and electromagnetic induction principles are used to convert the mechanical energy generated by the robot movement and vibration into electrical energy, and it is transmitted and preliminarily processed through high conductivity materials and filtering and voltage stabilization technology. Then, through the real-time monitoring and intelligent algorithm of the microprocessor of the power management system, the dynamic management and efficient allocation and storage of electric energy are realized. Finally, based on the actual operation data feedback, the charging system is comprehensively optimized to improve the efficiency of energy collection and power management.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a charging method for an intelligent robot, the specific steps of the charging method are:

[0007] S100, energy collection architecture construction: Through mechanical analysis and actual working condition monitoring methods, the motion posture, force distribution and vibration of the intelligent robot in daily operation are analyzed, and piezoelectric materials suitable for each part are selected to make energy collection devices. Electromagnetic induction vibration energy collection devices are installed on the main frame, and they are connected by electrical connection and mechanical fixing. Through various devices, the mechanical energy generated by the robot's movement is converted into electrical energy and transmitted, laying a solid foundation for the subsequent charging process;

[0008] S200, energy collection trigger conversion: When the robot starts to perform tasks, the piezoelectric module at the bottom is subjected to pressure, and the internal piezoelectric material lattice is distorted, causing the directional movement of positive and negative charges, generating a potential difference. The charges are gathered into a DC signal under the action of the charge collection circuit of the bottom device. The flexible piezoelectric device at the joint of the robot arm continuously changes the force state with the flexion, extension and rotation of the joint, generating piezoelectric charges. At the same time, the vibration generated by the movement of the robot is transmitted to the vibration energy collection device on the main frame. According to the principle of electromagnetic induction, its coil cuts the magnetic lines of force in the magnetic field, generating an AC signal, which is converted into DC through the built-in rectifier circuit and transmitted to the front-end preprocessing circuit together with the electric energy generated by the piezoelectric device;

[0009] S300, power transmission purification and control: Use highly conductive metal materials as transmission wires, select the cross-sectional area and length of the wires according to the transmission power and current size, and use cables with multi-layer shielding structures. Follow the shortest path principle for wiring to transmit current to the power management system. The rectifier bridge in the front-end preprocessing circuit converts the AC generated by the vibration energy collection device into DC, and uses the unidirectional conductivity of the diode to achieve unidirectional and stable current flow. Through the filter network composed of filter capacitors and inductors, according to the charging and discharging characteristics of the capacitors and the hindering effect of the inductors on current changes, remove the clutter signals from the energy collection end and the transmission line. The voltage regulator diode and the intelligent voltage regulator chip work together to stabilize the voltage within a range suitable for subsequent processing and storage according to the voltage requirements of the back-end battery and electrical equipment.

[0010] S400, intelligent power management decision-making: The power management system's microprocessor monitors the battery's power, voltage, and current parameters in real time, and formulates a dynamic power allocation strategy based on the robot's current work tasks and external environmental conditions;

[0011] S500, charging system optimization and upgrade: Through actual operation data feedback, the charging system is optimized in all aspects. In terms of piezoelectric materials, new composite materials and microstructure optimization methods are used to introduce an adaptive adjustment mechanism for the energy collection device, so that it can automatically adjust the working state according to different vibration frequencies and stress conditions, and broaden the frequency band and operating range of energy collection. For the power management system, in terms of the power management system, an artificial intelligence algorithm is introduced to learn and analyze a large amount of historical data, so that it can make power management decisions according to working conditions.

[0012] Furthermore, in the S100, the selection of piezoelectric materials and the design of energy collection devices in the construction of the energy collection architecture, for the bottom part that is subjected to greater pressure, a multilayer piezoelectric ceramic composite material with high compressive strength and high piezoelectric constant is used, and the structure is designed to be a wavy or honeycomb structure; for the joints of the robotic arm, a piezoelectric polymer material with good flexibility is selected to make a bending or stretching energy collection device.

[0013] Furthermore, in S100, the energy harvesting architecture is constructed, and the vibration energy harvesting device is selected and installed. Through actual measurement and analysis of the robot's vibration spectrum, the main vibration frequency range and amplitude distribution are determined, and a vibration energy harvesting device based on the piezoelectric effect is selected. A cantilever beam piezoelectric crystal structure is selected, and the resonant frequency is optimized by adjusting the size, shape and position of the mass block to match it with the main vibration frequency of the robot. For the electromagnetic induction vibration energy harvesting device, the number of turns, wire diameter, winding method of the coil, and the material, shape and magnetic field strength of the magnet are designed to enhance the coupling between the coil and the magnetic field and capture the vibration energy.

[0014] Furthermore, in the energy collection trigger conversion in S200, the energy value of the piezoelectric material converted from the mechanical energy of the robot movement into electrical energy within a specific time period is calculated by the piezoelectric material energy collection formula, and the formula is: Where: E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], α pz is a comprehensive coefficient related to the performance of piezoelectric materials, F(t) is the time-varying force acting on the piezoelectric material, v(t) is the velocity of the piezoelectric material at the force point, ω is the angular frequency of vibration, is the phase angle, γ pz is a coefficient related to the geometry and mounting method of the piezoelectric material.

[0015] Furthermore, in the energy collection trigger conversion, in S200, the energy value converted from the robot vibration mechanical energy into electrical energy by the electromagnetic induction vibration energy collection device within a specific time period is calculated by a vibration energy collection formula, and the formula is: Where: E vibis the total energy collected by the vibration energy harvesting device in the time period [t1, t2], β vib is a comprehensive coefficient related to the performance of the electromagnetic induction device, B(t) is the magnetic field strength that changes with time, A(t) is the effective area of ​​the coil, and μ vib is a coefficient related to the vibration frequency and direction.

[0016] Furthermore, the S400, power management strategy in intelligent power management decision-making: when the battery power is at a low level and the robot is in a non-critical mission stage, the energy consumption of non-essential functional modules is suspended, and all the collected power is used for fast charging of the battery; when the battery power is sufficient and the power generation power of the energy collection device is high, the charging of the auxiliary energy storage device is increased while ensuring the normal operation of the robot; when the robot performs an emergency task and the energy collection device generates insufficient power, the battery power is allocated according to the task priority and energy consumption requirements to ensure the stable operation of the power system and control system, and at the same time a low power warning signal is sent to the operator to prompt timely external charging or battery replacement.

[0017] Furthermore, in the S400, the intelligent power management decision is made by using a battery charging power allocation formula to calculate the power allocated to the battery charging at time t according to the power output of the energy collection device in real time and the current state of the battery and the robot. The formula is: P ch (t) = λ(t)·(E pz (t)+E vib (t))·f(SOC(t), T(t), P load (t)), where: P ch (t) is the power allocated to the battery for charging at time t, λ(t) is the power allocation coefficient that varies with time, and E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], E vib is the total energy collected by the vibration energy harvesting device in the time period [t1, t2], f(SOC(t), T(t), P load (t)) is a function of the battery state of charge SOC(t), temperature T(t) and load power P load (t), the formula is: f(SOC(t), T(t), P load (t))=b1×SOC(t)+b2×T(t)+b3×P load (t)+b4, where b1, b2, b3 and b4 are coefficients determined according to the actual system characteristics, SOC(t) represents the state of charge of the battery at time t, E pz (t) and E vib(t) represent the electrical energy generated by the piezoelectric material and the vibration energy harvesting device at time t, T(t) represents the temperature at time t, P load (t) represents the load power of the robot at time t.

[0018] Furthermore, in the S400, the intelligent power management decision is to adjust the energy consumption power formula of the robot's non-critical functional modules at time t according to the battery charging demand and energy collection situation through the robot functional module energy consumption adjustment formula: P func (t) = P func0 (t)·(1-δ(t)·g(sOC(t),(E pz (t)+E vib (t)), P load (t))), where: P func (t) is the energy consumption power of a functional module of the robot after adjustment at time t, P func0 (t) is the original energy consumption power of the functional module at time t, δ(t) is the energy consumption adjustment coefficient that changes with time, E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], E vib is the total energy collected by the vibration energy harvesting device during the time period [t1, t2], g(sOC(t), (E pz (t)+E vib (t)), P load (t)) is a function of the battery state of charge, total energy harvested, and load power, and is calculated as:

[0019] g(SOC(t),(E pz (t)+E vib (t)), P load (t)) = a1 × SOC (t) + a2 × (E pz (t)+E vib (t))+a3×P load (t)+a4

[0020] , where a1, a2, a3 and a4 are coefficients that need to be determined according to the actual system characteristics, SOC(t) represents the state of charge of the battery at time t, E pz (t) and E vib (t) represent the electric energy generated by the piezoelectric material and the vibration energy harvesting device at time t, respectively. load (t) represents the load power of the robot at time t.

[0021] Compared with the prior art, the charging method of the intelligent robot has the following beneficial effects:

[0022] 1. The present invention realizes the efficient conversion and utilization of mechanical energy during the movement of the intelligent robot through the refined layout and installation of the energy collection device. By adopting piezoelectric materials with different characteristics for different parts and designing them into wavy, honeycomb or curved, and tensile structures, as well as selecting a cantilever beam piezoelectric crystal structure and optimizing the design of the electromagnetic induction vibration energy collection device, the efficiency and range of energy collection are improved, which not only broadens the frequency band and working range of energy collection, but also enables the intelligent robot to autonomously collect energy in various complex environments, thereby reducing its dependence on external power supplies and improving its autonomous operation capability and endurance.

[0023] 2. The present invention uses a microprocessor to monitor the battery power, voltage, and current parameters in real time, and in combination with the robot's current work tasks and external environmental conditions, it can formulate a dynamic power distribution strategy. When the battery power is low, it prioritizes fast charging of the battery. When the power is sufficient and the power generation power is high, the charging of auxiliary energy storage equipment is increased. In emergency tasks and insufficient power generation, power is distributed according to task priority and energy consumption requirements. This not only improves the efficiency of power utilization, but also ensures that the intelligent robot can operate stably under various working conditions, thereby improving its overall performance and reliability.

[0024] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 A flowchart of a charging method for an intelligent robot;

[0027] Figure 2 The present invention is a process framework diagram of a charging method for an intelligent robot. DETAILED DESCRIPTION

[0028] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0029] Embodiment 1

[0030] Logistics handling robot charging

[0031] Scenario setting: Logistics handling robots carry out cargo handling work in large warehouses. The working environment is relatively stable, but the robots need to start, stop, and turn frequently, and they will be under greater pressure when carrying heavier goods.

[0032] Charging method implementation steps:

[0033] Energy harvesting architecture construction (S100): For the bottom part, a multilayer piezoelectric ceramic composite material is used and designed into a wavy structure to better withstand the greater pressure when the robot is carrying goods and efficiently convert the pressure into electrical energy. At the joints of the robotic arm, a piezoelectric polymer material with good flexibility is selected to make a bending energy harvesting device to adapt to the flexion and extension of the joints. By analyzing the vibration spectrum of the robot, the main vibration frequency range is determined, and a vibration energy harvesting device with a cantilever beam piezoelectric crystal structure is selected, and its resonant frequency is optimized. At the same time, an electromagnetic induction vibration energy harvesting device is installed on the main frame, and appropriate coil turns, wire diameter, winding method and magnet parameters are designed to enhance the ability to capture vibration energy.

[0034] Energy collection triggers conversion (S200): When the robot starts to carry goods, the piezoelectric module at the bottom is subjected to pressure, the lattice distortion of the piezoelectric material generates a potential difference, and the charge is gathered into a DC signal through the collection circuit. The flexible piezoelectric device at the joint of the robot arm generates piezoelectric charge as the joint moves. The vibration generated by the movement of the robot is transmitted to the vibration energy collection device on the main frame. Electromagnetic induction generates an AC signal, which is converted into DC through a rectifier circuit and transmitted to the front-end preprocessing circuit together with the electric energy generated by the piezoelectric device. For example, during a handling process, the energy value of the piezoelectric material converted from mechanical energy to electrical energy within a period of time is calculated according to the energy collection formula of the piezoelectric material. The formula is: Where: E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], α pz is a comprehensive coefficient related to the performance of piezoelectric materials, F(t) is the time-varying force acting on the piezoelectric material, v(t) is the velocity of the piezoelectric material at the force point, ω is the angular frequency of vibration, is the phase angle, γ pz It is a coefficient related to the geometric shape and installation method of the piezoelectric material. The electromagnetic induction vibration energy harvesting device calculates the energy value converted from the robot vibration mechanical energy into electrical energy in a specific time period according to the vibration energy harvesting formula in the same time. The formula is: Where: E vib is the total energy collected by the vibration energy harvesting device in the time period [t1, t2], β vibis a comprehensive coefficient related to the performance of the electromagnetic induction device, B(t) is the magnetic field strength that changes with time, A(t) is the effective area of ​​the coil, and μ vib is a coefficient related to the vibration frequency and direction.

[0035] Power transmission purification and control (S300): Use highly conductive copper wires, select appropriate cross-sectional area and length according to the transmission power and current, use cables with multi-layer shielding structure, and transmit power to the power management system according to the shortest path principle. The rectifier bridge in the front-end preprocessing circuit converts AC power into DC power, and the filter network filters out clutter signals. The voltage regulator diode and the intelligent voltage regulator chip work together to stabilize the voltage within a range suitable for subsequent processing and storage, such as stabilizing it at 12V.

[0036] Intelligent power management decision (S400): The microprocessor of the power management system monitors the parameters of battery power, voltage, and current in real time. When the battery power of the robot is at a low level (such as less than 30%) during the handling process and is in a non-emergency handling task stage, the energy consumption of non-essential functional modules such as cargo scanning and identification is suspended, and all the collected power is used for fast charging of the battery. If the battery power is sufficient (such as higher than 80%) and the power generation power of the energy collection device is high, the charging of the auxiliary energy storage device is increased while ensuring the normal operation of the robot. At this time, the power allocated to the battery charging at time t is calculated according to the real-time output power of the energy collection device and the current state of the battery and the robot through the battery charging power allocation formula. The formula is: P ch (t) = λ(t)·(E pz (t)+E vib (t))·f(SOC(t), T(t), P load (t)), where: P ch (t) is the power allocated to the battery for charging at time t, λ(t) is the power allocation coefficient that varies with time, and E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], E vib is the total energy collected by the vibration energy harvesting device in the time period [t1, t2], f(SOC(t),T(t),P load (t)) is a function of the battery state of charge SOC(t), temperature T(t) and load power P load (t), the formula is: f(SOC(t), T(t), P load (t))=b1×SOC(t)+b2×T(t)+b3×P load (t)+b4, where b1, b2, b3 and b4 are coefficients determined according to the actual system characteristics, SOC(t) represents the state of charge of the battery at time t, E pz (t) and Evib (t) represent the electrical energy generated by the piezoelectric material and the vibration energy harvesting device at time t, T(t) represents the temperature at time t, P load (t) represents the load power of the robot at time t. According to the real-time output power of the energy collection device and the current state of the battery and the robot, the power allocated to the battery charging at time t is calculated. At the same time, the energy consumption adjustment formula of the robot functional module is used to adjust the energy consumption of the non-critical functional modules of the robot at time t according to the battery charging requirements and energy collection conditions: P func (t) = P func0 (t)·(1-δ(t)·g(SOC(t),(E pz (t)+E vib (t)),P load (t))), where: P func (t) is the energy consumption power of a functional module of the robot after adjustment at time t, P func0 (t) is the original energy consumption power of the functional module at time t, δ(t) is the energy consumption adjustment coefficient that changes with time, E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], E vib is the total energy collected by the vibration energy harvesting device during the time period [t1, t2], g(SOC(t), (E pz (t)+E vib (t)), P load (t)) is a function of the battery state of charge, total energy harvested, and load power, and is calculated as:

[0037] g(SOC(t),(E pz (t)+E vib (t))P load (t)) = a1 × SOC (t) + a2 × (E pz (t)+E vib (t))+a3×P load (t)+a4

[0038] , where a1, a2, a3 and a4 are coefficients that need to be determined according to the actual system characteristics, SOC(t) represents the state of charge of the battery at time t, E pz (t) and E vib (t) represent the electric energy generated by the piezoelectric material and the vibration energy harvesting device at time t, respectively. load (t) represents the load power of the robot at time t.

[0039] Charging system optimization and upgrade (S500): Through the analysis of the robot's long-term operation data, it was found that the energy collection efficiency was low at certain vibration frequencies during the handling process. The energy collection device was improved using new composite materials and microstructure optimization methods so that it can automatically adjust the working state according to different vibration frequencies and broaden the energy collection frequency band. At the same time, artificial intelligence algorithms were introduced to optimize the power management system. According to the warehouse environment and the working conditions of the handling task volume, more accurate power management decisions can be made to improve charging efficiency.

[0040] To sum up, in this embodiment, the charging method of the logistics handling robot is optimized according to the characteristics of warehouse operations, energy collection triggers the conversion link, the materials and devices of the adaptation parts are reasonably designed, the motion energy is effectively collected, energy calculation provides a basis for management, and the power transmission purification and regulation ensures high efficiency and stability. Intelligent power management decisions are flexibly allocated based on power and tasks to improve energy efficiency, and the charging system is optimized and upgraded to adapt to long-term operation. In short, this method improves the robot's energy self-sufficiency rate, reduces dependence on external charging, and enhances the continuity and efficiency of logistics handling operations, which is of great significance to the development of automation in the logistics industry.

[0041] In summary, the charging method of the logistics handling robot shows good adaptability and practicality in large warehouse handling scenarios. Through the carefully designed energy collection trigger conversion link, suitable piezoelectric materials and structures are selected for the bottom and arm joints, combined with the optimized vibration energy collection device, the mechanical energy in the robot movement is effectively converted into electrical energy. In the power transmission purification and regulation stage, reasonable material selection and wiring ensure stable power transmission, and after processing, stable voltage is provided for subsequent use. Intelligent power management decisions flexibly allocate power according to battery status and task conditions to improve charging efficiency. Continuous optimization and upgrading of the charging system further enhances the energy collection capability and the accuracy of management strategies, providing strong support for the long-term and efficient operation of the logistics handling robot, reducing dependence on external charging facilities, and improving overall work efficiency and stability.

[0042] Embodiment 2:

[0043] Rescue Detection Robot Charging

[0044] Scenario setting: The rescue detection robot performs search and rescue tasks in the complex environment of earthquake ruins. The environment is unstable and the terrain is complex. The robot needs to climb and cross obstacles and may be subjected to a certain degree of impact and vibration.

[0045] Charging method implementation steps:

[0046] Energy harvesting architecture construction (S100): The bottom is made of a honeycomb structure made of multi-layer piezoelectric ceramic composite materials to enhance pressure resistance and energy collection efficiency. The flexible piezoelectric device at the joint of the robotic arm is made of high-performance piezoelectric polymer material and made into a tensile structure to adapt to complex joint movements. For complex vibration environments, through precise measurement and analysis of vibration spectra, suitable piezoelectric effect vibration energy harvesting devices and electromagnetic induction vibration energy harvesting devices are selected, and optimized designs are performed to ensure that vibration energy of different directions and frequencies can be effectively captured.

[0047] Energy collection trigger conversion (S200): During the rescue operation, when the robot walks and climbs on the ruins, the piezoelectric module at the bottom and the piezoelectric devices at the joints of the robot arm continuously generate electrical energy. For example, during a complex action (such as within a time interval), the energy value collected by the piezoelectric material is calculated according to the piezoelectric material energy collection formula, which is: Where: E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], α pz is a comprehensive coefficient related to the performance of piezoelectric materials, F(t) is the time-varying force acting on the piezoelectric material, v(t) is the velocity of the piezoelectric material at the force point, ω is the angular frequency of vibration, is the phase angle, γ pz It is a coefficient related to the geometric shape and installation method of the piezoelectric material. The electromagnetic induction vibration energy harvesting device calculates the collected energy value according to the vibration energy harvesting formula, which is: Where: E vib is the total energy collected by the vibration energy harvesting device in the time period [t1, t2], β vib is a comprehensive coefficient related to the performance of the electromagnetic induction device, B(t) is the magnetic field strength that changes with time, A(t) is the effective area of ​​the coil, and μ vib It is a coefficient related to the vibration frequency and direction. At the same time, the vibration of the robot during movement is converted into electrical energy through the vibration energy collection device on the main frame and transmitted to the front-end preprocessing circuit.

[0048] Power transmission, purification and regulation (S300): Considering the complexity of the rescue environment, silver wires with good flexibility and high conductivity are selected to ensure the stability of power transmission under various movements of the robot. Multi-layer shielded cables are used to prevent external interference. The cables are laid out along the shortest path to transmit power to the power management system. The front-end preprocessing circuit rectifies, filters and stabilizes the power to ensure power quality and stabilize the voltage for subsequent use.

[0049] Intelligent power management decision (S400): The microprocessor monitors the battery status and robot working conditions in real time. When the robot performs an emergency rescue task (such as detecting signs of life) and the energy collection device is insufficient, the battery power is allocated first to ensure the stable operation of the power system and the control system, ensuring that the robot can successfully complete key tasks. At the same time, according to the task priority and energy consumption requirements, the energy consumption of other functional modules is reasonably adjusted, such as appropriately reducing the transmission power of the communication module. If the battery power is low and no emergency task is performed, the robot will find a relatively safe position, suspend some non-critical functions, and use the collected power for charging. At this time, the power allocated to the battery charging at time t is also calculated according to the battery charging power allocation formula. The formula is: P ch (t) = λ(t)·(E pz (t)+E vib (t))·f(SOC(t), T(t), P load (t)), where: P ch (t) is the power allocated to the battery for charging at time t, λ(t) is the power allocation coefficient that varies with time, and E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], E vib is the total energy collected by the vibration energy harvesting device in the time period [t1, t2], f(SOC(t), T(t), P load (t)) is a function of the battery state of charge SOC(t), temperature T(t) and load power P load (t) related functions, through the robot function module energy consumption adjustment formula according to the battery charging requirements and energy collection conditions, the energy consumption power formula of the robot non-critical function module at time t is adjusted as follows: func (t) = P func0 (t)·(1-δ(t)·g(SOC(t),(E pz (t)+E vib (t)), P load (t))), where: P func (t) is the energy consumption power of a functional module of the robot after adjustment at time t, P func0 (t) is the original energy consumption power of the functional module at time t, δ(t) is the energy consumption adjustment coefficient that changes with time, E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], E vib is the total energy collected by the vibration energy harvesting device during the time period [t1, t2], g(SOC(t), (E pz (t)+E vib (t)), P load (t)) is a function of the battery state of charge, the total energy harvested, and the load power.

[0050] Charging system optimization and upgrade (S500): Based on the actual operation data at the rescue site, it was found that the energy collection device had energy loss when the robot moved on certain special terrains. The piezoelectric material was improved using new composite materials to improve the energy conversion efficiency. Artificial intelligence algorithms were introduced into the power management system so that it could intelligently formulate the optimal power management strategy according to the different working conditions at the rescue site (such as ruins structure and temperature), extend the robot's working time at the rescue site, and improve rescue efficiency.

[0051] In summary, the charging solution for the rescue detection robot performs well in complex and dangerous earthquake ruins rescue scenarios. The specially designed bottom and arm joint energy collection devices, combined with vibration energy collectors customized for complex vibration environments, ensure that the robot can fully collect energy during climbing and crossing actions. The particularity of the rescue environment is taken into account during the power transmission process, and high-quality wires and shielded cables are selected to ensure stable power transmission. The intelligent power management system gives priority to key functions according to emergency mission requirements, and flexibly adjusts the energy consumption of functional modules according to the battery power and energy collection conditions to improve energy utilization. Continuous optimization and upgrading enable the system to adapt to different rescue conditions and enhance the robot's endurance. This helps to more efficiently search for signs of life and transmit information during rescue missions, improve the success rate and effectiveness of rescue operations, and provide more reliable technical guarantees for rescue work.

[0052] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A charging method for an intelligent robot, characterized in that: The specific steps of the charging method are: S100, energy collection architecture construction: Through mechanical analysis and actual working condition monitoring methods, the motion posture, force distribution and vibration of the intelligent robot in daily operation are analyzed, and piezoelectric materials suitable for each part are selected to make energy collection devices. Electromagnetic induction vibration energy collection devices are installed on the main frame, and they are connected by electrical connection and mechanical fixing. Through various devices, the mechanical energy generated by the robot's movement is converted into electrical energy and transmitted, laying a solid foundation for the subsequent charging process; S200, energy collection trigger conversion: When the robot starts to perform tasks, the piezoelectric module at the bottom is subjected to pressure, and the internal piezoelectric material lattice is distorted, causing the directional movement of positive and negative charges, generating a potential difference. The charges are gathered into a DC signal under the action of the charge collection circuit of the bottom device. The flexible piezoelectric device at the joint of the robot arm continuously changes the force state with the flexion, extension and rotation of the joint, generating piezoelectric charges. At the same time, the vibration generated by the movement of the robot is transmitted to the vibration energy collection device on the main frame. According to the principle of electromagnetic induction, its coil cuts the magnetic lines of force in the magnetic field, generating an AC signal, which is converted into DC through the built-in rectifier circuit and transmitted to the front-end preprocessing circuit together with the electric energy generated by the piezoelectric device; S300, power transmission purification and control: Use highly conductive metal materials as transmission wires, select the cross-sectional area and length of the wires according to the transmission power and current size, and use cables with multi-layer shielding structures. Follow the shortest path principle for wiring to transmit current to the power management system. The rectifier bridge in the front-end preprocessing circuit converts the AC generated by the vibration energy collection device into DC, and uses the unidirectional conductivity of the diode to achieve unidirectional and stable current flow. Through the filter network composed of filter capacitors and inductors, according to the charging and discharging characteristics of the capacitors and the hindering effect of the inductors on current changes, remove the clutter signals from the energy collection end and the transmission line. The voltage regulator diode and the intelligent voltage regulator chip work together to stabilize the voltage within a range suitable for subsequent processing and storage according to the voltage requirements of the back-end battery and electrical equipment. S400, intelligent power management decision-making: The power management system's microprocessor monitors the battery's power, voltage, and current parameters in real time, and formulates a dynamic power allocation strategy based on the robot's current work tasks and external environmental conditions; S500, charging system optimization and upgrade: Through actual operation data feedback, the charging system is optimized in all aspects. In terms of piezoelectric materials, new composite materials and microstructure optimization methods are used to introduce an adaptive adjustment mechanism for the energy collection device, so that it can automatically adjust the working state according to different vibration frequencies and stress conditions, and broaden the frequency band and operating range of energy collection. For the power management system, in terms of the power management system, an artificial intelligence algorithm is introduced to learn and analyze a large amount of historical data, so that it can make power management decisions according to working conditions.

2. The charging method of an intelligent robot according to claim 1, characterized in that: The S100, in the selection of piezoelectric materials and the design of energy collection devices in the construction of the energy collection architecture, uses a multilayer piezoelectric ceramic composite material with high compressive strength and high piezoelectric constant for the bottom part that is subjected to greater pressure, and is designed into a wavy or honeycomb structure; for the joints of the robotic arm, a piezoelectric polymer material with good flexibility is selected to make a bending or stretching energy collection device.

3. The charging method of an intelligent robot according to claim 1, characterized in that: In S100, the energy collection architecture is constructed, and the vibration energy collection device is selected and installed. Through actual measurement and analysis of the robot's vibration spectrum, the main vibration frequency range and amplitude distribution are determined, and a vibration energy collection device based on the piezoelectric effect is selected. A cantilever beam piezoelectric crystal structure is selected, and the resonant frequency is optimized by adjusting the size, shape and position of the mass block to match it with the main vibration frequency of the robot. For the electromagnetic induction vibration energy collection device, the number of turns, wire diameter, winding method of the coil, and the material, shape and magnetic field strength of the magnet are designed to enhance the coupling between the coil and the magnetic field and capture the vibration energy.

4. The charging method of an intelligent robot according to claim 1, characterized in that: In the energy collection trigger conversion, the energy value of the piezoelectric material converted from the mechanical energy of the robot movement to the electrical energy in a specific time period is calculated by using the piezoelectric material energy collection formula in S200. The formula is: Where: E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], α pz is a comprehensive coefficient related to the performance of piezoelectric materials, F(t) is the time-varying force acting on the piezoelectric material, v(t) is the velocity of the piezoelectric material at the force point, ω is the angular frequency of vibration, is the phase angle, γ pz is a coefficient related to the geometry and mounting method of the piezoelectric material.

5. The charging method of an intelligent robot according to claim 1, characterized in that: In the energy collection trigger conversion, S200 calculates the energy value of the electromagnetic induction vibration energy collection device converted from the robot vibration mechanical energy into electrical energy within a specific time period through the vibration energy collection formula, and the formula is: Where: E vib is the total energy collected by the vibration energy harvesting device in the time period [t1, t2], β vib is a comprehensive coefficient related to the performance of the electromagnetic induction device, B(t) is the magnetic field strength that changes with time, A(t) is the effective area of ​​the coil, and μ vib is a coefficient related to the vibration frequency and direction.

6. The charging method of an intelligent robot according to claim 1, characterized in that: The S400, power management strategy in intelligent power management decision-making: when the battery power is at a low level and the robot is in a non-critical task stage, the energy consumption of non-essential functional modules is suspended, and all the collected power is used for fast charging of the battery; when the battery power is sufficient and the power generation power of the energy collection device is high, the charging of the auxiliary energy storage device is increased while ensuring the normal operation of the robot; when the robot performs an emergency task and the energy collection device generates insufficient power, the battery power is allocated according to the task priority and energy consumption requirements to ensure the stable operation of the power system and control system, and at the same time a low power warning signal is sent to the operator to prompt timely external charging or battery replacement.

7. The charging method of an intelligent robot according to claim 1, characterized in that: In the S400, the intelligent power management decision is made by using the battery charging power allocation formula to calculate the power allocated to the battery charging at time t according to the power output of the energy collection device in real time and the current state of the battery and the robot. The formula is: P ch (t) = λ(t)·(E pz (t)+E vib (t))·f(SoC(t),T(t),P load (t)) Where: P ch (t) is the power allocated to the battery for charging at time t, λ(t) is the power allocation coefficient that varies with time, and E pz is the total energy collected by the piezoelectric material during the time period [t1, 2], E vib is the total energy collected by the vibration energy harvesting device in the time period [t1, 2], f(SOC(t), T(t), P load (t)) is a function of the battery state of charge SOC(t), temperature T(t) and load power P load (t), the formula is: f(SOC(t),T(t),P load (t))=b1×SOC(t)+b2×T(t)+b3×P load (t)+b4, where b1, b2, b3 and b4 are coefficients determined according to the actual system characteristics, SOC(t) represents the state of charge of the battery at time t, E pz (t) and E vib (t) represent the electrical energy generated by the piezoelectric material and the vibration energy harvesting device at time t, T(t) represents the temperature at time t, P load (t) represents the load power of the robot at time t.

8. The charging method of an intelligent robot according to claim 1, characterized in that: In the S400, the intelligent power management decision is made through the robot function module energy consumption adjustment formula according to the battery charging demand and energy collection situation, and the energy consumption power formula of the robot non-critical function module at time t is adjusted as follows: func (t) = P func0 (t)·(1-δ(t)·g(SOC(t),(E pz (t)+E vib (t)), P load t)))Where: P func (t) is the energy consumption power of a functional module of the robot after adjustment at time t, P func0 (t) is the original energy consumption power of the functional module at time t, δ(t) is the energy consumption adjustment coefficient that changes with time, E pz is the total energy collected by the piezoelectric material during the time period [t1, t2], E vib is the total energy collected by the vibration energy harvesting device during the time period [t1, t2], g(SOC(t),(E pz (t)+E vib (t)),P load (t)) is a function of the battery state of charge, total energy harvested, and load power, and is calculated as: g(SOC(t),(E pz (t)+E vib (t)),P load (t))=a1×SOC(t)+a2×(E pz (t)+E vib (t))+a3×P load (t)+a4, Where a1, a2, a3 and a4 are coefficients that need to be determined according to the actual system characteristics, SOC(t) represents the state of charge of the battery at time t, E pz (t) and E vib (t) represent the electric energy generated by the piezoelectric material and the vibration energy harvesting device at time t, respectively. load (t) represents the load power of the robot at time t.

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