A walking mechanism system and method of a photovoltaic intelligent cleaning robot

Abstract

The application discloses a walking mechanism system and method of a photovoltaic intelligent cleaning robot, a foot of a wheel-foot composite mechanism adopts a planar linkage mechanism, has three joints, is configured in a side swing-pitch-pitch sequence, and comprises three active joint degrees of freedom and three adaptive degrees of freedom; a supporting foot comprises a vacuum generator, a vacuum chuck and a safety valve; the adaptability of the cleaning robot is improved through a robot peristaltic gait control method and a robot wheel-foot composite movement strategy planning method, and cleaning efficiency and intelligence are promoted.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of robots, and particularly relates to a walking mechanism system and method of a robot. BACKGROUND

[0002] Photovoltaic energy is an important part of clean energy, and more and more photovoltaic power station projects are put into operation. Photovoltaic panels are arranged in the open air for a long time, and dust will accumulate after a long time, which affects the normal work of the photovoltaic panels and reduces the power generation efficiency. Therefore, the photovoltaic panels need to be cleaned regularly to make the photovoltaic power station operate efficiently. At present, photovoltaic cleaning robots have been applied to various types of photovoltaic power stations, and have high cleaning efficiency and low comprehensive cost, which is an effective way to clean photovoltaic panels.

[0003] Most of the existing photovoltaic cleaning robots are designed for photovoltaic power stations with flat terrain, and have requirements for the arrangement of photovoltaic panels. For photovoltaic power stations with complex terrain conditions and large ground undulations, when the arrangement between photovoltaic panels is misaligned and has a gap, the photovoltaic cleaning robot cannot cross the obstacle by itself and needs manual cooperation to complete the cleaning of all photovoltaic panels, which will reduce the efficiency and increase the cost. SUMMARY

[0004] In order to overcome the shortcomings of the prior art, the application provides a walking mechanism system and method of a photovoltaic intelligent cleaning robot. The foot of the wheel-foot composite mechanism adopts a planar linkage mechanism and has three joints, which are configured in the order of side swing-pitch-pitch, including 3 active joint degrees of freedom and 3 adaptive degrees of freedom. The support foot includes a vacuum generator, a vacuum suction cup and a safety valve. The adaptability of the cleaning robot is improved by the robot peristaltic gait control method and the robot wheel-foot composite movement strategy planning method, and the cleaning efficiency and intelligence are promoted.

[0005] The technical solution adopted by the application to solve the technical problems is as follows:

[0006] A walking mechanism system of a photovoltaic intelligent cleaning robot is a multi-wheel-foot composite mechanism with a support foot. The foot of the wheel-foot composite mechanism adopts a planar linkage mechanism and has three joints, which are configured in the order of side swing-pitch-pitch, including 3 active joint degrees of freedom and 3 adaptive degrees of freedom. The side swing joint functions as horizontal movement and in-place rotation, the pitch joint provides forward power during walking and can effectively adjust the attitude of the robot, realizing three-dimensional translation and three-dimensional rotation, so that the cleaning robot maintains flexible contact with the ground and reduces the impact force from the ground during movement.

[0007] The wheel-foot composite structure is installed with a walking wheel structure at the bottom end of the foot. The photovoltaic cleaning robot uses a wheel type movement mode during cleaning operation. When the movement attitude needs to be changed, the walking mechanism system is transformed into a multi-wheel-foot walking movement mode.

[0008] The support foot comprises a vacuum generator, a vacuum chuck and a safety valve; when the cleaning robot is linearly cleaning, the support foot is provided with suction force, so that the cleaning robot has grip and pressure in the case that the photovoltaic panel has dust or is inclined, and the cleaning effect is ensured; when the cleaning robot is crossing an obstacle, the chuck of the support foot is adsorbed on the photovoltaic panel by the generated suction force of the panel, and the robot gravity is overcome to complete the obstacle crossing action.

[0009] A robot peristalsis gait control method, comprising the following steps:

[0010] Step 1: initial state: the support foot is adsorbed on the photovoltaic panel, so that the cleaning robot is kept stable and falls off the photovoltaic panel;

[0011] Step 2: the body is moved forward under the support of a plurality of wheel feet, and reaches a starting state of posture conversion;

[0012] Step 3: the left front, right rear, right front and left rear wheel feet complete a lifting and placing action in turn;

[0013] Step 4: the cleaning robot is moved forward under the support of four wheel feet, and returns to the starting state of the next posture conversion.

[0014] A photovoltaic cleaning robot wheel foot composite movement strategy planning method, comprising the following steps:

[0015] Step 1: the cleaning robot receives the surrounding environment information of the external perception unit and analyzes and evaluates, and identifies the wheel movable area of the robot;

[0016] Step 2: the terrain type and parameters between the wheel movable areas are analyzed, and the obstacles are identified;

[0017] Step 3: according to the geometric characteristics of the wheel movable area and the type of the obstacle, the robot wheel movement posture of each area, i.e. the joint space state quantity, is planned;

[0018] Step 4: the pose conversion quantity between adjacent wheel states is planned.

[0019] Further, step 1 of the photovoltaic cleaning robot wheel foot composite movement strategy planning method is specifically:

[0020] Step 1-1: the cleaning robot analyzes and evaluates the surrounding environment information through the external perception unit, performs ground segmentation before obstacle identification, excludes the interference of ground information on identification, and calculates the height value of the obstacle relative to the ground according to the ground height;

[0021] Step 1-2: Ground segmentation is performed using a plane fitting method. In the fitting process, a set of space points is generated according to the two-dimensional coordinates and elevation values of the grid points of the elevation values in the sub-region. The original ground point set and the calculated ground point set are obtained by ground segmentation, and an elevation map of the cleaning robot operating area is constructed.

[0022] Further, step 2 of the wheel-foot combined movement strategy planning method of the photovoltaic cleaning robot is specifically as follows:

[0023] Step 2-1: Obtain the position, size and direction information of the obstacle according to the elevation map;

[0024] Step 2-2: Identify the type and parameters of the obstacle by calculating the bounding box. First, calculate the minimum rectangular bounding box of the obstacle. The bounding box is determined by the bottom rectangle and the height. The minimum area rectangle projected on the horizontal plane of the obstacle is the bottom of the bounding box, and the maximum height of the obstacle relative to the ground is the height of the bounding box.

[0025] Step 2-3: Determine whether the obstacle has the condition for the robot to pass through by analyzing the similarity of the obstacle and the bounding box and combining the size of the obstacle.

[0026] Further, step 3 of the wheel-foot combined movement strategy planning method of the photovoltaic cleaning robot is specifically as follows:

[0027] Step 3-1: The robot uses a segmented obstacle crossing planning method. The switching condition of the obstacle crossing step is that the robot reaches a preset pose or the robot moves to an expected position. The pose is judged according to the position feedback of the suspension and the central axis. The expected position is determined according to the position of the robot relative to the obstacle.

[0028] Step 3-2: Obtain the real-time position relationship of the robot relative to the obstacle and the feature information of the obstacle by using the single-line laser feature extraction method.

[0029] Step 3-3: In the data processing process, first filter the noise points, and then find the edge point information of the obstacle. The process of two-dimensional laser line feature extraction can be divided into three steps: data preprocessing, scan line segmentation and corner point extraction. In the obstacle crossing process, real-time tracking and monitoring of these noise points can obtain the relative position relationship between the robot and the obstacle, and then realize the switching of the obstacle crossing step.

[0030] Further, step 4 of the wheel-foot combined movement strategy planning method of the photovoltaic cleaning robot is specifically as follows:

[0031] Step 4-1: Use the state quantity and pose conversion quantity to represent the wheel-foot combined movement strategy of the cleaning robot. Use the joint space state quantity and the pose conversion quantity as the optimization variables of the movement strategy.

[0032] Step 4-2: the moving time and the energy consumption of the moving strategy are optimized as the optimization target;

[0033] Step 4-3: the constraint conditions of the optimization model include the passability constraint, the stability constraint, the robot posture constraint, the foot end mechanics constraint and the motor performance constraint;

[0034] The passability constraint is the maximum fall, the maximum gap between the panels and the large climbing angle of the photovoltaic cleaning robot crossing the photovoltaic panel; the stability constraint is the ability of the robot to resist overturning during moving across the obstacles, and the energy stability boundary method NESM is used as the basis for judging the stability of the robot;

[0035] The posture constraint of the body is that the maximum change amount of the pitch angle and the roll angle does not exceed the limit value of the smoothness;

[0036] The foot end mechanics constraint is the constraint of the leg joint angle, the foot end support force of the robot is related to the support foot joint angle, so that the ratio of the tangential foot end force generated by the contact between the support foot and the ground to the normal foot end force is less than the maximum static friction coefficient, avoiding the damage of the wheel and the photovoltaic panel caused by the long-time relative sliding between the wheel and the photovoltaic panel during the movement;

[0037] The motor performance constraint includes the torque and the angular velocity of the joint driving motor. According to the target function and the motion constraint condition, the robot wheel-foot efficient moving strategy optimization model is established.

[0038] The beneficial effects of the present application are as follows:

[0039] The present application is not limited to the photovoltaic panel terrain and the arrangement of the photovoltaic panel, and can adapt to various terrain conditions and types of photovoltaic power stations, so that the cleaning task can be completed without too much manual intervention in the whole photovoltaic power station, and the wheel-foot compound efficient moving strategy based on time and energy consumption optimization proposed in the present application optimizes the moving strategy of the cleaning robot, and realizes the optimization of the cleaning cost and the cleaning benefit. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 It is a structure schematic diagram of a photovoltaic intelligent cleaning robot walking mechanism.

[0041] Figure 2 It is a system block diagram of a photovoltaic intelligent cleaning robot walking mechanism.

[0042] Figure 3 It is a peristaltic gait schematic diagram of a photovoltaic intelligent cleaning robot.

[0043] Figure 4 It is a wheel-foot moving strategy planning flow chart of a photovoltaic intelligent cleaning robot.

[0044] Figure 5 It is a moving strategy optimization flow chart of a photovoltaic intelligent cleaning robot. Detailed Implementation

[0045] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0046] The purpose of this invention is to address the shortcomings of existing walking mechanism systems in photovoltaic cleaning robots by proposing a walking mechanism system for photovoltaic intelligent cleaning robots, thereby improving the adaptability, cleaning efficiency, and intelligence of the cleaning robots.

[0047] Reference Figure 1 and Figure 2 The present invention proposes a walking mechanism system for cleaning photovoltaic panels, which includes a sensor information processing module, an environmental perception and obstacle recognition module, a movement and obstacle avoidance planning module, and a multi-wheeled walking mechanism control module.

[0048] The walking mechanism of the photovoltaic cleaning robot is a multi-wheeled composite mechanism with supporting feet. The feet of this composite mechanism employ a planar linkage mechanism with three joints arranged in a lateral-pitch-pitch sequence, including three active degrees of freedom and three adaptive degrees of freedom. The lateral joints primarily function for lateral movement and rotation, while the pitch joints provide forward propulsion and effectively adjust the robot's posture, achieving three-dimensional translation and rotation. This allows the quadruped robot to maintain flexible contact with the ground while reducing impact forces during movement. The composite mechanism incorporates wheels at the bottom of the feet. During normal cleaning operations, the robot uses wheeled movement. When moving linearly on the photovoltaic panels, the feet maintain stability and lower the robot's center of gravity. When encountering complex terrain requiring a change in posture, the robot's multi-wheeled composite walking mechanism switches to a multi-legged movement mode under control module commands.

[0049] The support legs of the photovoltaic cleaning robot consist of a vacuum generator, vacuum suction cups, and a safety valve. When the robot walks onto a damaged panel or a gap between panels, the vacuum suction cups cannot form a closed space with the surface they are adsorbing, causing the adsorption system to fail. The safety valve automatically disconnects the suction cups from the system, thus ensuring the safety of the entire vacuum adsorption system and preventing the robot from falling. When the cleaning robot is cleaning in a straight line, the support legs, by setting appropriate suction, enable the cleaning robot to have good grip in harsh environments such as wet and slippery photovoltaic panels with a lot of dust, and to reliably adsorb onto photovoltaic panels at large tilt angles in complex terrain. They also provide appropriate downforce to ensure cleaning effectiveness. At the same time, the support legs also assist the cleaning robot in posture transitions and creeping gait. When crossing obstacles, the cleaning robot relies on the friction generated between the suction cups of the support legs and the panel to adhere to the photovoltaic panel, overcoming the robot's gravity to complete the obstacle crossing action.

[0050] ReferenceFigure 3 The photovoltaic cleaning robot walking system adopts a kind of suitable for complex environment's adherent foot type crawling robot peristalsis gait, the robot main body moves and gait transformation is separated, when the wheel foot mechanism of cleaning robot moves, the supporting foot keeps in line with the ground, makes the robot keep stable, after completing the swing of all wheel foot mechanisms in turn, the main body is lifted and moves forward, the corresponding robot state of peristalsis gait is as follows: (1) starting state, the supporting foot adsorbs photovoltaic panel, makes the cleaning robot keep stable, avoids falling from photovoltaic panel; (2) the main body moves forward under the support of four legs, reaches the starting state of a posture conversion; (3) left front, right rear, right front, left rear wheel foot completes a lifting and placing action in turn; (4) the robot moves forward under the support of four wheel feet, reaches the starting state of next posture conversion.

[0051] Referring to Figure 4 The wheel foot composite movement strategy planning flow of photovoltaic cleaning robot walking system under complex terrain is as follows: (1) receiving the surrounding environment information of external perception unit and analyzing and evaluating, identifying the wheel type movable area of wheel-legged robot; (2) analyzing the terrain type and parameter between wheel type movable area, identifying the obstacle; (3) according to the geometric characteristics of wheel type movable area and the type of obstacle, planning the robot wheel type movement posture of each area, namely the joint space state quantity; (4) planning the pose conversion quantity between each adjacent wheel type state.

[0052] The photovoltaic cleaning robot walking system analyzes and evaluates the surrounding environment information through external perception unit, carries out ground segmentation before obstacle identification, excludes the interference of ground information on identification, calculates the height value of obstacle relative to ground according to ground height; plane fitting method is adopted for ground segmentation, space point set is generated according to the two-dimensional coordinates and elevation value of elevation value grid points in sub-area in the fitting process, the original ground point set and the ground point set are obtained through ground segmentation; ground segmentation mainly includes two processes: seed point selection and iterative optimization, the points on the ground are selected as the estimation of ground model, after obtaining the plane model, the vertical distance of the points in the point set to the plane is calculated, the ground points are identified through threshold, and the plane is refitted according to these ground points, the optimal estimation of ground and the original ground point set are calculated. Through ground segmentation, the elevation map of the working area of cleaning robot is constructed.

[0053] The photovoltaic cleaning robot obtains the position, size and direction information of the obstacle according to the height map. The common obstacle type of the photovoltaic cleaning robot is the large gap between photovoltaic panels, and the obstacle is relatively regular. Therefore, the method of calculating the bounding box is used to identify the obstacle type and parameters. First, the minimum rectangular bounding box of the obstacle is calculated. The bounding box is determined by the bottom rectangle and the height. The minimum area rectangle of the horizontal projection of the obstacle is used as the bottom of the bounding box, and the maximum height of the obstacle relative to the ground is used as the height of the bounding box. Then, by analyzing the similarity of the obstacle and the bounding box, the size of the obstacle is combined to determine whether the obstacle meets the conditions for the robot to pass through. The obstacle recognition process can be divided into four steps: convex hull calculation, minimum area rectangle calculation, bounding box generation and obstacle passing condition analysis.

[0054] The cleaning robot walking system adopts a segmented mobile obstacle crossing planning mode. The switching condition of the obstacle crossing step is that the robot reaches the preset posture or the robot moves to the expected position. The posture judgment is realized by the feedback of the cleaning robot wheel-foot walking mechanism, and the expected position is judged by the distance of the cleaning robot relative to the obstacle. The cleaning robot walking system extracts features from 2D point cloud information to obtain the real-time position relationship of the robot relative to the obstacle and the feature information of the obstacle. The features in the two-dimensional laser scanning line include corner points, surface points and noise points. In the data processing process, noise points are filtered first, and then edge point information of the obstacle is found. The process of two-dimensional laser line feature extraction can be divided into three steps: data preprocessing, scanning line segmentation and feature point extraction. In the obstacle crossing process, these features are tracked and monitored in real time to obtain the relative position relationship between the robot and the obstacle, and then the planning and switching of the mobile obstacle crossing step are realized.

[0055] Reference Figure 5A novel optimization model of mobile strategy for a wheel-legged robot is proposed to achieve efficient movement. The wheel-legged robot is characterized by the state variables and pose transformation variables. The joint space state variables and pose transformation variables are used as the optimization variables of the mobile strategy. The moving time and energy consumption of the mobile strategy are used as the optimization objectives. The constraints of the optimization model include the passability constraint, stability constraint, robot pose constraint, foot mechanics constraint and motor performance constraint. The passability constraint is the maximum fall, the maximum gap between panels and the large climbing angle of the photovoltaic panel. The stability constraint is the ability of the robot to resist overturning during movement and obstacle crossing. The energy stability boundary method is used as the basis for evaluating the stability of the robot. The robot pose constraint is the maximum change of the pitch angle and roll angle, which should not exceed the limit of the stability. The foot mechanics constraint is the constraint of the leg joint angle. The ratio of the tangential foot force to the normal foot force should be less than the maximum static friction coefficient to avoid damage to the wheel and photovoltaic panel. The motor performance constraint includes the torque and angular velocity of the joint drive motor.

Claims

1. A robot wheel-foot compound movement strategy planning method of a walking mechanism system of a photovoltaic intelligent cleaning robot, characterized in that, The walking mechanism system is a multi-wheel foot composite mechanism with supporting feet; the foot of the wheel-foot composite mechanism adopts a planar linkage mechanism and has three joints to form a side swing-pitch-pitch configuration in the order of configuration, including three active joint degrees of freedom and three adaptive degrees of freedom, wherein the side swing joint functions as horizontal movement and in-place rotation, the pitch joint provides forward power during walking and can effectively adjust the posture thereof to realize three-dimensional translation and three-dimensional rotation, so that the cleaning robot and the ground are kept in flexible contact, and the impact force from the ground during movement is reduced; The wheel-foot composite mechanism is provided with a walking wheel structure at the bottom end of the foot, and the photovoltaic cleaning robot uses a wheeled moving mode during cleaning operation; when it is necessary to change the movement posture, the walking mechanism system is transformed into a multi-wheel foot walking movement mode; The supporting feet include a vacuum generator, a vacuum suction cup and a safety valve; when the cleaning robot is linearly cleaned, the suction force is set to enable the cleaning robot to have a gripping force and a pressure on the photovoltaic panel in the case that the photovoltaic panel has dust or is inclined, so as to ensure the cleaning effect; when the cleaning robot crosses an obstacle, the suction cup of the supporting foot is adsorbed on the photovoltaic panel by the suction force generated by the panel to overcome the gravity of the robot to complete the obstacle crossing action; The moving strategy planning method comprises the following steps: Step 1: the cleaning robot receives the surrounding environment information from the external perception unit and analyzes and evaluates the information to identify the wheeled movable area of the robot; Step 2: the terrain type and parameters between the wheeled movable areas are analyzed to identify the obstacles; Step 3: according to the geometric characteristics of the wheeled movable areas and the types of the obstacles, the robot wheeled movement postures of the areas, i.e. the joint space state quantities, are planned; Step 4: the pose conversion quantities between the adjacent wheeled states are planned; Step 3 of the robot wheel-foot composite moving strategy planning method is specifically as follows: Step 3-1: the robot adopts a segmented obstacle crossing planning mode, and the switching condition of the obstacle crossing step is that the robot reaches a preset posture or the robot moves to an expected position, and the posture is judged according to the position feedback of the suspension and the central shaft, and the expected position is judged according to the position of the robot relative to the obstacle; Step 3-2: a single line laser feature extraction method is adopted to obtain the real-time position relationship of the robot relative to the obstacle and the feature information of the obstacle; Step 3-3: in the data processing process, noise points are filtered first, and then edge point information of the obstacle is found; the process of two-dimensional laser line feature extraction can be divided into three steps of data preprocessing, scanning line segmentation and corner point extraction; in the obstacle crossing process, the relative position relationship of the robot and the obstacle is obtained by tracking and monitoring these noise points in real time, and then the switching of the obstacle crossing step is realized; Step 4 of the robot wheel-foot composite moving strategy planning method is specifically as follows: Step 4-1: the joint space state quantity and the pose conversion quantity are used to represent the moving strategy of the cleaning robot wheel-foot composite, and the joint space state quantity and the pose conversion quantity are used as the optimization variables of the moving strategy; Step 4-2: the moving time and the energy consumption of the moving strategy are used as the optimization objectives; The constraint conditions of the optimization model include passability constraints, stability constraints, robot posture constraints, foot end mechanics constraints and motor performance constraints; The passability constraints are the maximum fall, the maximum gap between panels and the large climbing angle of the photovoltaic cleaning robot crossing the photovoltaic panel; the stability constraints are the ability of the robot to resist overturning during moving across obstacles, and the energy stability margin method (NESM) is used as the basis for judging the stability of the robot; The robot posture constraints are that the maximum change of the pitch angle and the roll angle does not exceed the limit value of the smoothness; The foot end mechanics constraints are the constraints on the leg joint angle, the support foot joint angle related to the support foot end reaction force of the robot, the ratio of the tangential foot end force to the normal foot end force generated by the contact between the support foot and the ground is less than the maximum static friction coefficient, so as to avoid damage to the wheel and the photovoltaic panel caused by long-term relative sliding between the wheel and the photovoltaic panel during movement; The motor performance constraints include the torque and angular velocity of the joint driving motor, and according to the objective function and the motion constraint conditions, an optimization model of the wheel-foot high-efficiency movement strategy of the robot is established.

2. The robot wheel-foot compound movement strategy planning method of the walking mechanism system of the photovoltaic intelligent cleaning robot according to claim 1, characterized in that, Step 1 of the wheel-foot composite movement strategy planning method of the photovoltaic cleaning robot is specifically: Step 1-1: The cleaning robot analyzes and evaluates the surrounding environment information through the external perception unit, performs ground segmentation before obstacle identification, excludes the interference of ground information on identification, and calculates the height value of the obstacle relative to the ground according to the ground height; Step 1-2: The ground segmentation is performed by using the plane fitting method, the space point set is generated according to the two-dimensional coordinates and elevation values of the grid points in the sub-region during the fitting process, the original ground point set and the calculated ground point set are obtained by ground segmentation, and an elevation map of the working area of the cleaning robot is constructed. 3.The robot wheel-foot compound movement strategy planning method of the walking mechanism system of the photovoltaic intelligent cleaning robot according to claim 1, wherein, Step 2 of the wheel-foot composite movement strategy planning method of the photovoltaic cleaning robot is specifically: Step 2-1: Obtain the position, size and direction information of the obstacle according to the elevation map; Step 2-2: The method of calculating the bounding box is used to identify the type and parameters of the obstacle, the minimum rectangular bounding box of the obstacle is calculated first, the bounding box is determined by the bottom rectangular and the height, the minimum area rectangular projected on the horizontal plane of the obstacle is used as the bottom of the bounding box, and the maximum height value of the obstacle relative to the ground is used as the height of the bounding box; Step 2-3: Then, by analyzing the similarity between the obstacle and the bounding box, the size of the obstacle is combined to determine whether the obstacle meets the conditions for the robot to pass through the obstacle.

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