Control method and device of autonomous navigation lower limb robot, terminal and medium

Abstract

The invention discloses a control method of an autonomous navigation lower limb robot, which comprises the following steps: acquiring human gait data to obtain an original gait curve, optimizing gaits in combination with sensor data, and controlling exoskeleton to perform rehabilitation training; on the basis of the lower limb motion parameters and the navigation instruction, the speed of the driving wheels is controlled, so that the platform moves forwards in the target direction in cooperation with the lower limb motion parameters, and the functions of gait training and autonomous navigation are achieved to improve the comfort during lower limb rehabilitation training and the experience feeling of a patient; real-time regulation and control of lower limb movement and autonomous control of the walking direction of the patient during training are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of rehabilitation training devices, and in particular relates to a control method, device, terminal and medium for an autonomous navigation lower limb robot. Background Art

[0003] In the prior art, there are a variety of lower limb exoskeleton lower limb robots designed to help patients with rehabilitation training, most of which are dedicated to training patients' ability to walk upright. On the one hand, the existing lower limb rehabilitation lower limb robots provide walking assistance to patients through the lower limb exoskeleton, and on the other hand, the lower limb exoskeleton adjusts the patient's gait when walking, so that the patient can walk on the ground with the correct gait.

[0004] At present, lower limb rehabilitation robots are roughly divided into fixed gait training lower limb rehabilitation robots and power-assisted walking lower limb rehabilitation robots. Fixed gait rehabilitation training lower limb robots mainly drive patients to perform standard gait training in a fixed position through lower limb exoskeleton, such as a control method of gait rehabilitation training lower limb robot disclosed in CN103536424A. Power-assisted walking lower limb rehabilitation lower limb robots provide assistance for patients to walk, combined with a predetermined standard gait, so as to drive patients to perform walking training on the ground according to the standard gait, which can improve the patient's experience during training. At present, most of the power-assisted walking lower limb rehabilitation lower limb robots can only drive patients to perform straight walking training, and cannot meet the needs of patients to actively control the direction of travel. For example, CN105456004A discloses an exoskeleton mobile walking rehabilitation training device and method. The technical solution drives the lower limbs of the human body to perform walking rehabilitation training in a mobile platform through an exoskeleton mechanical leg, and the platform can be moved by wheels. However, the platform needs to be fixed during training, and can only perform gait training in situ. During training, the platform cannot move and turn with gait. Summary of the invention

[0005] In order to solve at least one of the problems existing in the prior art, the present invention provides a control method for an autonomous navigation lower limb robot. The present invention collects human gait data to obtain the original gait curve, optimizes the gait in combination with sensor data, and controls the exoskeleton to perform rehabilitation training; based on the lower limb motion parameters and navigation instructions, the speed of the driving wheel is controlled so that the platform moves in the target direction in accordance with the lower limb motion parameters, thereby realizing the functions of gait training and autonomous navigation. The present invention allows patients to perform lower limb rehabilitation training and autonomously control the walking direction during training, which can improve the comfort of patients during training, and at the same time has the function of protecting the patient's limbs, providing a new technical direction for the design of lower limb rehabilitation training exoskeleton lower limb robots.

[0006] To achieve the purpose of the present invention, a control method of an autonomous navigation lower limb robot of the present invention comprises the following steps:

[0007] Use the lower limb robot to guide the patient to perform gait training according to the standard movement gait;

[0008] Perform safety state detection in the order of priority of obstacle monitoring feedback, sole pressure sensor feedback, and sole height feedback, and adjust the motion state of the lower limb robot according to the feedback of the safety state detection;

[0009] After ensuring through a safety status detection that the patient has not encountered any obstacles and is in a ground contact state, the movement of the lower limb robot is controlled by controlling the driving wheels of the lower limb robot to rotate;

[0010] The lower limb robot obtains the motion parameters of the patient's lower limbs, calculates the patient's foot horizontal speed, and controls the speed of the driving wheel of the lower limb robot based on the patient's foot horizontal speed, so that the speed of the driving wheel is consistent with the patient's foot horizontal speed, so that the patient can perform straight walking training;

[0011] According to the turning radius r and the horizontal speed of the patient's sole, the angular velocity of the lower limb robot and the speed of the driving wheels on both sides are calculated, and the turning of the lower limb robot is controlled by the speed difference of the driving wheels on both sides, so that the patient can realize turning during the straight walking training process;

[0012] The target heading angle of the lower limb robot is calculated by the turning radius and the horizontal speed of the sole, and the actual heading angle of the lower limb robot is corrected according to the target heading angle.

[0013] Furthermore, the method for acquiring the standard movement gait includes the following steps:

[0014] Collect normal people's gait images, extract gait information, and obtain gait motion parameter database;

[0015] A gait model is established based on the gait motion parameter database, and a standard motion gait is obtained based on the gait model.

[0016] Further, the safety state detection is performed in the order of priority of obstacle monitoring feedback, sole pressure sensor feedback, and sole height feedback, and the motion state of the lower limb robot is adjusted according to the feedback of the safety state detection, including:

[0017] Obstacle monitoring feedback is performed to monitor the external torque applied to each joint of the lower limb robot in real time. When the external torque applied to any joint of the lower limb robot exceeds a preset torque threshold, it is determined that an obstacle has been encountered, and the lower limb robot is controlled to stop moving.

[0018] When the external torque applied to the joints of the lower limb robot does not exceed a preset torque threshold, the plantar pressure of the patient is monitored in real time, and when the plantar pressure exceeds a preset pressure value, the lower limb robot is controlled to make the plantar pressure lower than the preset pressure value;

[0019] When the sole pressure does not exceed the preset pressure value, the sole height feedback is used to ensure that the patient's sole is in contact with the ground.

[0020] Furthermore, when the patient performs the gait optimization training, the obstacle monitoring feedback has a higher priority than the ground clearance height feedback, and the ground clearance height feedback has a higher priority than the plantar pressure sensor feedback.

[0021] Furthermore, before the lower limb robot drives the patient's lower limbs to perform gait optimization training according to the standard movement gait, it also includes ensuring that the sole of the lower limb robot is in a ground contact state.

[0022] Furthermore, the height of the sole of the foot off the ground is fed back to ensure that the sole of the patient is in a state of contact with the ground. The calculation formula of the height of the sole of the foot off the ground is:

[0023] h=Hxd

[0024] x=L1cos·(θ1)+L2cos·(θ1+θ2)

[0025] Wherein, h is the height of the sole from the ground, H is the distance from the hip joint of the lower limb robot to the ground, d is the distance from the ankle joint of the lower limb robot to the sole plane, x is the height difference between the hip joint and the ankle joint, L1 is the thigh length of the lower limb robot, L2 is the calf length of the lower limb robot, θ1 is the angle between the thigh of the lower limb robot and the vertical line, θ2 is the angle between the thigh and the calf of the lower limb robot;

[0026] When the height of the sole of the foot from the ground is less than zero, θ1 and θ2 are adjusted to ensure that the height of the sole of the foot remains zero.

[0027] Furthermore, the plantar pressure sensor feedback is used to ensure that the patient's foot is in a ground contact state. Specifically, the plantar pressure of the patient is monitored in real time by the pressure sensor. When the plantar pressure exceeds the preset pressure value, the lower limb robot is controlled to make the plantar pressure lower than the preset pressure value.

[0028] Furthermore, the calculation formula of the horizontal speed of the sole is:

[0029]

[0030] In the formula, v f is the horizontal velocity of the foot, v ankleis the horizontal speed of the ankle joint, L1 is the thigh length of the lower limb robot, L2 is the calf length of the lower limb robot, θ1 is the angle between the thigh of the lower limb robot and the vertical line, θ2 is the angle between the thigh and the calf of the lower limb robot, are the first-order derivatives of θ1 and θ2 respectively.

[0031] Furthermore, the patient can perform straight walking training by the following formula: v = -v f , v l =v r =v, where v in the above formula is the moving speed of the lower limb robot, v f v is the horizontal velocity of the sole of the foot, the velocity is positive when it is forward and negative when it is backward. l is the left driving wheel speed, v r is the right driving wheel speed;

[0032] Furthermore, the calculation formula for the angular velocity of the lower limb robot turning and the speed of the left and right driving wheels is:

[0033]

[0034]

[0035] In the formula, ω is the angular velocity, d is the distance between the two feet of the lower limb robot, D is the distance between the two driving wheels of the lower limb robot, r is the turning radius, and sign l is the direction variable related to the lower limb robot’s ground contact foot, v l is the speed of the left driving wheel, v r is the speed of the right driving wheel. When the contact foot is on the same side as the turning direction, the variable sign l When the foot touching the ground and the turning direction are on opposite sides, the variable sign l is 1, sign m This is the direction variable associated with the driving wheel. This variable is -1 when turning left and 1 when turning right.

[0036] Furthermore, the calculation formula of the target heading angle is:

[0037]

[0038] In the formula, is the target heading angle, is the heading angle at the beginning of walking, ω(t) is a function of the angular velocity, describing the angular velocity changing with time t;

[0039] The method of correcting the actual heading angle of the lower limb robot by using the target heading angle is as follows:

[0040]

[0041] In the formula, v l is the left driving wheel speed before correction, v r is the right driving wheel speed before correction, v l ' is the corrected left driving wheel speed, v r ′ is the corrected right driving wheel speed, is the current heading angle, is the error correction function, which is used to calculate the driving wheel speed increment.

[0042] Furthermore, the external torque exerted on the lower limb robot is monitored in real time by the joint torque pressure sensor of the lower limb robot, and the external torque exerted on the lower limb robot is calculated by the following formula:

[0043] T=T r -T0

[0044] T0 is the torque generated by the joint’s own weight, T r To monitor the torque in real time, T is the external torque. When the external torque exceeds the threshold of the preset torque, it is determined that an obstacle is encountered and the lower limb robot is controlled to stop moving.

[0045] The present invention provides a control device for an autonomous navigation lower limb robot, comprising:

[0046] In the training module, the lower limb robot drives the patient to start training in situ according to the standard movement gait;

[0047] A motion state adjustment module is used to perform safety state detection in the order of priority of obstacle monitoring feedback, sole pressure sensor feedback, and sole height feedback, and adjust the motion state of the lower limb robot according to the feedback of the safety state detection;

[0048] A travel control module, used to control the travel of the lower limb robot by controlling the rotation of the driving wheels of the lower limb robot after ensuring that the patient has not encountered any obstacles and is in a ground contact state through a safety state detection;

[0049] A straight walking training control module is used to obtain the motion parameters of the patient's lower limbs through the lower limb robot, calculate the horizontal speed of the patient's soles, and control the speed of the driving wheel of the lower limb robot based on the horizontal speed of the patient's soles to make it consistent with the horizontal speed of the patient's soles, so that the patient can perform straight walking training;

[0050] A turning control module is used to calculate the angular velocity of the lower limb robot and the speeds of the left and right driving wheels according to the turning radius r and the horizontal speed of the patient's sole, and control the turning of the lower limb robot through the speed difference of the left and right driving wheels, so that the patient can turn during the straight walking training;

[0051] The actual heading angle correction module is used to calculate the target heading angle of the lower limb robot through the turning radius and the horizontal speed of the sole, and to correct the actual heading angle of the lower limb robot according to the target heading angle.

[0052] The invention also provides a terminal device.

[0053] The present invention also provides a computer-readable storage medium.

[0054] Compared with the prior art, the present invention can at least achieve the following beneficial effects:

[0055] The present invention integrates multiple sensors to detect state parameters in real time, and can optimize the gait according to the patient's lower limb movement state and stress state during training, thereby improving the comfort of lower limb training. According to the patient's consciousness and state parameters (the patient's consciousness is the turning command and turning radius issued by the patient, and the state parameter is the movement state of the lower limb exoskeleton, including the foot speed, whether it encounters obstacles, and whether it touches the ground), the walking direction is actively controlled to bypass obstacles and reach the target point autonomously during indoor and outdoor training, which increases the sense of participation and self-confidence, reduces the workload of the therapist, and provides a new technical direction for the design of lower limb rehabilitation training exoskeleton lower limb robots. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a structural diagram of an autonomous navigation lower limb robot provided in an embodiment of the present invention.

[0057] Figure 2 A control diagram of a control method for an autonomous navigation lower limb robot provided in an embodiment of the present invention.

[0058] Figure 3 A flowchart of the steps of a control method for an autonomous navigation lower limb robot provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0060] The core of the present invention is to provide a control method for an autonomous navigation lower limb robot. When the sole of the lower limb exoskeleton touches the ground for lower limb walking training, the movement and stopping, movement speed and movement direction of the lower limb robot are controlled based on the lower limb motion parameters of the exoskeleton lower limb robot to ensure that the sole of the exoskeleton and the ground remain relatively still when the lower limb robot moves, thereby achieving a state in which the body movement is consistent with the lower limb movement during walking.

[0061] For ease of understanding, the structure of the lower limb robot is introduced here. Figure 1 , Figure 1 This is a structural diagram of an autonomous navigation lower limb robot provided in an embodiment of the present invention.

[0062] An autonomous navigation lower limb robot, comprising:

[0063] The left hip joint structure 1 comprises a motor and a torque sensor, wherein the motor is used to control the rotation of the left thigh structure 1.1, and the torque sensor is used to measure the output torque of the motor.

[0064] The left knee joint structure 2 comprises a motor and a torque sensor. The motor is used to control the rotation of the left calf structure 2.1, and the torque sensor is used to measure the output torque of the motor.

[0065] The right hip joint structure 4, the left hip joint structure 4 comprises a motor and a torque sensor, the motor is used to control the rotation of the right thigh structure 4.1, and the torque sensor is used to measure the output torque of the motor.

[0066] The right knee joint structure 5, the left knee joint structure 5 comprises a motor and a torque sensor, the motor is used to control the rotation of the right calf structure 5.1, and the torque sensor is used to measure the output torque of the motor.

[0067] The left driving wheel 3 and the right driving wheel 6 are installed at the left front and right front of the frame of the lower limb robot. The left driving wheel 3 and the right driving wheel 6 are used to realize the movement of the lower limb robot. The rotation direction and rotation speed of the left driving wheel 3 are adjustable, and the rotation direction and rotation speed of the right driving wheel 6 are adjustable.

[0068] By adjusting the speed of the left driving wheel 3 and the right driving wheel 6, the forward speed and forward direction of the lower limb robot are controlled.

[0069] The left plantar structure 7 is provided with a plantar pressure sensor, and the plantar pressure sensor is used to detect the plantar pressure of the left plantar structure 7 and to detect whether the left plantar structure 7 touches the ground.

[0070] The right plantar structure 8 is provided with a plantar pressure sensor, and the plantar pressure sensor is used to detect the plantar pressure of the right plantar structure 8 and to detect whether the right plantar structure 8 touches the ground.

[0071] The rear universal wheels 9 are used to rotate freely following the movement of the lower limb robot. There are two rear universal wheels 9, which are installed at the left rear and right rear of the frame of the lower limb robot.

[0072] The lower limb robot is also provided with an electronic compass, through which the orientation direction of the lower limb robot is measured.

[0073] Joint torque, wherein the joint torque includes the joint motor output torque of the hip joint and the knee joint of the lower limb robot.

[0074] Joint angles, the joint angles include an angle θ1 between the thigh and the vertical line and an angle θ2 between the thigh and the calf of the lower limb robot.

[0075] The height of the lower limb robot is the vertical distance between the hip joint of the lower limb robot and the ground.

[0076] The length of the calf and thigh, wherein the length of the calf and thigh includes the thigh length L1 and the calf length L2.

[0077] The terminal plantar position is the height of the plantar from the ground;

[0078] Joint angular velocity, the joint angular velocity includes the rotation angular velocity of the hip joint motor and the rotation angular velocity of the knee joint motor of the lower limb robot.

[0079] The direction of travel instruction is a direction instruction input by the patient through an input device, including a turning direction and a turning radius. When the direction instruction is to go straight, v l =v r =v.

[0080] The travel control is achieved by controlling the speed of the left and right wheels and performing the direction feedback in the step.

[0081] See also Figure 2 and Figure 3 The present invention provides a control method for an autonomous navigation lower limb robot, which mainly includes two parts: gait control and travel control. The control method includes the following steps:

[0082] Step 1: Collect normal human gait images, extract effective gait information, and obtain a gait motion parameter database; based on the gait motion parameter database, establish a gait model, and obtain a standard motion gait based on the gait model. The lower limb robot can drive the patient to start training on the spot according to the standard motion gait.

[0083] In one embodiment of the present invention, this step specifically includes the following sub-steps:

[0084] Step 101: collecting walking gait videos of multiple persons through a camera, and extracting effective gait information from the walking gait videos, wherein the gait information includes a timestamp, a hip joint angle, and a knee joint angle;

[0085] Step 102: Establishing a gait motion parameter database through the gait information;

[0086] The gait motion parameter database includes multiple time points and the knee joint angle and hip joint angle corresponding to each time point.

[0087] Step 103: Obtain a gait model by Fourier transforming the knee joint angle and hip joint angle data in the gait motion parameter database, wherein the gait model is a function of the joint angle with respect to time;

[0088] In this sub-step, the gait model can be used to calculate the angles of the hip joint and the knee joint at any time.

[0089] Step 104: inputting a time parameter into the gait model, and obtaining a standard motion gait after calculation by the gait model, wherein the parameters of the standard motion gait are a hip joint angle and a knee joint angle;

[0090] Step 105: The lower limb robot drives the patient to perform training according to the obtained standard gait.

[0091] It is understandable that in other embodiments, the existing disclosed standard movement gait may also be directly adopted.

[0092] Step 2: Perform safety status detection in the order of priority of obstacle monitoring feedback, plantar pressure sensor feedback, and plantar height feedback, and adjust the motion state of the lower limb robot based on the feedback of the safety status detection.

[0093] To protect the safety of patients, the priority of safety status detection is obstacle monitoring feedback, sole height feedback, sole pressure sensor feedback, and sole height feedback. Among them:

[0094] Safety status detection 1: Obstacle monitoring is performed to determine whether the lower limb exoskeleton lower limb robot encounters external resistance during movement. When the external torque applied to any joint of the lower limb robot exceeds the preset torque threshold, it is determined that an obstacle is encountered, and the lower limb robot is controlled to stop moving, and the plantar pressure and the height of the plantar from the ground are no longer detected.

[0095] Safety state detection 2: Perform safety state detection based on the feedback of the plantar pressure sensor to ensure that the patient's sole is in the ground contact state. Specifically, the plantar pressure of the patient is monitored in real time by the plantar pressure sensor. When the plantar pressure exceeds the preset pressure value, the lower limb robot is controlled to make the plantar pressure lower than the preset pressure value. When it is monitored that the external torque on any joint of the lower limb robot is less than the preset torque threshold, but the plantar pressure is greater than the preset pressure value, the height of the sole from the ground is no longer detected.

[0096] Safety status detection 3: Perform safety status detection based on the feedback of the height of the sole of the foot off the ground to ensure that the sole of the patient is in a state of touching the ground.

[0097] Step 2 specifically includes:

[0098] First, obstacle monitoring feedback is performed. The external torque applied to each joint of the lower limb robot is monitored in real time through the torque sensors on the output shafts of the motors of each joint of the lower limb robot. The external torque applied to each joint of the lower limb robot is calculated using the following formula:

[0099] T=T r -T0

[0100] T0 is the torque generated by the weight of each joint of the lower limb robot (including left and right hip joints and left and right knee joints), T r is the real-time monitored torque of the joint, and T is the external torque of the joint.

[0101] When the external torque applied to any joint of the lower limb robot exceeds a preset torque threshold, it is determined that an obstacle is encountered, and the lower limb robot is controlled to stop moving;

[0102] When the external torque applied to the joints of the lower limb robot does not exceed the threshold of the preset torque, the sole of the patient's foot is ensured to be in a ground contact state through feedback from the sole pressure sensor. Specifically, the sole pressure of the patient's foot is monitored in real time through the sole pressure sensor. When the sole pressure exceeds the preset pressure value, the lower limb robot is controlled to make the sole pressure lower than the preset pressure value.

[0103] When the plantar pressure does not exceed the preset pressure value, the plantar height feedback is used to ensure that the patient's plantar is in a ground contact state. Specifically, the plantar height is calculated by the following formula:

[0104] x=L1cos·(θ1)+L2cos·(θ1+θ2)

[0105] h=Hxd

[0106] Where x is the height difference between the hip joint and the ankle joint, L1 is the thigh length of the lower limb robot, L2 is the calf length of the lower limb robot, θ1 is the angle between the thigh of the lower limb robot and the vertical line, θ2 is the angle between the thigh and the calf of the lower limb robot, H is the distance from the hip joint of the lower limb robot to the ground, d is the distance from the ankle joint of the lower limb robot to the plantar plane, h is the height of the plantar from the ground, are the first-order derivatives of θ1 and θ2 respectively.

[0107] When the height of the sole of the foot from the ground is less than zero, θ1 and θ2 are adjusted to ensure that the height of the sole of the foot from the ground remains zero.

[0108] Step 3: After ensuring through a safety status detection that the patient has not encountered any obstacles and is in a ground contact state, the movement of the lower limb robot is controlled by controlling the rotation of the driving wheels of the lower limb robot.

[0109] Step 4: The motion parameters of the patient's lower limbs are obtained through the lower limb robot, and the horizontal speed of the patient's soles is calculated. Based on the horizontal speed of the patient's soles, the speed of the driving wheels of the lower limb robot is controlled to be consistent with the horizontal speed of the patient's soles, so that the patient can start straight walking training.

[0110] Among them, the end plantar velocity of the lower limb robot is the horizontal plantar velocity, which is equivalent to the horizontal velocity of the ankle joint and can be calculated based on the length of the thigh and shank and the angular velocity of the joint.

[0111] In one embodiment of the present invention, the lower limb robot obtains the thigh length L1, the calf length L2, the angle θ1 between the thigh and the vertical line, and the angle θ2 between the thigh and the calf of different patients, and calculates the patient's ankle joint horizontal speed, that is, the plantar horizontal speed v f , the calculation formula is:

[0112]

[0113] In the formula, v ankle is the horizontal velocity of the ankle joint.

[0114] Based on the horizontal speed of the patient's sole, the speed of the driving wheel of the lower limb robot is controlled to be consistent with the horizontal speed of the patient's sole, so that the patient starts to walk straight. Specifically, the travel speed of the lower limb robot is calculated according to the horizontal speed of the end sole: v = -v f , v l =v r =v, where v is the moving speed of the lower limb robot, v f is the horizontal velocity of the sole of the foot, the velocity is positive when it is forward and negative when it is backward, v l is the speed of the left driving wheel, v r is the speed of the right driving wheel.

[0115] Step 5: According to the turning radius r and the horizontal speed of the patient's sole, the angular velocity of the lower limb robot and the speeds of the left and right driving wheels are calculated, and the lower limb robot is controlled to turn by the speed difference of the left and right driving wheels, so that the patient can turn during the straight walking training:

[0116] Specifically, it is achieved through the following formula: Wherein, ω is the angular velocity, d is the distance between the two feet of the lower limb robot (the foot spacing is the horizontal distance between the two foot structures), D is the wheelbase of the driving wheels on both sides of the lower limb robot (the wheelbase of the two driving wheels, the driving wheelbase is the distance between the two driving wheels’ contact points), r is the turning radius, sign l is the direction variable related to the lower limb robot’s touching foot. When the touching foot and the turning direction are on the same side, this variable is -1; when the touching foot and the turning direction are on opposite sides, this variable is 1. m This is the direction variable associated with the driving wheel. This variable is -1 when turning left and 1 when turning right.

[0117] The larger the turning radius, the closer it is to going straight, and the smaller the turning radius, the faster it turns. The algorithm will limit the minimum turning radius (a minimum turning radius value is set in the algorithm in advance based on the developer's experience and the machine size. The patient cannot change the turning radius to less than this value. In some embodiments of the present invention, this value is set to 0.5m, and in other embodiments it can also be modified according to specific circumstances). The patient can control the turning radius within a limited range according to the needs of moving forward.

[0118] Step 6: Calculate the target heading angle of the lower limb robot through the turning radius and the horizontal speed of the sole, obtain the actual heading angle of the lower limb robot according to the electronic compass on the lower limb robot, and correct the actual heading angle of the lower limb robot according to the target heading angle.

[0119] The calculation formula of the target heading angle is:

[0120]

[0121] in, is the target heading angle, is the heading angle at the beginning of walking, measured by an electronic compass, and ω(t) is a function of the angular velocity, describing the angular velocity that changes with time t.

[0122] The actual heading angle of the lower limb robot is corrected by the target heading angle. The correction method is:

[0123]

[0124] Among them, v l is the speed of the left driving wheel before correction, v r is the speed of the right driving wheel before correction, v l ' is the corrected speed of the left driving wheel, v r ′ is the corrected speed of the right driving wheel, is the current heading angle, measured by an electronic compass. is the error correction function, which is used to calculate the speed increment of the driving wheel.

[0125] In one embodiment of the present invention, a control device for an autonomous navigation lower limb robot is also provided, comprising the following modules:

[0126] In the training module, the lower limb robot drives the patient to start training in situ according to the standard movement gait;

[0127] A motion state adjustment module is used to perform safety state detection in the order of priority of obstacle monitoring feedback, sole pressure sensor feedback, and sole height feedback, and adjust the motion state of the lower limb robot according to the feedback of the safety state detection;

[0128] A travel control module, used to control the travel of the lower limb robot by controlling the rotation of the driving wheels of the lower limb robot after ensuring that the patient has not encountered any obstacles and is in a ground contact state through a safety state detection;

[0129] A straight walking training control module is used to obtain the motion parameters of the patient's lower limbs through the lower limb robot, calculate the horizontal speed of the patient's soles, and control the speed of the driving wheel of the lower limb robot based on the horizontal speed of the patient's soles to make it consistent with the horizontal speed of the patient's soles, so that the patient can perform straight walking training;

[0130] A turning control module is used to calculate the angular velocity of the lower limb robot and the speeds of the left and right driving wheels according to the turning radius r and the horizontal speed of the patient's sole, and control the turning of the lower limb robot through the speed difference of the left and right driving wheels, so that the patient can turn during the straight walking training;

[0131] The actual heading angle correction module is used to calculate the target heading angle of the lower limb robot through the turning radius and the horizontal speed of the sole, and to correct the actual heading angle of the lower limb robot according to the target heading angle.

[0132] The device also includes a standard motion gait acquisition module, which is used to collect gait images of ordinary people to extract effective gait information, obtain a gait motion parameter database, and establish a gait model based on the gait motion parameter database. The standard motion gait obtained based on the gait model can enable the lower limb robot to drive the patient to start training on the spot according to the standard motion gait.

[0133] In one of the embodiments of the present invention, a terminal device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the aforementioned method when executing the computer program.

[0134] In one of the embodiments of the present invention, a computer-readable storage medium is further provided, wherein the computer-readable storage medium stores a computer program, and the computer program implements the steps of the aforementioned method when executed by a processor.

[0135] The above is a detailed introduction to a control method for an autonomous navigation lower limb robot provided by the present invention. The above description of the disclosed embodiments enables professionals and technicians in the field to implement or use the present invention. Various modifications to these embodiments will be obvious to professionals and technicians in the field, and the general principles defined in this article can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown in this article, but will conform to the widest range consistent with the principles and novel features disclosed in this article.

Claims

1. A control method for an autonomous navigation lower limb robot, characterized in that: The steps include: Use the lower limb robot to guide the patient to perform gait training according to the standard movement gait; Perform safety state detection in the order of priority of obstacle monitoring feedback, sole pressure sensor feedback, and sole height feedback, and adjust the motion state of the lower limb robot according to the feedback of the safety state detection; After ensuring through a safety status detection that the patient has not encountered any obstacles and is in a ground contact state, the movement of the lower limb robot is controlled by controlling the driving wheels of the lower limb robot to rotate; The lower limb robot obtains the motion parameters of the patient's lower limbs, calculates the patient's foot horizontal speed, and controls the speed of the driving wheel of the lower limb robot based on the patient's foot horizontal speed, so that the speed of the driving wheel is consistent with the patient's foot horizontal speed, so that the patient can perform straight walking training; According to the turning radius r and the horizontal speed of the patient's sole, the angular velocity of the lower limb robot and the speed of the driving wheels on both sides are calculated, and the turning of the lower limb robot is controlled by the speed difference of the driving wheels on both sides, so that the patient can realize turning during the straight walking training process; The target heading angle of the lower limb robot is calculated by the turning radius and the horizontal speed of the sole, and the actual heading angle of the lower limb robot is corrected according to the target heading angle.

2. The control method of an autonomous navigation lower limb robot according to claim 1, characterized in that: The method for acquiring the standard movement gait comprises the following steps: Collect normal people's gait images, extract gait information, and obtain gait motion parameter database; A gait model is established based on the gait motion parameter database, and a standard motion gait is obtained based on the gait model.

3. The control method of an autonomous navigation lower limb robot according to claim 1, characterized in that: The safety state detection is performed in the order of priority of obstacle monitoring feedback, sole pressure sensor feedback, and sole height feedback, and the motion state of the lower limb robot is adjusted according to the feedback of the safety state detection, including: Obstacle monitoring feedback is performed to monitor the external torque applied to each joint of the lower limb robot in real time. When the external torque applied to any joint of the lower limb robot exceeds a preset torque threshold, it is determined that an obstacle has been encountered, and the lower limb robot is controlled to stop moving. When the external torque applied to the joints of the lower limb robot does not exceed a preset torque threshold, the plantar pressure of the patient is monitored in real time, and when the plantar pressure exceeds a preset pressure value, the lower limb robot is controlled to make the plantar pressure lower than the preset pressure value; When the sole pressure does not exceed the preset pressure value, the sole height feedback is used to ensure that the patient's sole is in contact with the ground.

4. The control method of the autonomous navigation lower limb robot according to claim 3, characterized in that: The calculation formula of the height of the sole from the ground is: h=Hxd x=L1cos·(θ1)+L2cos·(θ1+θ2) Wherein, h is the height of the sole from the ground, H is the distance from the hip joint of the lower limb robot to the ground, d is the distance from the ankle joint of the lower limb robot to the sole plane, x is the height difference between the hip joint and the ankle joint, L1 is the thigh length of the lower limb robot, L2 is the calf length of the lower limb robot, θ1 is the angle between the thigh of the lower limb robot and the vertical line, θ2 is the angle between the thigh and the calf of the lower limb robot; When the height of the sole of the foot from the ground is less than zero, θ1 and θ2 are adjusted to ensure that the height of the sole of the foot remains zero.

5. The control method of an autonomous navigation lower limb robot according to claim 1, characterized in that: The calculation formula of the horizontal speed of the sole is: In the formula, v f is the horizontal velocity of the foot, v ankle is the horizontal speed of the ankle joint, L1 is the thigh length of the lower limb robot, L2 is the calf length of the lower limb robot, θ1 is the angle between the thigh of the lower limb robot and the vertical line, θ2 is the angle between the thigh and the calf of the lower limb robot, are the first-order derivatives of θ1 and θ2 respectively.

6. A control method for an autonomous navigation lower limb robot according to any one of claims 1 to 5, characterized in that: The calculation formula for the angular velocity of the lower limb robot turning and the speed of the left and right driving wheels is: In the formula, ω is the angular velocity, d is the distance between the two feet of the lower limb robot, D is the distance between the two driving wheels of the lower limb robot, r is the turning radius, and sign l is the direction variable related to the lower limb robot’s ground contact foot, sign m is the direction variable related to the driving wheel, v l is the speed of the left driving wheel, v r is the speed of the right driving wheel.

7. The control method of the autonomous navigation lower limb robot according to claim 6, characterized in that: The calculation formula of the target heading angle is: In the formula, is the target heading angle, is the heading angle at the beginning of walking, ω(t) is a function of the angular velocity, describing the angular velocity changing with time t; The method of correcting the actual heading angle of the lower limb robot by using the target heading angle is as follows: In the formula, v l is the left driving wheel speed before correction, v r is the right driving wheel speed before correction, v l ' is the corrected left driving wheel speed, v r ′ is the corrected right driving wheel speed, is the current heading angle, is the error correction function.

8. A control device for an autonomous navigation lower limb robot, characterized in that: For implementing the method described in any one of claims 1 to 7, the device comprises: In the training module, the lower limb robot drives the patient to start training in situ according to the standard movement gait; A motion state adjustment module is used to perform safety state detection in the order of priority of obstacle monitoring feedback, sole pressure sensor feedback, and sole height feedback, and adjust the motion state of the lower limb robot according to the feedback of the safety state detection; A travel control module, used to control the travel of the lower limb robot by controlling the rotation of the driving wheels of the lower limb robot after ensuring that the patient has not encountered any obstacles and is in a ground contact state through a safety state detection; A straight walking training control module is used to obtain the motion parameters of the patient's lower limbs through the lower limb robot, calculate the horizontal speed of the patient's soles, and control the speed of the driving wheel of the lower limb robot based on the horizontal speed of the patient's soles to make it consistent with the horizontal speed of the patient's soles, so that the patient can perform straight walking training; A turning control module is used to calculate the angular velocity of the lower limb robot and the speeds of the left and right driving wheels according to the turning radius r and the horizontal speed of the patient's sole, and control the turning of the lower limb robot through the speed difference of the left and right driving wheels, so that the patient can turn during the straight walking training; The actual heading angle correction module is used to calculate the target heading angle of the lower limb robot through the turning radius and the horizontal speed of the sole, and to correct the actual heading angle of the lower limb robot according to the target heading angle.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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