CN110262485B - Mobile robot obstacle avoidance method based on self-adaptive gravitation - Google Patents
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Abstract
A mobile robot obstacle avoidance method based on self-adaptive gravity comprises the following steps: step 1) establishing an expression of a reference track curve; step 2), self-adaptive gravity design is carried out to obtain a self-adaptive gravity value; step 3) enabling the self-adaptive gravity to act on a time scale to obtain a gravity-based reference track curve; step 4) determining the output of the fuzzy controller through a reference track curve; when the robot does not detect an obstacle in the process of tracking the track, the control quantity of the robot is determined by the output of the track tracking controller, and when the robot detects the obstacle and is close to the obstacle, the current control quantity of the robot is determined by the output of the fuzzy controller. According to the invention, when the situation of the obstacle is complex or the time for the robot to complete obstacle avoidance is long, the problem of excessive distance of the reference robot can be effectively avoided, so that the robot can quickly return to the reference track curve after completing the obstacle avoidance task, and the energy consumption of the robot is reduced.
Description
Technical Field
The invention belongs to the technical field of motion control of wheeled robots, and relates to the problem of reference track change during autonomous obstacle avoidance in the track tracking process of wheeled mobile robots, in particular to the problem of how to avoid excessive distance of a reference track robot when the situation of obstacles is complex or the time for the robot to complete obstacle avoidance is long, so that the robot can quickly return to a reference track curve after the track tracking of the robot completes an autonomous obstacle avoidance task.
Background
As the application of robots is more and more extensive, people have higher and higher requirements on the robots, especially the ability of mobile robots to interact with the surrounding environment during the movement process. The autonomy of the mobile robot is embodied in that the mobile robot can safely and effectively avoid the obstacles in the process of advancing according to the environmental information collected by the sensor and move forward towards the target direction.
One key technology in the motion control technology of the wheeled mobile robot is trajectory tracking control. The robot can encounter obstacles in the track tracking process, and the robot needs to be capable of safely and effectively bypassing the obstacles in the track tracking process under an unknown environment and continuously tracking the reference track curve motion after obstacle avoidance is finished. The problem is the autonomous obstacle avoidance in the track tracking control process of the mobile robot.
The reference track curve of the track tracking control is a function related to time, the track tracking process can be regarded as the motion of the current robot tracking reference robot, and the position and the posture of the reference robot are determined by the reference track curve and the time. In the process of avoiding the obstacle, if the obstacle situation is complex or the time for avoiding the obstacle is long, the position of the reference robot and the current position of the robot form a large error, so that the current robot tracks the reference robot at the fastest speed, and the robot does not move on the reference track curve in the tracking process.
Disclosure of Invention
The invention mainly aims to solve the problem that the position of a reference robot is excessively far away when the robot autonomously avoids an obstacle in the track tracking process, and provides a mobile robot obstacle avoiding method based on self-adaptive gravitation.
The invention adopts the following technical scheme:
a mobile robot obstacle avoidance method based on self-adaptive gravity is characterized by comprising the following steps:
step 1) establishing an expression of a reference track curve;
step 2) self-adaptive gravity design to obtain a self-adaptive gravity value;
step 3) enabling the self-adaptive gravity to act on a time scale to obtain a gravity-based reference track curve;
step 4) determining the output of the fuzzy controller through a reference track curve; when the robot does not detect an obstacle in the process of tracking the track, the control quantity of the robot is determined by the output of the track tracking controller, and when the robot detects the obstacle and is close to the obstacle, the current control quantity of the robot is determined by the output of the fuzzy controller.
The reference trajectory curve includes a straight line or a circle or a curve.
The adaptive gravitation value is
Wherein theta is△An angle formed by the connection line of the two robots and the orientation of the reference robot, d△Distance of the robot from the reference robot, ksIs a coefficient of gravity, d0Is the minimum gravitational distance.
The step 3) is specifically as follows: applying the self-adaptive gravitation on the time step T, and introducing a time scale coefficient kt，
The expression generated with reference to the trajectory curve is
Wherein: (x)r,yr) Is the expected position coordinate of the reference robot in a world coordinate system, fx fyThe trajectory functions are respectively of an x axis and a y axis.
The step 4) is specifically as follows: output v of the fuzzy controller1、w1And the output v of the trajectory tracking controller2、w2Weighted summation as control quantity v of forward speed and steering angular speed of robotc、wc(ii) a And introducing a weighting coefficient lambda, then
In the formula dmin∈[0,b3]，b3A third level distance which is a distance scale level of the fuzzy controller;
d when the robot does not detect an obstacle during trajectory trackingmin＝b3λ is 1, and the control amount of the robot is determined by the output of the trajectory tracking controller; when the robot detects an obstacle and is in close proximity, the amount of control is determined by the output of the fuzzy controller.
As can be seen from the above description of the present invention, compared with the prior art, the present invention has the following advantages:
the invention provides a mobile robot obstacle avoidance method based on self-adaptive gravitation, which can effectively avoid the problem that a reference robot excessively keeps away when the obstacle situation is more complex or the robot finishes obstacle avoidance for a longer time, so that the robot can quickly return to a reference track curve after finishing an obstacle avoidance task, and the energy consumption of the robot is reduced.
Drawings
FIG. 1 is a block diagram of decision control for mobile robot tracking and obstacle avoidance;
FIG. 2 is a tracking situation of excessive distance from a reference robot after obstacle avoidance is completed;
FIG. 3 is a relative position of a current robot to a reference robot;
FIG. 4 shows the equation when d△>>d0And theta△The relative position condition is close to pi/2;
FIG. 5 is a diagram of a concave special obstacle encountered during trajectory tracking;
FIG. 6 is an autonomous obstacle avoidance scenario when unprocessed circular trajectory curves reference trajectories are generated;
FIG. 7 is a diagram of autonomous obstacle avoidance during dynamic reference trajectory generation based on adaptive gravity circular trajectory curves;
FIG. 8 is an autonomous obstacle avoidance scenario when unprocessed arbitrary trajectory profile reference trajectory generation;
FIG. 9 is an autonomous obstacle avoidance situation when an arbitrary curve dynamic reference trajectory generation method based on adaptive gravity is used;
the invention is described in further detail below with reference to the figures and specific examples.
Detailed Description
The invention is further described below by means of specific embodiments.
FIG. 1 shows a tracking and obstacle avoidance weighting system for a mobile robot with a fuzzy controller output v1、w1The output of the trajectory tracking controller is v2、w2And weighting and summing the two outputs to obtain a control quantity v of the advancing speed and the steering angular speed of the wheeled mobile robotc、wcTo adjust a series of motion forms of the robot. When the front side has no obstacle, the robot can track the movement of the reference track curve, when the front side has the obstacle, the robot can avoid automatically, and the robot continues to track the reference track curve after avoiding.
Fig. 2 shows that when the situation of an obstacle is complex or the time for the robot to complete obstacle avoidance is long, the reference robot is excessively far away, the current position of the robot and the position of the reference robot form a large error, which results in that the current robot performs track tracking at the fastest speed, and the track tracking motion with the error reduced is not on the reference track curve.
FIG. 3 shows the relative positions of the current robot and the reference robot when θ△At an obtuse angle (theta)△∈(π/2,π]) Should let the reference robot slow down waiting for the current robot when theta△At acute or right angles (theta)△∈[0,π/2]) The reference robot should be allowed to accelerate at this time.
FIG. 4 shows the equation when d△>>d0And theta△In the case of a pi/2 approach, the reference robot should keep the original birthTo speed, the time scale should not be changed excessively at this time.
Fig. 5 shows a situation of a concave special obstacle encountered in the trajectory tracking process, and at this time, if the reference robot position has an obtuse angle for a long time and the reference time node moves backward too much, a dead zone is formed, and the robot cannot bypass the obstacle.
A mobile robot obstacle avoidance method based on self-adaptive gravity comprises the following processes:
step 1) establishing an expression of a reference trajectory curve
The generation of the dynamic track is changed, and firstly, an expression of a reference track curve needs to be established. The reference trajectory curve in the trajectory tracking process is generally a time-dependent function, and the speed of the generation of the reference trajectory curve can be dynamically changed by changing the time scale or the node. The expression of the trajectory curve is shown below
(xr,yr) Is the expected position coordinate of the reference robot in a world coordinate system, fx fyThe trajectory functions are respectively of an x axis and a y axis.
Step 2) self-adaptive gravity design to obtain self-adaptive gravity value
(1) When the obstacle is complex and the robot obstacle avoidance time is long, the reference robot is excessively far away from the current robot. At the moment, the connecting line of the two robots forms an included angle theta with the orientation of the reference robot△At an obtuse angle (theta)△∈(π/2,π]) An attractive force is required to slow down the generation speed of the reference track, and an attractive force F is introduced by changing the time scale or the node of the reference track generationaActing on a time scale and the distance d of the robot from the reference robot△The farther away the attractive force FaThe larger. Attractive force FaAnd d△Can be considered as
In the formula ksIs a coefficient of gravity, d0For minimum gravitational distance, only when d△>d0Only then the attractive force F needs to be changedaThe size of (2). But when d is△>>d0And theta△In the case of a near pi/2, the reference robot should not be slowed down and the original generation speed should be maintained. Thus, the formula (2) is modified
When theta is△In the case of approaching pi/2, d can be weakened△Attraction force FaThe influence of (c).
(2) When theta is△At acute or right angles (theta)△∈[0,π/2]) The reference trajectory curve should be generated faster, and an attractive force F is introducedbOn varying the time scale of reference trajectory generation, likewise d△The farther away the attractive force FbThe larger. Attractive force FbAnd d△Can be considered as
In conclusion, for the obstacle avoidance problem in the process of tracking the reference track curve by the robot, the adaptive gravity F of the mobile robot obstacle avoidance method based on the adaptive gravity takes the value as
Step 3) acting the gravitation on a time scale to obtain a reference track curve based on the gravitation
In practical application, the generated expression of the trajectory curve is generally in a discrete form, and the gravitation can be acted on a time step T, wherein a time scale coefficient k is introducedt，
The expression generated with reference to the trajectory curve is
Step 4) tracking and obstacle avoidance weighting system
The tracking and obstacle avoidance weighting system considered by the invention is to output v of the fuzzy controller1、w1And the output v of the trajectory tracking controller2、w2Weighted summation is used as control quantity v of forward speed and steering angular speed of wheeled mobile robotc、wc. And introducing a weighting coefficient lambda, then
In the formula dminFor the minimum of the distances to the obstacle measured in the three regions, b3Third level distance, d, being the fuzzy controller distance scale levelmin∈[0,b3]Thus λ ∈ [0,1 ]]。
It is easy to know that d is the time when the robot does not detect an obstacle during trajectory trackingmin＝b3When the robot detects an obstacle and is in close proximity, λ is small, and the control amount of the robot is largely determined by the output of the fuzzy controller. Therefore, the purpose that the robot avoids obstacles indiscriminately is avoided, the robot can move close to the reference track curve as much as possible while bypassing the obstacles, and the energy consumption of the robot is reduced.
Example one
The reference track curve is a straight line or a round reference track
Step 1) Generation of an expression of a reference trajectory Curve
The reference trajectory curve of straight lines and circles can be generally defined by a reference speed vrReference steering speed wrAnd initial position posture q of reference robot0(xr(1),yr(1),θr(1) Produced, the discrete form of the trajectory curve generation is shown below
Wherein (x)r,yr) Is the expected position coordinate of the reference robot in a world coordinate system thetarReference to the angle between the orientation of the robot and the X-direction of the world coordinate system, [ X ]r yr θr]TIs the position and attitude of the reference robot, vr、wrReference is made to the forward speed and steering speed of the robot, respectively. Straight and circular mid vrAnd wrAre all constant, and the speed of the generation of the reference track curve can be changed by changing the time step T.
Step 2) self-adaptive gravity design to obtain a self-adaptive gravity value
(1) When the obstacle is complex and the robot obstacle avoidance time is long, the reference robot is excessively far away from the current robot. At the moment, the connecting line of the two robots forms an included angle theta with the orientation of the reference robot△At an obtuse angle (theta)△∈(π/2,π]) An attractive force is required to slow down the generation speed of the reference track, and an attractive force F is introduced by changing the time scale or the node of the reference track generationaActing on a time scale and the distance d of the robot from the reference robot△The farther away the attractive force FaThe larger. Attractive force FaAnd d△Can be considered as
In the formula ksIs a coefficient of gravity, d0Is a minimum leadDistance of force only when d△>d0Only then the attractive force F needs to be changedaThe size of (2). But when d is△>>d0And theta△In the case of a near pi/2, the reference robot should not be slowed down and the original generation speed should be maintained. Thus, the formula (2) is modified
When theta is△In the case of approaching pi/2, d can be weakened△Attraction force FaThe influence of (c).
(2) When theta is△At acute or right angles (theta)△∈[0,π/2]) It is desirable to have the reference trajectory curve generated at an increased speed, where an attractive force F is introducedbOn varying the time scale of reference trajectory generation, likewise d△The farther away the attractive force FbThe larger. Attractive force FbAnd d△Can be considered as
In conclusion, for the obstacle avoidance problem in the process of tracking the reference track curve by the robot, the adaptive gravity F of the obstacle avoidance method of the mobile robot based on the adaptive gravity takes the value as
Step 3) acting the gravitation on a time scale to obtain a reference track curve based on the gravitation
In practical application, the generated expression of the trajectory curve is generally in a discrete form, and the gravitation can be acted on a time step T, wherein a time scale coefficient k is introducedt
Then the generation mode of the straight line and circular track curve dynamic track based on the gravity is as follows:
step 4) tracking and obstacle avoidance weighting system
The tracking and obstacle avoidance weighting system considered by the invention is to output v of the fuzzy controller1、w1And the output v of the trajectory tracking controller2、w2Weighted summation is used as control quantity v of advancing speed and steering angular speed of wheeled mobile robotc、wc. And introducing a weighting coefficient lambda, then
In the formula dminFor the minimum of the distances to the obstacle measured in the three regions, b3Third level distance, d, being the fuzzy controller distance scale levelmin∈[0,b3]Thus λ ∈ [0,1 ]]。
It is easy to know that d is the time when the robot does not detect an obstacle during trajectory trackingmin＝b3When the robot detects an obstacle and is in close proximity, λ is small, and the control amount of the robot is largely determined by the output of the fuzzy controller. Therefore, the purpose that the robot avoids obstacles indiscriminately is avoided, the robot can move close to the reference track curve as much as possible while bypassing the obstacles, and the energy consumption of the robot is reduced.
Example two
The reference track curve is a curved reference track
Step 1) Generation of an expression of a trajectory Curve
The curve reference track is generated in a mode of a function of coordinates x and y with respect to time, and the discrete form of track curve generation is as follows
Wherein v isx、vyRespectively, the projection of the forward speed of the reference robot on the X-axis and the Y-axis of the coordinate system, the forward speed and the steering speed of the reference robot are then of the order of magnitude
Therefore, the speed of generation of the reference trajectory curve can be changed by changing the time node j.
Step 2) self-adaptive gravity design to obtain the value of self-adaptive gravity F
1) When theta is△At an obtuse angle (theta)△∈(π/2,π]) When the temperature of the water is higher than the set temperature,
then pair ktTake the integer kt＝-round(F)
j＝j+kt (12)
However, in consideration of the situation of the special obstacle, for the concave obstacle, if the reference robot position has an obtuse angle for a long time and the reference time node moves backwards too much, a dead zone is formed, and the robot cannot bypass the obstacle. Therefore, the reference time node is left to wait, F is 1, and the reference trajectory stops being generated.
j＝j-1 (13)
2) When theta is△At acute or right angles (theta)△∈[0,π/2]) When the temperature of the water is higher than the set temperature,
then to ktTake an integer, kt＝round(F)
j＝j+kt (15)
When d is△<d0When F is equal to 0
j＝j (16)
In conclusion, for the obstacle avoidance problem in the process of tracking the reference track curve by the robot, the adaptive gravity F of the mobile robot obstacle avoidance method based on the adaptive gravity is valued as
Step 3) acting the gravitation on a time scale to obtain a reference track curve based on the gravitation
In practical application, the generated expression of the curve track curve is generally in a functional form, the gravitation can be acted on a time node j, and a time node coefficient k is introducedtTime node coefficient k for dynamic reference trajectory generationtTake a value of
kt＝round(F) (18)
Then, the method for generating the dynamic trajectory of the curve reference trajectory based on the gravity is as follows:
step 4) tracking and obstacle avoidance weighting system
The tracking and obstacle avoidance weighting system considered by the invention is to output v of the fuzzy controller1、w1And the output v of the trajectory tracking controller2、w2Weighted summation is used as control quantity v of advancing speed and steering angular speed of wheeled mobile robotc、wc. And introducing a weighting coefficient lambda, then
In the formula dminFor measuring obstacles in three regionsMinimum value of distance, b3Third level distance, d, being the fuzzy controller distance scale levelmin∈[0,b3]Thus λ ∈ [0,1 ]]。
It is known that when the robot does not detect an obstacle during trajectory tracking, dmin＝b3When the robot detects an obstacle and is in close proximity, λ is small, and the control amount of the robot is largely determined by the output of the fuzzy controller. Therefore, the purpose that the robot avoids obstacles indiscriminately is avoided, the robot can move close to the reference track curve as much as possible while bypassing the obstacles, and the energy consumption of the robot is reduced.
Simulation verification
The track tracking and autonomous obstacle avoidance simulation of the wheeled mobile robot is built in an MATLAB environment, as shown in figure 1, the robot can track a dynamically generated reference track curve, the robot can detect the distance and direction information of an obstacle when the robot meets the obstacle, autonomous obstacle avoidance is carried out by using a fuzzy control algorithm, and the reference track curve is continuously tracked after obstacle avoidance is finished. And (3) performing simulation analysis on the autonomous obstacle avoidance of the reference track curve under the following conditions respectively:
(1) circular reference trajectory curve
As shown in fig. 6, a red curve is a reference track, coordinates of a start point are (0,0), an initial angle is 0, coordinates of a start point of a robot are (0, -0.2), and an initial angle is 0, it can be seen from the figure that the robot firstly tracks the reference track, and a pose error of the reference robot rapidly converges to 0.
When the dynamic reference track generation method based on the gravitation is applied, in the process of carrying out an obstacle avoidance task by the robot, the speed of reference track generation is dynamically changed according to the relative position information of the current robot and the reference robot, and the reference robot is prevented from excessively leaving the current robot position, so that the robot can quickly return to the reference track curve after finishing obstacle avoidance, as shown in fig. 7.
(2) Curve reference trajectory curve
Assuming that the curve reference trajectory curve is generated by the formula
When the obstacle is complex and the robot needs a long time to complete the obstacle avoidance task, if the processing of generating the reference track in the robot obstacle avoidance process is not considered, the tracking obstacle avoidance effect is as shown in fig. 8. When the dynamic reference track generation method based on the gravity is applied, the time node generated by the reference track is dynamically changed in the process of the robot performing the obstacle avoidance task, and the tracking effect is as shown in fig. 9.
The above description is only an embodiment of the present invention, but the design concept of the present invention is not limited thereto, and any insubstantial modifications made by using the design concept should fall within the scope of infringing the present invention.
Claims (3)
1. A mobile robot obstacle avoidance method based on self-adaptive gravity is characterized by comprising the following steps:
step 1) establishing an expression of a reference track curve;
step 2) self-adaptive gravity design, and obtaining a self-adaptive gravity value as
Wherein theta is△An angle formed by the connection line of the two robots and the orientation of the reference robot, d△Distance of the robot from the reference robot, ksIs a coefficient of gravity, d0Is the minimum gravitational distance;
step 3) making the self-adaptive attraction forceThe method is used on a time scale to obtain a gravity-based reference track curve, and specifically comprises the following steps: applying self-adaptive gravity on time step T, and introducing a time scale coefficient kt，
The expression generated with reference to the trajectory curve is
Wherein: (x)r,yr) Is the expected position coordinate of the reference robot in a world coordinate system, fx fyRespectively are track functions of an x axis and a y axis;
step 4) determining the output of the fuzzy controller through a reference track curve; when the robot does not detect an obstacle in the process of tracking the track, the control quantity of the robot is determined by the output of the track tracking controller, and when the robot detects the obstacle and is close to the obstacle, the control quantity of the current robot is mostly determined by the output of the fuzzy controller.
2. The adaptive gravity-based obstacle avoidance method for the mobile robot as claimed in claim 1, wherein the reference trajectory curve comprises a straight line or a circle or a curve.
3. The obstacle avoidance method of the mobile robot based on the adaptive gravitation as claimed in claim 1, wherein: the step 4) is specifically as follows: output v of the fuzzy controller1、w1And the output v of the trajectory tracking controller2、w2Weighted summation as control quantity v of forward speed and steering angular speed of robotc、wc(ii) a And introducing a weighting coefficient lambda, then
In the formula dmin∈[0,b3]，b3A third level distance which is a distance scale level of the fuzzy controller;
d when the robot does not detect an obstacle during trajectory trackingmin＝b3λ is 1, and the control amount of the robot is determined by the output of the trajectory tracking controller; when the robot detects an obstacle and is in close proximity, the amount of control is largely determined by the output of the fuzzy controller.
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