阅读说明：本技术 一种轮腿式移动机器人蠕动的控制系统及其控制方法 (Control system and control method for wriggling of wheel-legged mobile robot ) 是由 尤波 廉文昊 齐华囡 李佳钰 闫俊青 高彪 于 2021-07-27 设计创作，主要内容包括：本发明提供了一种轮腿式移动机器人蠕动的控制系统及其控制方法,涉及机器人控制技术领域。该控制系统包括速度传感器、比较器、微分器、模糊控制器、保留器、下一级控制器、驱动车轮和制动车轮。该控制方法的步骤为：首先,通过采集信号并计算获得机器人制动车轮的线速度误差和线速度误差变化率,将制动车轮的线速度误差和线速度误差变化率输入到模糊控制器中,模糊控制器输出驱动轮和制动轮滑转率的调节增量,经保留器与上一次滑转率值相加迭代并将最终滑转率目标值输入到下一级控制器中,进而调整驱动轮和制动轮转速达到目标滑转率。通过采用本方法,能充分利用制动轮后退阻力,降低机器人车体蠕动对驱动轮牵引力和转速要求,减少车体后退,提高行驶效率,从而达到降低能量消耗的目的。(The invention provides a control system and a control method for the peristalsis of a wheel-legged mobile robot, and relates to the technical field of robot control. The control system comprises a speed sensor, a comparator, a differentiator, a fuzzy controller, a retainer, a next-stage controller, a driving wheel and a braking wheel. The control method comprises the following steps: firstly, acquiring signals and calculating to obtain a linear speed error and a linear speed error change rate of a braking wheel of the robot, inputting the linear speed error and the linear speed error change rate of the braking wheel into a fuzzy controller, outputting an adjusting increment of the slip rate of a driving wheel and the braking wheel by the fuzzy controller, adding the adjusting increment and a last slip rate value through a retainer for iteration, inputting a final slip rate target value into a next-stage controller, and further adjusting the rotating speed of the driving wheel and the braking wheel to reach the target slip rate. By adopting the method, the retreating resistance of the brake wheel can be fully utilized, the requirements of the creeping of the robot body on the traction force and the rotating speed of the driving wheel are reduced, the retreating of the robot body is reduced, the running efficiency is improved, and the purpose of reducing energy consumption is achieved.)

1. The control system for the peristalsis of the wheel-leg type mobile robot is characterized by comprising a speed sensor, a comparator, a differentiator, a fuzzy controller, a retainer, a next-stage controller, driving wheels and braking wheels;

the speed sensor is used for measuring the actual linear speed of the wheel;

the comparator is used for calculating the linear speed error of the braking wheel;

the differentiator is used for calculating the linear speed error change rate;

the fuzzy controller is used for obtaining wheel slip rate adjustment increment through fuzzy reasoning;

the retainer is used for storing the last slip ratio target value;

the next-stage controller is used for controlling the rotating speed of the wheels so as to enable the wheels to reach a target slip rate;

the driving wheels and the braking wheels are controlled objects of the control system.

2. The control method of the control system for the peristaltic motion of the wheel-legged mobile robot according to claim 1, comprising the steps of:

the linear velocity of a brake wheel in the creeping process of the robot is obtained by utilizing the velocity sensor, and the average linear velocity v ═ Σ v of the brake wheel is obtained_iAnd/j (j is the number of brake wheels) and the sign of the speed of the robot in the backward direction is negative. The two input quantities of the comparator are respectively the actual linear velocity and the target linear velocity 0 of the braking wheel of the robot, and the linear velocity error e-v-0-v and the linear velocity error change rate d of the braking wheel are calculated through the comparator and the differentiator

Secondly, the obtained linear velocity error and the linear velocity error change rate of the braking wheel are used as input quantities of the fuzzy controller, and two corresponding fuzzy input quantities E and EC are obtained by utilizing membership function fuzzy quantization;

thirdly, fuzzy reasoning is carried out on the obtained two fuzzy input quantities E and EC of the linear speed error and the linear speed error change rate of the brake wheel according to a fuzzy rule so as to obtain two fuzzy control output quantities delta S of the corresponding driving wheel slip ratio adjustment increment and the brake wheel slip ratio adjustment increment_driAnd Δ S_bra；

(IV) according to the two obtained fuzzy control output quantities Delta S_driAnd Δ S_braObtaining the wheel slip rate adjustment increment delta s after the ambiguity resolution_driAnd Δ s_braAnd adding the target value of the slip rate of the driving wheel and the brake wheel in the retainer, performing iterative calculation to obtain the target value of the slip rate of the driving wheel and the brake wheel, storing the target value of the slip rate of the wheel in the retainer, inputting the target value of the slip rate of the wheel into a next-stage controller, and controlling the rotating speed of the wheel to reach the target slip rate, so that the robot obtains good traction performance and running efficiency in the creeping process.

3. The method of claim 2, wherein the brake wheel linear velocity error e, linear velocity error rate of changeDrive wheel slip ratio adjustment increment Δ s_driAnd brake wheel slip rate adjustment increment Δ s_braThe fuzzy language values of (1) are: { NB, NS, ZE, PS, PB }, the elements in the set representing negative big, negative small, zero, positive small, positive big, respectively.

4. The method of claim 2, wherein the fuzzy rule is:

if EC is negative large and E is negative, then Δ S_driIs positive; if EC is small negative and E is negative, then Δ S_driIs small; if E is negative and EC is negative, then Δ S_braIs positive; if E is small negative and EC is negative, then Δ S_braIs small;

if EC is positive and E is positive, then Δ S_driThe negative is large; if EC is positive small and E is positive, then Δ S_driThe negative is small; if it isE is positive and EC is positive, then Δ S_braThe negative is large; if E is positive small and EC is positive, then Δ S_braThe negative is small;

if EC is zero and E is zero, then Δ S_driAnd Δ S_braAre all zero;

if EC and E are opposite in sign, Δ S_driAnd Δ S_braAre all zero.

5. A method according to claim 2, wherein the wheel slip ratio is adjusted by an incremental amount as_driAnd Δ s_braAdding the target value of the last slip ratio of the retainer and the target value of the slip ratio of the driving wheel and the braking wheel to obtain the target value of the slip ratio of the driving wheel and the braking wheel by iterative calculation:

s_dri＝s′_dri+Δs_dri，s_bra＝s′_bra+Δs_bra

wherein, s'_driAnd s'_braThe last wheel slip target value in the retainer.

6. A method according to claim 2, wherein the slip rate increment control of the drive wheels and the brake wheels is performed using a fuzzy controller with an output as_driAnd Δ s_braThe two next-stage controller inputs are s_driAnd s_braThe rotation speed and the slip ratio of the driving wheel and the braking wheel are respectively controlled.

Technical Field

The invention belongs to the technical field of robot control, and particularly relates to a wheel-leg type mobile robot peristalsis control system and a control method thereof.

Background

With the continuous deepening of detection degrees of stars such as moon and mars in various countries, complex environments such as meteor craters also become detection targets, and the asterism detection mobile robot is required to have strong large-angle climbing moving capability and multi-terrain self-adaptive capability. The wheel-leg type mobile robot has a multi-degree-of-freedom wheel-leg structure, can realize various gaits such as peristalsis and the like, has strong moving capacity, and is widely used for planet detection. In the creeping climbing process of the wheel-legged mobile robot, the conditions of large backward sliding of the brake wheel and overlarge sliding rate of the drive wheel are caused by the discordance of the drive wheel and the brake wheel, and the energy consumption and the climbing failure risk of the robot are increased. Therefore, the coordination control between the driving wheel and the braking wheel is an important problem for fully utilizing the traction capacity of the robot and saving energy.

In order to solve the above problems, some researchers have implemented direct control of wheel traction by installing a six-dimensional force sensor on a wheel, but the six-dimensional force sensor is heavy and is not suitable for being installed on a robot. In a certain slip ratio change range, wheel traction increases along with the increase of the slip ratio, and some researchers set a wheel rotation speed control method taking the slip ratio as a target according to traction and retreating resistance requirements of a driving wheel and a braking wheel, but for complex and changeable terrains, wheel-ground contact model parameters and a proper wheel target slip ratio are difficult to accurately determine. Therefore, it is necessary to enhance the degree of intelligence of the control method and improve the adaptability to variable terrain.

Disclosure of Invention

The invention solves the problems that the wheel-leg type mobile robot has overlarge slip rate of driving wheels and larger backward movement of a vehicle body due to the fact that the driving wheels and the brake wheels are not coordinated in the creeping process, so that the robot fails to climb a slope and the energy consumption of the robot is increased.

The invention provides a wheel-leg type mobile robot peristalsis control system and a control method thereof, wherein the control system comprises a speed sensor, a comparator, a differentiator, a fuzzy controller, a retainer, a next-stage controller, driving wheels and braking wheels;

the speed sensor is used for measuring the actual linear speed of the wheel;

the comparator is used for calculating the linear speed error of the braking wheel;

the differentiator is used for calculating the linear speed error change rate;

the fuzzy controller is used for obtaining wheel slip rate adjustment increment through fuzzy reasoning;

the retainer is used for storing the last slip ratio target value;

the next-stage controller is used for controlling the rotating speed of the wheels so as to enable the wheels to reach a target slip rate;

the driving wheels and the braking wheels are controlled objects of the control system.

The control method comprises the following steps:

the linear velocity of a brake wheel in the creeping process of the robot is obtained by utilizing the velocity sensor, and the average linear velocity v ═ Σ v of the brake wheel is obtained_iAnd/j (j is the number of brake wheels) and the sign of the speed of the robot in the backward direction is negative. The two input quantities of the comparator are respectively the actual linear velocity and the target linear velocity 0 of the braking wheel of the robot, and the linear velocity error e-v-0-v and the linear velocity error change rate of the braking wheel are calculated through the comparator and the differentiator

Secondly, the obtained linear velocity error and the linear velocity error change rate of the braking wheel are used as input quantities of the fuzzy controller, and two corresponding fuzzy input quantities E and EC are obtained by utilizing membership function fuzzy quantization;

thirdly, fuzzy reasoning is carried out on the obtained two fuzzy input quantities E and EC of the linear velocity error and the linear velocity error change rate of the brake wheel according to a fuzzy rule so as to obtain the corresponding adjustment increase of the slip ratio of the driving wheelTwo fuzzy control output quantities delta S of quantity and brake wheel slip rate regulation increment_driAnd Δ S_bra；

(IV) according to the two obtained fuzzy control output quantities Delta S_driAnd Δ S_braObtaining the wheel slip rate adjustment increment delta s after the ambiguity resolution_driAnd Δ s_braAnd adding the target value of the slip rate of the driving wheel and the brake wheel in the retainer, performing iterative calculation to obtain the target value of the slip rate of the driving wheel and the brake wheel, storing the target value of the slip rate of the wheel in the retainer, inputting the target value of the slip rate of the wheel into a next-stage controller, and controlling the wheel to reach the target slip rate, so that the robot obtains good traction performance and driving efficiency in the creeping process.

Further, in the method, the linear speed error e and the linear speed error change rate of the brake wheelThe change value deltas of the slip ratio of the driving wheel_driAnd a value of change of slip rate of the brake wheel Δ s_braThe fuzzy language values of (1) are: { NB, NS, ZE, PS, PB }, the elements in the set representing negative big, negative small, zero, positive small, positive big, respectively.

Further, in the above method, the fuzzy rule is:

if EC is negative large and E is negative, then Δ S_driIs positive; if EC is small negative and E is negative, then Δ S_driIs small; if E is negative and EC is negative, then Δ S_braIs positive; if E is small negative and EC is negative, then Δ S_braIs small;

if EC is positive and E is positive, then Δ S_driThe negative is large; if EC is positive small and E is positive, then Δ S_driThe negative is small; if E is positive and EC is positive, then Δ S_braThe negative is large; if E is positive small and EC is positive, then Δ S_braThe negative is small;

if EC is zero and E is zero, then Δ S_driAnd Δ S_braAre all zero;

if EC and E are opposite in sign, Δ S_driAnd Δ S_braAre all zero;

further, the wheel slip ratio adjustment increment Δ s described in the above method_driAnd Δ s_braAdding the target value of the last slip ratio of the retainer and the target value of the slip ratio of the driving wheel and the braking wheel to obtain the target value of the slip ratio of the driving wheel and the braking wheel by iterative calculation:

s_dri＝s′_dri+Δs_dri，s_bra＝s′_bra+Δs_bra

wherein, s'_driAnd s'_braThe last wheel slip target value in the retainer.

Further, the fuzzy controller in the method performs slip rate increment control on the driving wheel and the braking wheel, and the output is delta s_driAnd Δ s_braThe two next-stage controller inputs are s_driAnd s_braAnd respectively controlling the slip rates of the driving wheel and the braking wheel.

Drawings

FIG. 1 is a schematic diagram of the peristalsis of a wheel-legged mobile robot;

FIG. 2 is a diagram of a control system for the peristalsis of the wheel-legged mobile robot;

FIG. 3 is a diagram of the internal structure of the fuzzy controller;

FIG. 4 is a graph of fuzzy controller linguistic variable membership functions.

Detailed Description

The present invention will be further described with reference to the accompanying drawings and the detailed description, but it should be understood that the scope of the invention is not limited by the detailed description.

The wheel-leg type mobile robot changes the included angle between the main rocker arms and controls the rotating speed of the wheels at the same time, so that one part of the wheels are used as brake wheels to keep static relative to the ground, and the other part of the wheels are used as driving wheels to move relative to the ground, and the robot performs periodic peristaltic action. Fig. 1 shows a backward peristalsis schematic diagram of a six-wheel leg robot, wherein the front two wheels Wo1 and Wo2 are used as driving wheels and the rear four wheels Wo 3-Wo 6 are brake wheels before the backward peristalsis; the front two wheels Wo1 and Wo2 are used as braking wheels and the rear four wheels WO 3-WO 6 are used as driving wheels after the rear half period of backward peristalsis.

The structure of the control system for the peristalsis of the wheel-legged mobile robot is shown in fig. 2, wherein the control system comprises a speed sensor, a comparator, a differentiator, a fuzzy controller, a retainer, a next-stage controller, a driving wheel and a braking wheel. The speed sensor is used for measuring the actual linear speed of a wheel, the comparator is used for calculating the linear speed error of the braking wheel, the differentiator is used for calculating the change rate of the linear speed error, the fuzzy controller is used for carrying out fuzzy reasoning to obtain the adjustment increment of the wheel slip rate, the retainer is used for storing the target value of the last slip rate, the next-stage controller is used for controlling the rotating speed of the wheel so that the wheel reaches the target slip rate, and the driving wheel and the braking wheel are control objects of the control system.

The control method of the control system comprises the following steps:

the linear velocity of a brake wheel in the creeping process of the robot is obtained by utilizing the velocity sensor, and the average linear velocity v ═ Σ v of the brake wheel is obtained_iAnd/j (j is the number of brake wheels) and the sign of the speed of the robot in the backward direction is negative. The two input quantities of the comparator are respectively the actual linear velocity and the target linear velocity 0 of the braking wheel of the robot, and the linear velocity error e-v-0-v and the linear velocity error change rate of the braking wheel are calculated through the comparator and the differentiator

Secondly, the obtained linear velocity error and the linear velocity error change rate of the braking wheel are used as input quantities of the fuzzy controller, and two corresponding fuzzy input quantities E and EC are obtained by utilizing membership function fuzzy quantization;

as shown in fig. 3, which is an internal structure diagram of the fuzzy controller, the linguistic variables of the fuzzy controller are defined in the basic domains of the fuzzy set as:

the fuzzy subset is { NB, NS, ZE, PS, PB }, and the elements in the subset respectively represent negative big, negative small, zero, positive small, and positive big.

If e is set, the process is carried out,the variation range is [ -4,4 [)]If the interval is not in the interval, the value can be taken as [ a, b ] through a linear variation formula]To [ -4,4 ] by a continuous amount]In the meantime.

The membership functions for each fuzzy state select symmetric triangles as shown in figure 4. Fuzzy quantization of linear velocity error e and linear velocity error change rate of braking wheel by using triangular symmetric membership functionObtaining two corresponding fuzzy input quantities E and EC;

thirdly, fuzzy reasoning is carried out on the obtained two fuzzy input quantities E and EC of the linear speed error and the linear speed error change rate of the brake wheel according to a fuzzy rule so as to obtain two fuzzy control output quantities delta S of the corresponding driving wheel slip ratio adjustment increment and the brake wheel slip ratio adjustment increment_driAnd Δ S_bra；

The fuzzy rule is as follows:

if EC is negative large and E is negative, then Δ S_driIs positive; if EC is small negative and E is negative, then Δ S_driIs small; if E is negative and EC is negative, then Δ S_braIs positive; if E is small negative and EC is negative, then Δ S_braIs small;

if EC is positive and E is positive, then Δ S_driThe negative is large; if EC is positive small and E is positive, then Δ S_driThe negative is small; if E is positive and EC is positive, then Δ S_braThe negative is large; if E is positive small and EC is positive, then Δ S_braThe negative is small;

if EC is zero and E is zero, then Δ S_driAnd Δ S_braAre all zero;

if EC and E are opposite in sign, Δ S_driAnd Δ S_braAre all zero;

the fuzzy rule table made according to the fuzzy rule is as follows:

note: there are 2 fuzzy control rules in the table, Δ S from left to right_braAnd Δ S_driThe fuzzy control rule of (1).

Output variable deltas of a fuzzy controller_driAnd Δ S_braMethod for solving ambiguity by using gravity center method to obtain wheel slip rate adjustment increment delta s_driAnd Δ s_bra。

The slip ratio of the drive wheels is defined as,

the slip rate of the brake wheel is defined as,

where ω is a positive value and v is a negative value. The initial value of the slip rate of the driving wheel is 0.8, and the value range is 0.6-0.9. The initial value of the slip rate of the brake wheel is 1, and the value range is 1-1.9.

(IV) adjusting the obtained wheel slip ratio by an increment deltas_driAnd Δ s_braAnd adding the target value of the slip rate of the last driving wheel and the target value of the slip rate of the braking wheel in the retainer for iterative calculation to obtain the target value of the slip rate of the driving wheel and the braking wheel at the current time as follows:

s_dri＝s′_dri+Δs_dri，s_bra＝s′_bra+Δs_bra

wherein, s'_driAnd s'_braThe slip target value obtained by the previous calculation of the retainer.

The target value of the slip rate of the driving wheel and the braking wheel is stored in a retainer and input into a next-stage controller, and the two next-stage controllers use ADRC active disturbance rejection controllers to control the rotating speed of the wheels so as to quickly reach the target slip rate of the wheels.

It should be understood that the above-mentioned invention is only a preferred embodiment of the present invention, and is not intended to limit the present invention.