Lightweight lower limb exoskeleton robot system for iron tower climbing operation

Abstract

The invention relates to the technical field of exoskeleton robots, and discloses a lightweight lower limb exoskeleton robot system for iron tower climbing operation. The system comprises a bionic joint driving module which comprises a two-degree-of-freedom hip joint driving sub-module, a single-degree-of-freedom knee joint assisting sub-module and an ankle joint stabilizing sub-module; the distributed power transmission module comprises a waist driving motor sub-module and an elastic energy storage sub-module; the dynamic load balancing module comprises an adjustable supporting rod sub-module and a force distribution calculation sub-module; the multi-mode control module comprises a sensing submodule, a decision submodule and an execution submodule. An asymmetric structure is adopted to be matched with four-connecting-rod transmission and waist centralized driving, and efficient power transmission and movement flexibility improvement are achieved; by means of an adjustable supporting rod and a force distribution mechanism, the supporting force is dynamically adjusted according to real-time posture data, and the adaptability problem of a traditional fixed supporting structure is solved; the climbing intention is accurately predicted by fusing multi-sensor data, and dynamic adjustment of the joint torque and the supporting force is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of exoskeleton robots, and particularly to a lightweight lower limb exoskeleton robot system for tower climbing operations. Background Art

[0002] In the power industry, as a key support structure for transmission lines, towers require crucial maintenance and inspection work. Traditionally, these operations mainly rely on manual tower climbing by workers. However, manual tower climbing has many drawbacks, seriously restricting work efficiency and safety.

[0003] In terms of work efficiency, the process of manual tower climbing is slow. Each climb requires workers to expend a large amount of physical strength and time. This problem is particularly prominent when facing tall and complex tower structures and tasks that require frequent up-and-down tower climbs. For example, in the transmission line relocation and construction caused by urban construction, due to the complexity of the adjacent energized lines and the cumbersome power outage and construction procedures, workers not only have to carefully deal with the complex environment but also frequently climb the tower for inspection and adjustment, greatly reducing the overall work progress. When the workload of the annual comprehensive inspection work is full, the problem of low efficiency becomes even more prominent. In terms of safety risks, high-altitude climbing operations themselves are extremely dangerous. During the climbing process, workers are extremely vulnerable to factors such as poor outdoor construction environment, fatigue operations, and human defense oversights. A slight carelessness may lead to a fall accident. At the same time, since there may be energized lines around the tower, when working near energized lines, workers also face the risk of accidentally climbing onto the energized side, which is very likely to cause serious personal injuries and equipment damage accidents.

[0004] To solve the problem of manual tower climbing, some auxiliary devices or apparatuses have been developed. For example, some existing tower anti-climbing devices on the market include foot studs or temporary warning devices suspended on the tower body, permanent tower retreat enclosures for anti-climbing, and tower body enclosure-type anti-climbing devices. However, these devices are mainly used to prevent unauthorized personnel from climbing, and their climbing assistance for workers is limited. Even after installation, it becomes more time-consuming and laborious for normal company workers to climb the tower, with the average tower climbing time increasing by 15 - 20 minutes. Although research has been conducted on power tower climbing robots, such as mechanical clamping mechanism power tower climbing robots and electromagnetic adsorption climbing robots designed by imitating insect peristalsis, their movement methods are mainly step-by-step and peristaltic leapfrog, and their static positioning methods are mechanical clamping and magnetic adsorption. Although the mechanical clamping type can stably clamp, its structure is complex and the gripper has poor versatility; the magnetic adsorption type has a simple structure but poor stability. Moreover, most of the existing designs fail to effectively utilize the foot studs on the angle steel and have difficulties in crossing obstacles such as bolt areas on power towers, making it difficult to promote and apply.

[0005] At present, there is an urgent need for a technical solution that can significantly improve the efficiency of tower climbing operations, ensure the safety of operators, and at the same time have good adaptability and practicality. Summary of the Invention

[0006] The main object of the present invention is to provide a lightweight lower limb exoskeleton robot system for tower climbing operations, aiming to solve at least one of the above technical problems.

[0007] To achieve the above object, the present invention provides a lightweight lower limb exoskeleton robot system for tower climbing operations, including: A bionic joint drive module, including a two-degree-of-freedom hip joint drive sub-module, a single-degree-of-freedom knee joint assistance sub-module, and an ankle joint stabilization sub-module, which is used to adopt an asymmetric structure with two degrees of freedom for the hip joint and one degree of freedom for the knee joint, cooperate with a four-bar linkage transmission and a waist centralized drive, and automatically adjust the damping through the ankle joint stabilization sub-module to suppress vibration; A distributed power transmission module, including a waist drive motor sub-module and an elastic energy storage sub-module, which is used to transmit power to the hip joint and dynamically adjust the energy storage characteristics according to the pedaling force; A dynamic load balancing module, including an adjustable support rod sub-module and a force distribution calculation sub-module, which is used to dynamically adjust the supporting force based on real-time attitude data; A multi-modal control module, including a sensing sub-module, a decision-making sub-module, and an execution sub-module, which is used to fuse and analyze multi-source sensor data to predict the climbing intention and control the power output.

[0008] In some embodiments, the bionic joint drive module, the distributed power transmission module, the dynamic load balancing module, and the multi-modal control module are connected through mechanical interfaces and electrical signals to form a physical control closed-loop to achieve real-time feedback and coordination among the modules.

[0009] In some embodiments, the two-degree-of-freedom hip joint drive sub-module includes a four-bar linkage mechanism, a flexion and extension unit, and an abduction and adduction unit; wherein, The flexion and extension unit is used to achieve flexion and extension movements, and the abduction and adduction unit is used to achieve abduction and adduction movements; the length ratio of the active link to the driven link of the four-bar linkage mechanism is 1:3, and the abduction and adduction unit adopts an arc-shaped guide rail and a ball bearing structure to achieve a preset angle of lateral deflection.

[0010] In some embodiments, the single-degree-of-freedom knee joint assistance sub-module includes a spring-ratchet energy storage unit and a pressure trigger; wherein, The spring-ratchet energy storage unit cooperates with the pressure trigger to obtain the kinetic energy generated during pedaling and convert the kinetic energy into potential energy to achieve the combination of energy recovery and auxiliary drive.

[0011] In some embodiments, the ankle joint stabilizer sub-module includes a passive shock absorber, a damping regulating valve, and a plantar pressure sensor array; wherein, The passive shock absorber is used to absorb the impact force of the iron tower structure during climbing; the damping regulating valve is used to automatically adjust the damping coefficient according to the terrain inclination, and the plantar pressure sensor array is used to feedback sensor data to the perception sub-module of the multi-modal control module in real time. The damping regulating valve and the plantar pressure sensor array cooperate with each other to form a dynamic response mechanism.

[0012] In some embodiments, the waist drive motor sub-module includes a double-output shaft motor, a carbon fiber transmission connecting rod, and a quick-release interface; wherein, The double-output shaft motor is used to drive both hip joints simultaneously to achieve the consistency and stability of power output; the carbon fiber transmission connecting rod is used to transmit power to the hip joint, and the power output by the double-output shaft motor is transmitted to the double-degree-of-freedom hip joint drive sub-module through the carbon fiber transmission connecting rod, and the lower limb and the waist drive motor sub-module are quickly separated through the quick-release interface.

[0013] In some embodiments, the elastic energy storage sub-module includes a variable stiffness helical spring, a ratchet group, and an electromagnetic release; wherein, the variable stiffness helical spring and the ratchet group are used to adaptively store energy according to different pedaling forces; the electromagnetic release is used to receive instructions from the decision-making sub-module of the multi-modal control module and control energy release according to the instructions.

[0014] In some embodiments, the adjustable support rod sub-module includes a pneumatic telescopic rod, a force sensor, and a micro air pump; the force sensor is used to monitor the load pressure in real time, and based on the load pressure, cooperate with the micro air pump to control the telescopic of the pneumatic telescopic rod to form a closed-loop feedback regulation mechanism; The force distribution calculation sub-module includes an IMU sensor, a fuzzy logic controller, and a pneumatic valve group; the IMU sensor is used to collect attitude data, the fuzzy logic controller is used to calculate the optimal support force distribution ratio based on the collected attitude data, and control the pneumatic valve group to adjust the support rod output force of the adjustable support rod sub-module according to the optimal support force distribution ratio.

[0015] In some embodiments, the perception sub-module includes a plantar pressure sensor, an inertial measurement unit, and a joint angle encoder, and is used to collect gait phase, joint movement angle, and terrain inclination data, and obtain exoskeleton operation state information according to the gait phase, joint movement angle, and terrain inclination data; The decision-making sub-module includes an embedded processor, a fuzzy logic algorithm library, and a security policy database, and is used to predict the climbing intention based on the exoskeleton operation status information, and calculate the target torque of each joint and the output force value of the support rod of the adjustable support rod sub-module.

[0016] In some embodiments, the execution sub-module includes a motor driver, a pneumatic valve controller, and an electromagnetic release controller; wherein, The motor driver is used to output a PWM signal according to the target torque of each joint and the output force value of the support rod to control the rotation speed and steering of the motor; The pneumatic valve controller is used to adjust the opening of the pneumatic valve according to the target torque of each joint and the output force value of the support rod; The electromagnetic release controller is used to output an instruction to the elastic energy storage sub-module according to the target torque of each joint and the output force value of the support rod to control the energy release timing of the electromagnetic release of the elastic energy storage sub-module.

[0017] The present invention provides a lightweight lower limb exoskeleton robot system for tower climbing operations, including: a bionic joint drive module, including a two-degree-of-freedom hip joint drive sub-module, a single-degree-of-freedom knee joint assistance sub-module, and an ankle joint stability sub-module, which is used to adopt an asymmetric structure of two degrees of freedom for the hip joint and one degree of freedom for the knee joint, cooperate with a four-bar linkage transmission and a waist centralized drive, and automatically adjust the damping through the ankle joint stability sub-module to suppress vibration; a distributed power transmission module, including a waist drive motor sub-module and an elastic energy storage sub-module, which is used to transmit power to the hip joint and dynamically adjust the energy storage characteristics according to the pedaling force; a dynamic load balancing module, including an adjustable support rod sub-module and a force distribution calculation sub-module, which is used to dynamically adjust the support force based on real-time attitude data; a multi-modal control module, including a sensing sub-module, a decision-making sub-module, and an execution sub-module, which is used to fuse and analyze multi-source sensor data to predict the climbing intention and control the power output. In the present invention, an asymmetric structure of two degrees of freedom for the hip joint and one degree of freedom for the knee joint is adopted, combined with a four-bar linkage transmission and a waist centralized drive, which not only strengthens the lateral stability to adapt to complex climbing movements, but also amplifies the torque through the leverage ratio and reduces the motor power requirement, realizing the efficient transmission of power and the improvement of movement flexibility; at the same time, the ankle joint stability sub-module automatically adjusts the damping to suppress vibration. The dynamic load balancing module uses the adjustable support rod and the force distribution mechanism to dynamically adjust the support force according to the real-time attitude data, solving the adaptability problem of the traditional fixed support structure; the multi-modal control module fuses multi-sensor data to accurately predict the climbing intention, realizing the dynamic adjustment of joint torque and support force, so that the lightweight lower limb exoskeleton robot system for tower climbing operations is significantly superior to the prior art in terms of functional integration, safety, and operation adaptability. Description of the Drawings

[0018] Figure 1 This is a schematic diagram of modules of an embodiment of a lightweight lower limb exoskeleton robot system for tower climbing operations according to the present invention; Figure 2 This is a schematic diagram of the structural connection relationship involved in the embodiment solution of the present invention; Figure 3 This is a schematic diagram of the control logic of the hip joint drive sub-module involved in the embodiment solution of the present invention; Figure 4 This is a schematic diagram of the control logic of the knee joint assistance sub-module involved in the embodiment solution of the present invention; Figure 5 This is a schematic diagram of the control logic of the ankle joint stability sub-module involved in the embodiment solution of the present invention; Figure 6 This is a schematic diagram of the control logic of the waist drive sub-module involved in the embodiment solution of the present invention; Figure 7 This is a schematic diagram of the control logic of the elastic energy storage sub-module involved in the embodiment solution of the present invention; Figure 8 This is a schematic diagram of the control logic of the adjustable support rod sub-module involved in the embodiment solution of the present invention; Figure 9 This is a schematic diagram of the control logic of the force distribution calculation sub-module involved in the embodiment solution of the present invention; Figure 10 This is a schematic diagram of the control logic of the sensing sub-module involved in the embodiment solution of the present invention; Figure 11 This is a schematic diagram of the control logic of the decision-making sub-module involved in the embodiment solution of the present invention; Figure 12 This is a schematic diagram of the control logic of the execution sub-module involved in the embodiment solution of the present invention.

[0019] The realization of the object, functional features and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. Detailed implementation manners

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts belong to the scope of protection of the present invention.

[0021] It should be noted that all directional indications (such as up, down, left, right, front, back...) in the embodiments of the present invention are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly.

[0022] In addition, the descriptions involving "first", "second", etc. in the present invention are only for descriptive purposes, and should not be construed as indicating or implying their relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between various embodiments may be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement them. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the protection scope required by the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0023] The present invention provides a lightweight lower limb exoskeleton robot system for tower climbing operations.

[0024] An embodiment of the present invention provides a lightweight lower limb exoskeleton robot system for tower climbing operations. Refer to Figure 1 , Figure 1 which is a schematic diagram of modules of an embodiment of the lightweight lower limb exoskeleton robot system for tower climbing operations of the present invention.

[0025] As Figure 1 shown, the lightweight lower limb exoskeleton robot system for tower climbing operations includes: The bionic joint drive module 10, including a two-degree-of-freedom hip joint drive sub-module, a single-degree-of-freedom knee joint assist sub-module, and an ankle joint stabilization sub-module, is used to adopt an asymmetric structure with two degrees of freedom for the hip joint and one degree of freedom for the knee joint, cooperate with four-bar linkage transmission and centralized waist drive, and automatically adjust the damping through the ankle joint stabilization sub-module to suppress vibration; The distributed power transmission module 20, including a waist drive motor sub-module and an elastic energy storage sub-module, is used to transmit power to the hip joint and dynamically adjust the energy storage characteristics according to the pedaling force; The dynamic load balancing module 30, including an adjustable support rod sub-module and a force distribution calculation sub-module, is used to dynamically adjust the supporting force based on real-time attitude data; The multi-modal control module 40, including a sensing sub-module, a decision-making sub-module, and an execution sub-module, is used to fuse and analyze multi-source sensor data to predict the climbing intention and control the power output.

[0026] Specifically, the bionic joint drive module 10 (such as the bionic joint drive system shown in Figure 2 ) accurately adapts to complex actions such as striding and lateral movement during tower climbing through an asymmetric joint design. Compared with traditional symmetric joints, the movement flexibility is greatly improved; at the same time, the modular structure is convenient for maintenance and upgrading, reducing the use cost. As Figure 2As shown, the bionic joint drive system includes a hip joint drive sub-module with two degrees of freedom, a knee joint assist sub-module with one degree of freedom, and an ankle joint stabilization sub-module. Among them, the hip joint drive sub-module adopts a unique two-degree-of-freedom design, breaking the traditional symmetric layout, strengthening the lateral stability. Especially in actions such as crossing the cross-arm of a tower, it can effectively reduce the uneven force on the joints, improve the operation safety, and can flexibly achieve flexion / extension and adduction / abduction actions; the one-degree-of-freedom design of the knee joint assist sub-module combines a spring-ratchet energy storage unit, which stores energy efficiently during pedaling and releases assistance during leg lifting, reducing energy consumption by 30%-40% and significantly improving the endurance; the ankle joint stabilization sub-module senses terrain changes in real time through passive damping and pressure sensing, automatically adjusts the damping, suppresses vibrations, and ensures the stable standing and walking of operators on complex terrains.

[0027] Exemplarily, the distributed power transmission module 20 (such as Figure 2 the distributed power transmission system shown) includes a waist drive motor sub-module and an elastic energy storage sub-module. By adopting a waist centralized drive mode, the motor is far away from the legs, effectively reducing the inertial load on the legs and making the climbing action lighter; combined with the elastic energy storage sub-module, it realizes the recycling of energy and improves the system energy efficiency. As Figure 2 shown, the distributed power transmission system includes a drive motor module located at the waist and an elastic energy storage module located at the legs; among them, the waist drive motor module transmits power to the hip joint efficiently through a carbon fiber transmission connecting rod. The carbon fiber material has both high strength and lightweight characteristics, reducing the overall weight while ensuring stable power transmission; the quick-release interface design facilitates the disassembly of the equipment and meets the rapid switching requirements of different operation scenarios; the variable stiffness helical spring of the leg elastic energy storage module can dynamically adjust the energy storage characteristics according to the human pedaling force, accurately matching the force changes during climbing, ensuring the efficiency of energy storage and release, and precisely controlling the energy release timing through an electromagnetic release.

[0028] Specifically, the dynamic load balancing module 30 (such as Figure 2 the dynamic load balancing system shown) dynamically adjusts the supporting force based on real-time attitude data, effectively dispersing the human body weight. It can transfer 30%-50% of the body weight to the tower bracket, reducing the burden on the operator, thus avoiding the interference problem of traditional fixed support structures during multi-posture climbing and improving the operation fluency. As Figure 2 shown, the dynamic load balancing system includes an adjustable support rod module and a force distribution calculation module; among them, the adjustable support rod module is pneumatically driven, can extend and support during vertical climbing, quickly respond to load changes, maintain a stable connection between the human body and the tower, and contract and avoid during lateral movement to ensure flexible movement without limitation; the force distribution calculation module uses an IMU sensor and a fuzzy logic controller to achieve millisecond-level supporting force calculation and adjustment, adapt to complex and changeable operation environments, and accurately control the output force of the support rod through a pneumatic valve group.

[0029] Exemplarily, the multi-modal control module 40 (such as Figure 2 the multi-modal control system shown) fuses multi-source sensor data to achieve accurate prediction of the climbing intention. Compared with the traditional algorithm that only relies on height and weight calibration, the control accuracy is significantly improved; the safety redundancy design of dual-loop pneumatic drive and mechanical self-locking provides double protection for the operators and reduces the risk of high-altitude operations. As Figure 2 shown, the multi-modal control system includes a sensing module, a decision-making module, and an execution module; among them, the sensing module takes the plantar pressure sensor, the inertial measurement unit IMU, and the joint angle encoder as the core, and can collect data at a high sampling frequency of greater than or equal to 100 Hz and a low latency of less than 10 ms to ensure real-time and accurate information and comprehensively capture the human body movement state; the decision-making module uses the fuzzy logic algorithm to quickly analyze the sensed data, plan the joint torque and support force in advance, and make the assistance action seamlessly connect with the human intention; the execution module realizes precise control of the power output through the motor driver, the pneumatic valve controller, and the electromagnetic release to ensure the stable operation of the system.

[0030] In one embodiment, the bionic joint drive module, the distributed power transmission module, the dynamic load balancing module, and the multi-modal control module are connected through mechanical interfaces and electrical signals to form a physical control closed loop to achieve real-time feedback and coordination among the modules.

[0031] Exemplarily, as Figure 2 shown, the bionic joint drive system (i.e., the bionic joint drive module), the distributed power transmission system (i.e., the distributed power transmission module), the dynamic load balancing system (i.e., the dynamic load balancing module), and the multi-modal control system (i.e., the multi-modal control module) can be connected through mechanical interfaces and electrical signals to form a physical-control closed loop. In this embodiment, real-time feedback and coordination among the systems are achieved through the closed-loop design to ensure that the actions of each module are precisely consistent and improve the stability and reliability of the overall operation.

[0032] In one embodiment, the two-degree-of-freedom hip joint drive sub-module includes a four-bar mechanism, a flexion-extension unit, and an abduction-adduction unit; among them, the flexion-extension unit is used to achieve flexion-extension movement, and the abduction-adduction unit is used to achieve abduction-adduction movement; the length ratio of the active link to the driven link of the four-bar mechanism is 1:3, and the abduction-adduction unit adopts an arc-shaped guide rail and a ball bearing structure to achieve a preset angle of lateral deflection.

[0033] Specifically, as Figure 3 shown, the two-degree-of-freedom hip joint drive sub-module ( Figure 3The hip joint drive module shown in the figure adopts a four-bar linkage, in which the length ratio of the active link to the driven link of the four-bar linkage is 1:3, and the hip joint drive module includes a flexion and extension unit for realizing flexion and extension movement and an adduction and abduction unit for realizing adduction and abduction movement. The adduction and abduction unit adopts an arc guide rail and a ball bearing structure, and can achieve ±25° lateral deflection.

[0034] For example, in order to further improve the movement flexibility and power transmission efficiency of the hip joint in tower climbing operations, reduce the physical energy consumption of operators and enhance movement stability, the dual-degree-of-freedom hip joint drive submodule in this embodiment adopts a four-bar linkage, and the length ratio of the active link and the driven link of the four-bar linkage is 1:3. Compared with traditional worm gear and other transmission methods, the four-bar linkage effectively amplifies the motor output torque through a lever ratio of 1:3, while reducing the motor power demand, reducing the friction loss in the joint transmission process, and significantly improving the climbing efficiency; at the same time, the structure has good mechanical stability and can withstand large external force impacts during tower climbing, and the hip joint drive module includes a flexion and extension unit for realizing flexion and extension movement and an adduction and abduction unit for realizing adduction and abduction movement. The dual-degree-of-freedom design breaks the traditional exoskeleton symmetrical joint layout, and specifically strengthens the lateral stability of the hip joint in the tower climbing scenario, especially in asymmetric actions such as crossing crossarms and lateral shifting, which can effectively avoid the risk of joint injury caused by uneven force, and improve the safety and reliability of the operation.

[0035] Specifically, the adduction and abduction unit adopts an arc guide and ball bearing structure. The arc guide provides precise guidance for the adduction and abduction movements of the hip joint. Combined with the low-friction ball bearing, the hip joint can achieve a flexible lateral deflection of ±25°. This design can not only perfectly adapt to the frequent crossing, turning and other actions in tower climbing operations, but also improve the smoothness and comfort of the operator's movements by reducing the jamming phenomenon during the movement, and can achieve a lateral deflection of ±25°.

[0036] In one embodiment, the single-degree-of-freedom knee joint assist submodule comprises a spring-ratchet energy storage unit and a pressure trigger; wherein, The spring-ratchet energy storage unit cooperates with the pressure trigger to obtain the kinetic energy generated during pedaling and converts the kinetic energy into potential energy to achieve the combination of energy recovery and auxiliary drive.

[0037] Specifically, if Figure 4 As shown, the single-degree-of-freedom knee joint assist submodule ( Figure 4 The knee joint assist module shown in the figure includes a spring-ratchet energy storage unit and a pressure trigger. The spring stiffness of the spring-ratchet energy storage unit satisfies the formula: ,in, is the initial stiffness, is the non - linear coefficient, is the spring compression; during the pedaling stage, the spring of the spring - ratchet energy storage unit compresses to store energy, and the potential energy conversion efficiency is greater than or equal to 85%; during the leg - lifting stage, the pressure trigger releases the spring potential energy to assist the hip - flexion movement.

[0038] Exemplarily, in order to effectively reduce the energy consumption during tower climbing operations, fully recover human motion energy, and at the same time assist the operator to complete high - load leg - lifting actions, improving the overall operation efficiency and comfort, in this embodiment, the knee joint assistance sub - module includes a spring - ratchet energy storage unit and a pressure trigger, combining energy recovery and auxiliary drive. Compared with traditional exoskeletons driven by pure motors, the design of this embodiment can capture the kinetic energy generated during human pedaling and convert it into reusable potential energy, significantly reducing the system energy consumption; the spring - ratchet structure cooperates with the pressure trigger to achieve precise control of energy storage and release, avoiding energy waste. The spring stiffness of the spring - ratchet energy storage unit satisfies the formula: , where, is the initial stiffness, is the non - linear coefficient, is the spring compression. The non - linear stiffness design in this embodiment precisely matches the change characteristics of the human pedaling force. Under pedaling actions with different intensities, the spring can efficiently store energy. Compared with traditional linearly - stiffened springs, the energy storage efficiency is significantly improved. This characteristic enables the exoskeleton to better fit the human motion habit and reduce human - machine confrontation.

[0039] Specifically, during the pedaling stage, the spring of the spring - ratchet energy storage unit compresses to store energy, and the potential energy conversion efficiency ≥85%; the ultra - high energy conversion efficiency enables the energy generated by each pedaling to be fully utilized, effectively extending the battery life of the exoskeleton; at the same time, the energy storage process is stable without impact and will not interfere with the normal actions of the operator. During the leg - lifting stage, the pressure trigger releases the spring potential energy to assist the hip - flexion movement. The precise energy release timing perfectly matches the human leg - lifting rhythm, providing additional power support for the hip - flexion movement, reducing the burden on the leg muscles. Especially during long - term climbing operations, it can significantly relieve the fatigue of the operator and improve the continuous operation ability.

[0040] In one embodiment, the ankle joint stabilization sub - module includes a passive shock absorber, a damping regulating valve, and a plantar pressure sensor array; where the passive shock absorber is used to absorb the impact force of the tower structure during climbing; the damping regulating valve is used to automatically adjust the damping coefficient according to the terrain inclination, and the plantar pressure sensor array is used to real - time feedback sensor data to the perception sub - module of the multi - modal control module. The damping regulating valve and the plantar pressure sensor array cooperate with each other to form a dynamic response mechanism.

[0041] Specifically, asFigure 5 As shown, the ankle stabilization submodule ( Figure 5 The ankle joint stabilization module shown in the figure includes a passive shock absorber, a damping regulating valve and a plantar pressure sensor array. The damping regulating valve can automatically adjust the damping coefficient according to the terrain inclination, and the adjustment range is 0.5-2.0N・s / mm. The plantar pressure sensor array feeds back the foot contact status to the perception submodule of the multimodal control module in real time.

[0042] For example, in order to improve the stability and safety during the tower climbing operation, effectively cope with the complex and changeable working terrain, and provide accurate motion feedback data for the multimodal control module, in this embodiment, the ankle joint stabilization submodule includes a passive shock absorber, a damping regulating valve, and a plantar pressure sensor array, and a comprehensive ankle joint protection and data perception system is constructed through a three-in-one design. The passive shock absorber can absorb the impact force from the tower structure during the climbing process, reduce the vibration damage to the ankle joint, and provide a comfortable support experience for the operator; the damping regulating valve and the plantar pressure sensor array cooperate with each other to form a dynamic response mechanism. Compared with the traditional fixed damping structure, this embodiment can significantly improve the adaptability of the exoskeleton in complex terrain.

[0043] Specifically, the damping regulating valve can automatically adjust the damping coefficient according to the terrain inclination, and the adjustment range can be 0.5-2.0N・s / mm. The wide range of damping adjustment capability of this embodiment can enable the exoskeleton to maintain a stable posture in various working conditions such as flat crossarms and inclined brackets. When encountering steep terrain, the damping coefficient automatically increases to suppress excessive shaking of the joints; while when climbing steadily, the damping coefficient decreases to ensure the flexibility of the movement, effectively improving the operator's controllability and safety in different scenarios.

[0044] For example, the plantar pressure sensor array feeds back the foot contact status to the perception submodule of the multimodal control module in real time. The highly sensitive sensor array (plantar pressure sensor array) can capture the changes in the foot pressure distribution at a millisecond response speed, providing the system with accurate perception data such as gait phase and center of gravity offset. After these perception data are analyzed by the multimodal control module, the joint assistance and support force distribution can be adjusted in real time to achieve seamless human-machine collaboration. Compared with traditional single-point pressure detection, this embodiment can greatly improve the intelligent decision-making ability and motion control accuracy of the exoskeleton.

[0045] In one embodiment, the waist drive motor submodule includes a dual output shaft motor, a carbon fiber transmission connecting rod and a quick release interface; wherein, The dual-output shaft motor is used to drive both hip joints simultaneously to achieve the consistency and stability of power output; the carbon fiber transmission connecting rod is used to transmit power to the hip joint. The power output by the dual-output shaft motor is transmitted to the dual-degree-of-freedom hip joint drive sub-module through the carbon fiber transmission connecting rod, and the lower limb and the waist drive motor sub-module can be quickly separated through the quick-release interface.

[0046] Specifically, as Figure 6 shown, the waist drive sub-module of the distributed power transmission module ( Figure 6 the waist drive module shown) includes a dual-output shaft motor, a carbon fiber transmission connecting rod, and a quick-release interface. The power output by the dual-output shaft motor is transmitted to the hip joint drive sub-module (dual-degree-of-freedom hip joint drive sub-module) through the carbon fiber transmission connecting rod. The quick-release interface is used to separate the lower limb module from the waist module, and the disassembly time can be less than 30 seconds.

[0047] Exemplarily, in order to optimize the power transmission efficiency of the exoskeleton robot, reduce the inertial load of movement, simultaneously achieve efficient energy storage and precise release, meet the high energy consumption requirements of tower climbing operations, and improve the convenience of equipment maintenance, in this embodiment, the waist drive sub-module of the distributed power transmission module includes a dual-output shaft motor, a carbon fiber transmission connecting rod, and a quick-release interface, concentrating the power source on the waist. Compared with the traditional layout of integrated motors on the legs, this embodiment effectively reduces the inertial load of leg movement and makes the climbing action lighter and more flexible; the dual-output shaft motor can drive both hip joints simultaneously to ensure the consistency and stability of power output; the carbon fiber transmission connecting rod, with its high strength and lightweight characteristics, further reduces the overall equipment weight while ensuring lossless power transmission. The power output by the dual-output shaft motor is transmitted to the hip joint drive sub-module (dual-degree-of-freedom hip joint drive sub-module) through the carbon fiber transmission connecting rod. This transmission method reduces the energy loss of intermediate transmission components, improves the power transmission efficiency, provides a stable and strong driving force for the hip joint, and ensures the continuous supply of power during complex climbing actions. The quick-release interface is used to separate the lower limb module from the waist module, and the disassembly time can be less than 30 seconds. The quick disassembly design greatly improves the convenience of equipment maintenance. When the equipment fails or needs to be transported, it can be quickly disassembled; at the same time, the modular design facilitates subsequent upgrading and optimization of individual components and reduces the full life cycle cost of the equipment.

[0048] In one embodiment, the elastic energy storage sub-module includes a variable stiffness helical spring, a ratchet group, and an electromagnetic release; wherein, the variable stiffness helical spring and the ratchet group are used to adaptively store energy according to different pedaling forces; the electromagnetic release is used to receive the instruction of the decision-making sub-module of the multi-modal control module and control the energy release according to the instruction.

[0049] Specifically, asFigure 7 As shown, the elastic energy storage sub-module of the distributed power transmission module ( Figure 7 the elastic energy storage module shown), including a variable stiffness helical spring, a ratchet set, and an electromagnetic release, the stiffness of the variable stiffness helical spring changes non-linearly with the compression amount, and the electromagnetic release receives the instruction of the decision-making sub-module of the multi-modal control module to accurately control the energy release timing.

[0050] Exemplarily, the elastic energy storage sub-module of the distributed power transmission module includes a variable stiffness helical spring, a ratchet set, and an electromagnetic release. This elastic energy storage sub-module constructs an efficient energy recovery and reuse system, which effectively reduces the system energy consumption compared with the traditional single-motor drive mode; the variable stiffness helical spring cooperates with the ratchet set to adaptively store energy according to different pedaling forces of the human body, realizing the maximum recovery of energy. The stiffness of the variable stiffness helical spring changes non-linearly with the compression amount, and the non-linear stiffness characteristic accurately matches the dynamic change of the pedaling force during the human body movement, and can efficiently store energy under different pedaling forces. Compared with the traditional linear stiffness spring, this embodiment significantly improves the energy storage efficiency. The electromagnetic release receives the instruction of the decision-making sub-module of the multi-modal control module to accurately control the energy release timing. Through the collaborative work with the multi-modal control module, the electromagnetic release can release the stored energy at the most appropriate time according to the movement intention and actual action requirements of the operator, provide auxiliary power for joint movement, realize the perfect coordination of human-machine movement, and further improve the efficiency and comfort of climbing operations.

[0051] In one embodiment, the adjustable support rod sub-module includes a pneumatic telescopic rod, a force sensor, and a micro air pump; the force sensor is used to monitor the load pressure in real time, and based on the load pressure, cooperate with the micro air pump to control the expansion and contraction of the pneumatic telescopic rod, forming a closed-loop feedback adjustment mechanism; The force distribution calculation sub-module includes an IMU sensor, a fuzzy logic controller, and a pneumatic valve group; the IMU sensor is used to collect attitude data, and the fuzzy logic controller is used to calculate the optimal support force distribution ratio based on the collected attitude data, and control the pneumatic valve group to adjust the support rod output force of the adjustable support rod sub-module according to the optimal support force distribution ratio.

[0052] Specifically, as Figure 8 shown, the adjustable support rod sub-module of the dynamic load balancing module ( Figure 8 the adjustable support rod module shown), including a pneumatic telescopic rod, a force sensor, and a micro air pump. When climbing vertically, the pneumatic telescopic rod extends to transfer 30%-50% of the operator's body weight to the tower bracket. When moving horizontally, the pneumatic telescopic rod contracts to avoid movement interference.

[0053] Exemplarily, in order to effectively solve the problems of excessive human body load, posture imbalance and movement limitation in tower climbing operations, realize the intelligent distribution and dynamic adjustment of loads, and improve the operation safety and operation flexibility, the adjustable support rod sub-module of the dynamic load balancing module in this embodiment includes a pneumatic telescopic rod, a force sensor and a micro air pump. The adjustable support rod sub-module realizes intelligent support adjustment through pneumatic drive. Compared with the traditional fixed support structure, this embodiment can actively adapt to different operation postures; the force sensor monitors the load pressure in real time, and cooperates with the micro air pump to accurately control the telescopic of the pneumatic telescopic rod, forming a closed-loop feedback adjustment mechanism, significantly improving the accuracy and response speed of load distribution. When climbing vertically, the pneumatic telescopic rod extends to transfer 30%-50% of the operator's body weight to the tower bracket. By transferring part of the human body load to the tower structure, the burden on the operator's waist and legs is greatly reduced, the muscle fatigue degree is reduced, and the continuous operation time is extended; at the same time, the bearing pressure of the exoskeleton itself is reduced, and the service life of the equipment is improved. When moving horizontally, the pneumatic telescopic rod contracts to avoid movement interference, and the intelligent contraction design ensures that the exoskeleton will not collide with the tower components during complex climbing movements, effectively avoiding the falling risk caused by mechanical interference, and ensuring the safety and smoothness of the operator during side movement, crossing and other actions.

[0054] Specifically, as Figure 9 shown, the force distribution calculation sub-module of the dynamic load balancing module (such as the Figure 9 force distribution calculation module shown) includes an IMU sensor, a fuzzy logic controller and a pneumatic valve group. The fuzzy logic controller calculates the optimal support force distribution ratio based on the attitude data collected by the IMU sensor, and the pneumatic valve group adjusts the output force of the support rod of the adjustable support rod sub-module according to the calculation result. Among them, the output force range can be 200-800N.

[0055] Exemplarily, the force distribution calculation sub-module of the dynamic load balancing module includes an IMU sensor, a fuzzy logic controller, and a pneumatic valve group, constructing an intelligent decision-making system based on attitude perception. Compared with the traditional fixed force distribution scheme, the support force configuration can be optimized in real time and dynamically in this embodiment. The combination of the IMU sensor and the fuzzy logic controller can quickly process complex attitude data and output accurate force distribution strategies to adapt to the rapidly changing working conditions during tower climbing. The fuzzy logic controller calculates the optimal support force distribution ratio based on the attitude data collected by the IMU sensor, quickly analyzes information such as the body tilt angle and movement trend through a non-linear algorithm, and accurately matches the load requirements in different postures. Even under extreme conditions such as strong winds and sudden terrain changes, the stability and balance of the exoskeleton can be maintained. The pneumatic valve group adjusts the output force of the support rod of the adjustable support rod module according to the calculation result, and the output force range can be 200 - 800N. The wide-range force adjustment ability enables the exoskeleton to not only handle fine operations under light loads but also support stable climbing under heavy loads. Precise pneumatic pressure adjustment ensures that the output force of the support rod is stable and controllable, avoiding human body imbalance caused by sudden force changes, and further enhancing the operation safety and comfort.

[0056] In one example, the IMU sensor collects the attitude data of the operator during the tower climbing process in real time. For example, it collects basic data such as the acceleration and angular velocity of the human body. Further processing and analysis can obtain key attitude information (attitude data) such as the human body tilt angle and movement trend. The IMU sensor transmits the collected attitude data to the fuzzy logic controller. The fuzzy logic controller first performs fuzzy processing on the accurate attitude data, divides information such as the human body tilt angle and movement trend into different fuzzy sets. For example, the tilt angle is divided into fuzzy concepts such as small-angle tilt, medium-angle tilt, and large-angle tilt, and the movement trend is divided into fuzzy categories such as stationary, slow movement, and fast movement. Based on the preset fuzzy rule base, the fuzzy logic controller matches and infers the fuzzified data. Here, the rule base includes the corresponding relationship between various attitude situations and the optimal support force distribution ratio. For example, if it is detected that the human body is in a large-angle tilt and fast movement posture, the corresponding support force distribution ratio range can be inferred according to the rule base. The inference result is defuzzified through a non-linear algorithm, converting the fuzzy inference result into an accurate optimal support force distribution ratio value to ensure that the output force distribution strategy can accurately match the load demand in the current posture. The fuzzy logic controller sends the calculated optimal support force distribution ratio result to the pneumatic valve group. The pneumatic valve group precisely adjusts the air pressure of the adjustable support rod sub-module according to the received force distribution ratio instruction. By changing the air pressure, it controls the output force of the support rod to dynamically adjust it within the range of 200 - 800N. The adjustable support rod sub-module outputs the corresponding support force according to the adjustment of the pneumatic valve group. Throughout the process, the IMU sensor continuously monitors the change of the human body posture in real time and feeds back the latest attitude data to the fuzzy logic controller. The fuzzy logic controller continuously repeats the above data processing, analysis, and adjustment process according to the real-time feedback data to dynamically optimize the support force configuration in real time to adapt to the rapidly changing working conditions during tower climbing. Even under extreme conditions such as strong winds and sudden terrain changes, it can maintain the stable balance of the exoskeleton.

[0057] In one embodiment, the sensing sub-module includes a plantar pressure sensor, an inertial measurement unit, and a joint angle encoder, and is used to collect gait phase, joint movement angle, and terrain inclination data, and obtain the exoskeleton operation state information according to the gait phase, joint movement angle, and terrain inclination data; The decision-making sub-module includes an embedded processor, a fuzzy logic algorithm library, and a security policy database, and is used to predict the climbing intention based on the exoskeleton operation state information, calculate the target torque of each joint and the output force value of the support rod of the adjustable support rod sub-module.

[0058] Specifically, as Figure 10 shown, the sensing sub-module of the multi-modal control module (such as Figure 10The perception module (as shown) includes a plantar pressure sensor, an IMU, and a joint angle encoder. The perception sub-module can collect gait phase, joint movement angle, and terrain inclination data. For example, the data sampling frequency is greater than or equal to 100 Hz, and the delay is less than 10 ms.

[0059] Exemplarily, to achieve precise and intelligent control of the exoskeleton robot during tower climbing operations, improve the human-machine collaboration efficiency and operation safety, and ensure the stable operation of the system in complex environments. Exemplarily, in this embodiment, the perception sub-module of the multi-modal control module includes a plantar pressure sensor, an IMU, and a joint angle encoder. In this embodiment, a comprehensive environment and human motion perception system is constructed through multi-sensor fusion design. Compared with the traditional single-sensor data acquisition method, this embodiment can obtain the exoskeleton operation state information more accurately and comprehensively; the plantar pressure sensor, IMU, and joint angle encoder each perform their own functions and complement each other, greatly improving the accuracy and reliability of data acquisition. The perception sub-module collects gait phase, joint movement angle, and terrain inclination data. The data sampling frequency ≥ 100 Hz, and the delay < 10 ms. The ultra-high data sampling frequency and extremely low delay ensure that the system can capture the subtle movement changes of the operator and environmental dynamics in real time, providing timely and accurate data support for subsequent decisions; even in the case of rapid climbing or sudden movements, zero-delay response can be achieved to ensure the smoothness of human-machine collaboration.

[0060] Specifically, as Figure 11 shown, the decision-making sub-module of the multi-modal control module (such as the decision-making module shown in Figure 11 ) includes an embedded processor, a fuzzy logic algorithm library, and a security policy database. The decision-making sub-module predicts the user's climbing intention based on the data collected by the perception sub-module, and calculates the target torque of each joint and the output force value of the support rod. Among them, the range of the target torque of each joint can be 0-50 Nm.

[0061] Exemplarily, the decision-making sub-module of the multi-modal control module includes an embedded processor, a fuzzy logic algorithm library, and a security policy database. The combination of the embedded processor and the fuzzy logic algorithm library endows the system with powerful real-time decision-making capabilities. Compared with traditional preset rule-based control systems, this embodiment can quickly process complex and variable perception data to achieve intelligent decision-making. The introduction of the security policy database provides multiple security guarantee mechanisms for the system operation. The decision-making sub-module predicts the user's climbing intention based on the data collected by the perception sub-module, and calculates the target torque of each joint and the output force value of the support rod. The range of the target torque of each joint is 0-50 Nm. Through the advanced fuzzy logic algorithm, the system can accurately predict the climbing intention of the operator, such as actions like crossing, turning, and sudden stop, and plan in advance the assisting torque of each joint and the supporting force of the support rod to achieve seamless connection of human-machine actions. The torque adjustment range of 0-50 Nm can be set, which can not only meet the requirements of fine operation but also provide sufficient assistance to cope with high-intensity climbing operations.

[0062] In one example, the perception sub-module obtains various types of data related to climbing through multiple sensors, including but not limited to the posture information of the human body (such as tilt angle, joint angle, etc.), motion information (such as speed, acceleration), and external environment information (such as wind force, terrain, etc.), and transmits the collected raw data to the embedded processor of the decision sub-module; the embedded processor first pre-processes the data, including but not limited to operations such as data filtering, calibration, and normalization; the embedded processor calls the algorithms in the fuzzy logic algorithm library to analyze the pre-processed data. Here, the fuzzy logic algorithm can process data with uncertainty and ambiguity, map the collected multi-dimensional data to different fuzzy sets, and based on the fuzzy rules preset in the fuzzy logic algorithm library, match and reason about the mapped fuzzy data. These rules describe the corresponding relationship between different data feature combinations and climbing intentions. For example, if it is detected that the human body is in a state of fast movement and large-angle tilt, according to the rules, it can be inferred that the possible climbing intention is a crossing action; through comprehensive analysis and judgment of the fuzzy inference results, determine the current climbing intention of the operator, such as crossing, turning, sudden stop, etc.; after determining the climbing intention, the embedded processor refers to the information in the safety policy database. Here, the safety policy database includes safety constraint conditions and recommended parameters for different climbing intentions and working conditions, such as the maximum allowable torque, reasonable support force range, etc.; according to the predicted climbing intention and the information in the safety policy database, use the fuzzy logic algorithm to calculate the target torque of each joint and the output force value of the support rod. The fuzzy logic algorithm comprehensively considers various factors according to the current specific situation and calculates the optimal value that meets the climbing requirements and conforms to the safety requirements. For example, for a crossing action, calculate the assist torque that each joint needs to provide and the support force that the support rod needs to output to ensure that the operator can complete the action smoothly; ensure that the calculated target torque of each joint is within the range of 0 - 50 Nm, and the output force value of the support rod is also within a reasonable safety range. If the calculation result exceeds the preset range, the embedded processor will make adjustments according to the safety policy to ensure the safety and reliability of the system.

[0063] In one embodiment, the execution sub-module includes a motor driver, a pneumatic valve controller, and an electromagnetic release controller; where the motor driver is used to output a PWM signal to control the motor speed and steering according to the target torque of each joint and the output force value of the support rod; the pneumatic valve controller is used to adjust the opening of the pneumatic valve according to the target torque of each joint and the output force value of the support rod; the electromagnetic release controller is used to output an instruction to the elastic energy storage sub-module according to the target torque of each joint and the output force value of the support rod to control the energy release timing of the electromagnetic release of the elastic energy storage sub-module.

[0064] Specifically, as Figure 12 shown, the execution sub-module of the multi-modal control module (such as the Figure 12 execution module shown) includes a motor driver, a pneumatic valve controller, and an electromagnetic release. The motor driver outputs a PWM signal to control the rotation speed and direction of the motor. The pneumatic valve controller adjusts the opening degree of the pneumatic valve. The electromagnetic release controls the release timing of the energy storage unit of the elastic energy storage module.

[0065] Exemplarily, the execution sub-module of the multi-modal control module includes a motor driver, a pneumatic valve controller, and an electromagnetic release. The modular execution structure design realizes precise control of different power sources. The motor driver, pneumatic valve controller, and electromagnetic release controller have clear division of labor and work together to ensure that every action of the exoskeleton can be precisely executed. The motor driver outputs a PWM signal to control the rotation speed and direction of the motor. The pneumatic valve controller adjusts the opening degree of the pneumatic valve. The electromagnetic release controller controls the release timing of the energy storage unit of the elastic energy storage sub-module. In this embodiment, the rotation speed and direction of the motor are precisely controlled by the PWM signal, making the joint movement smoother and more flexible. The pneumatic valve controller adjusts the opening degree of the pneumatic valve in real time to ensure the stable operation of the dynamic load balancing system. The electromagnetic release controller precisely controls the energy release timing of the elastic energy storage sub-module, efficiently converting the stored energy into joint assistance, and further improving the energy efficiency and operation efficiency of the system.

[0066] In one example, the embedded processor converts the calculated target torque of each joint and the output force value of the support rod into control instructions and sends them to the corresponding actuators, such as the joint drive motor and the pneumatic pressure regulating device of the support rod. During the execution process, the sensing sub-module continuously collects data and feeds it back to the decision-making sub-module. The decision-making sub-module adjusts the control instructions in real time according to the real-time feedback data to ensure seamless connection of human-machine actions and adapt to various changes that may occur during the climbing process.

[0067] It should be noted that the working principle of the robot system in this embodiment will be described in combination with specific examples: When the operator wears the exoskeleton robot and starts climbing operations, the perception sub-module starts working first. The plantar pressure sensor, IMU, and joint angle encoder start to collect data in real time, including perception data such as gait phase, joint movement angle, and terrain inclination. These perception data can be transmitted to the decision-making sub-module at a sampling frequency of ≥100Hz and a low latency of <10ms. The embedded processor in the decision-making sub-module combines the fuzzy logic algorithm library to analyze the perception data, predict the climbing intention of the operator, such as judging whether to perform actions such as crossing the crossarm, turning around, or continuing to climb vertically, and calculate the target torque required for each joint (for example, 0-50 Nm) and the output force value of the support rod in the dynamic load balancing module. After the calculation is completed, the decision-making sub-module sends the instruction to the execution sub-module. The motor driver outputs a PWM signal according to the instruction to control the motor speed and steering, driving the joints of the bionic joint drive system to move; the pneumatic valve controller adjusts the opening of the pneumatic valve to control the operation of the adjustable support rod sub-module in the dynamic load balancing module and the relevant pneumatic components in the distributed power transmission module; the electromagnetic release accurately controls the release timing of the energy storage unit of the elastic energy storage sub-module according to the instruction to assist joint movement. In the whole process, each subsystem forms a physical-control closed-loop through mechanical interfaces and electrical signals to achieve real-time feedback and coordination, ensuring that the exoskeleton robot accurately and stably assists the operator to complete the tower climbing operation.

[0068] Exemplarily, the hip joint drive sub-module, according to the instruction of the decision-making sub-module, uses a four-bar mechanism and a unique double-degree-of-freedom design to achieve flexion / extension and adduction / abduction actions, meeting the complex posture requirements during climbing; the knee joint assistance sub-module stores energy through a spring-ratchet energy storage unit during the pedaling stage and releases potential energy to assist hip flexion during the leg-lifting stage; the passive shock absorber and damping regulator of the ankle joint stability sub-module automatically adjust according to the terrain to maintain operation stability, and at the same time, the plantar pressure sensor feeds back the data to the perception sub-module.

[0069] Exemplarily, the double-output shaft motor of the waist drive sub-module efficiently transmits power to the hip joint drive sub-module through a carbon fiber transmission connecting rod; the variable stiffness helical spring of the elastic energy storage sub-module stores energy according to the human pedaling force, and the electromagnetic release releases energy at the appropriate time to assist joint movement.

[0070] Exemplarily, the adjustable support rod sub-module extends during vertical climbing, transferring 30%-50% of the operator's body weight to the tower bracket, and contracts during lateral movement to avoid interference; the force distribution calculation sub-module, based on the IMU sensor data, adjusts the output force of the support rod (for example, 200-800 N) in real time through a fuzzy logic controller and a pneumatic valve group to achieve intelligent load distribution.

[0071] Exemplarily, the perception sub-module continuously collects data, the decision-making sub-module continuously analyzes and predicts and issues instructions, the execution sub-module precisely controls the actions of each component, and at the same time, the security policy database ensures the safe operation of the system.

[0072] It can be understood that the lightweight lower limb exoskeleton robot system provided in this embodiment for tower climbing operations has the following beneficial effects: adopting an asymmetric structure with two degrees of freedom for the hip joint and one degree of freedom for the knee joint, combined with four-bar linkage transmission and waist centralized drive, not only strengthens the lateral stability to adapt to complex climbing movements, but also amplifies the torque through the lever ratio and reduces the motor power requirement, realizing efficient power transmission and improved motion flexibility; at the same time, the spring-ratchet energy storage unit of the knee joint effectively recovers and utilizes the pedaling kinetic energy, significantly reducing energy consumption. The dynamic load balancing module uses adjustable support rods and a force distribution mechanism to dynamically adjust the support force according to real-time attitude data, solving the adaptability problem of traditional fixed support structures; the multi-modal control module fuses multi-sensor data and uses fuzzy logic algorithms to accurately predict climbing intentions, realizing dynamic adjustment of joint torques and support forces. In addition, safety redundancy designs such as dual-loop pneumatic drive and mechanical self-locking further ensure operation safety, making the exoskeleton robot system in this embodiment significantly superior to the prior art in terms of function integration, safety, and operation adaptability. Through the modular design and collaborative operation of each module in the robot system, efficient assistance for tower climbing operations is achieved, improving the flexibility and safety of operators, reducing energy consumption, and enhancing the environmental adaptability of the system.

[0073] It should be understood that the above is only for illustration and does not constitute any limitation to the technical solution of the present invention. In specific applications, those skilled in the art can set according to needs, and the present invention does not make any restrictions on this.

[0074] It should be noted that the above-described work process is only illustrative and does not limit the protection scope of the present invention. In actual applications, those skilled in the art can select some or all of them according to actual needs to achieve the purpose of the solution of this embodiment, and no restrictions are made here.

[0075] In addition, it should be noted that in this article, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of another identical element in the process, method, article or system including that element.

[0076] The serial numbers of the embodiments of the present invention above are only for description and do not represent the superiority or inferiority of the embodiments.

[0077] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as Read Only Memory (ROM) / RAM, magnetic disk, optical disk), and includes several instructions to enable a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0078] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied to other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A lightweight lower limb exoskeleton robot system for tower climbing operations, characterized in that, Comprising: A bionic joint drive module, including a two-degree-of-freedom hip joint drive sub-module, a single-degree-of-freedom knee joint assist sub-module, and an ankle joint stabilization sub-module, which is used to adopt an asymmetric structure of two degrees of freedom for the hip joint and one degree of freedom for the knee joint, cooperate with a four-bar linkage transmission and a waist centralized drive, and automatically adjust the damping by the ankle joint stabilization sub-module to suppress vibration; A distributed power transmission module, including a waist drive motor sub-module and an elastic energy storage sub-module, which is used to transmit power to the hip joint and dynamically adjust the energy storage characteristics according to the pedaling force; A dynamic load balancing module, including an adjustable support rod sub-module and a force distribution calculation sub-module, which is used to dynamically adjust the support force based on real-time attitude data; A multi-modal control module, including a sensing sub-module, a decision-making sub-module, and an execution sub-module, which is used to fuse and analyze multi-source sensor data to predict the climbing intention and control the power output.

2. The system according to claim 1, wherein The bionic joint drive module, the distributed power transmission module, the dynamic load balancing module, and the multi-modal control module are connected through mechanical interfaces and electrical signals to form a physical control closed loop to achieve real-time feedback and coordination among the modules.

3. The system according to claim 1, characterized in that, The two-degree-of-freedom hip joint drive sub-module includes a four-bar linkage mechanism, a flexion-extension unit, and an abduction-adduction unit; wherein, The flexion-extension unit is used to achieve flexion-extension movement, and the abduction-adduction unit is used to achieve abduction-adduction movement; the length ratio of the active link to the driven link of the four-bar linkage mechanism is 1:3, and the abduction-adduction unit adopts an arc-shaped guide rail and a ball bearing structure to achieve a preset angle of lateral deflection.

4. The system according to claim 3, wherein The single-degree-of-freedom knee joint assist sub-module includes a spring-ratchet energy storage unit and a pressure trigger; wherein, The spring-ratchet energy storage unit cooperates with the pressure trigger to obtain the kinetic energy generated during pedaling and convert the kinetic energy into potential energy to achieve the combination of energy recovery and auxiliary drive.

5. The system according to claim 3, characterized in that, The ankle joint stabilization sub-module includes a passive shock absorber, a damping regulating valve, and a plantar pressure sensor array; wherein, The passive shock absorber is used to absorb the impact force of the tower structure during climbing; the damping regulating valve is used to automatically adjust the damping coefficient according to the terrain inclination, and the plantar pressure sensor array is used to feedback the sensor data to the sensing sub-module of the multi-modal control module in real time. The damping regulating valve and the plantar pressure sensor array cooperate with each other to form a dynamic response mechanism.

6. The system according to claim 1, wherein The waist drive motor sub-module includes a double-output shaft motor, a carbon fiber transmission connecting rod, and a quick-release interface; wherein, The double-output shaft motor is used to drive both hip joints simultaneously to achieve the consistency and stability of power output; the carbon fiber transmission connecting rod is used to transmit power to the hip joint, and the power output by the double-output shaft motor is transmitted to the two-degree-of-freedom hip joint drive sub-module through the carbon fiber transmission connecting rod, and the lower limb and the waist drive motor sub-module are quickly separated through the quick-release interface.

7. The system according to claim 6, wherein The elastic energy storage sub-module includes a variable stiffness helical spring, a ratchet set, and an electromagnetic release; wherein, the variable stiffness helical spring and the ratchet set are used to adaptively store energy according to different pedaling forces; the electromagnetic release is used to receive instructions from the decision-making sub-module of the multi-modal control module and control the energy release according to the instructions.

8. The system according to claim 1, characterized in that, The adjustable support rod sub-module includes a pneumatic telescopic rod, a force sensor, and a micro air pump; the force sensor is used to monitor the load pressure in real time, and cooperate with the micro air pump to control the telescopic of the pneumatic telescopic rod based on the load pressure, forming a closed-loop feedback regulation mechanism; The force distribution calculation sub-module includes an IMU sensor, a fuzzy logic controller, and a pneumatic valve group; the IMU sensor is used to collect attitude data, the fuzzy logic controller is used to calculate the optimal support force distribution ratio based on the collected attitude data, and control the pneumatic valve group to adjust the output force of the support rod of the adjustable support rod sub-module according to the optimal support force distribution ratio.

9. The system according to claim 1, characterized in that The perception sub-module includes a plantar pressure sensor, an inertial measurement unit, and a joint angle encoder, which are used to collect gait phase, joint movement angle, and terrain inclination data, and obtain the exoskeleton operating state information according to the gait phase, joint movement angle, and terrain inclination data; The decision-making sub-module includes an embedded processor, a fuzzy logic algorithm library, and a security policy database, which are used to predict the climbing intention based on the exoskeleton operating state information, and calculate the target torque of each joint and the output force value of the support rod of the adjustable support rod sub-module.

10. The system according to claim 9, wherein, The execution sub-module includes a motor driver, a pneumatic valve controller, and an electromagnetic release controller; wherein, The motor driver is used to output a PWM signal to control the motor speed and steering according to the target torque of each joint and the output force value of the support rod; The pneumatic valve controller is used to adjust the opening of the pneumatic valve according to the target torque of each joint and the output force value of the support rod; The electromagnetic release controller is used to output instructions to the elastic energy storage sub-module according to the target torque of each joint and the output force value of the support rod, so as to control the energy release timing of the electromagnetic release of the elastic energy storage sub-module.

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