CN104007762A - Navigation method of electric power inspection robot - Google Patents

Abstract

The invention provides a navigation method of an electric power inspection robot. The navigation method comprises the steps that a fuzzy controller for movement of the electric power inspection robot is established, and the input variable and the output variable of the fuzzy controller are determined; a fuzzy set of the input variable and the output variable is set, and a fuzzy set of the acceptance level of the output variable is set; a qualitative reasoning principle is determined according to a fuzzy control theory, and a fuzzy control rule is established according to the input variable and the output variable of the fuzzy controller; the subordinating degree function of the input variable and the output variable is established; voting is conducted according to a subordinating degree function maximum principle, corresponding action is conducted on the electric power inspection robot, and navigation to the electric power inspection robot is achieved. A practicable navigation method can be provided for the electric power inspection robot, and the obstacle avoidance rate of the electric power inspection robot can be improved.

Description

The air navigation aid of a kind of electric inspection process robot

Technical field

The present invention relates to a kind of air navigation aid, in particular for the air navigation aid of electric inspection process robot.

Background technology

Navigation is indispensable important component part in mobile robot's autonomous intelligence, and it requires robot according to the instruction and the autonomous decision path of environmental information that give, and avoiding obstacles, realizes task object.Navigation is the safety guarantee that mobile robot finishes the work, also be the important symbol of the intelligent degree of mobile robot simultaneously, especially in the situation that the precision of robot hardware's system can not be resolved in a short time, the research of navigation algorithm is more seemed to particularly important, this will fundamentally change mobile robot's navigation performance, mobile robot's intellectual level will be improved, reduce the nondeterministic statement that mobile robot exists in moving process, improve speed and activity that mobile robot moves, for developing the remote transfer robot of high intelligence, sniffing robot, service robot, automatic vehicle control system lays the first stone.

And Robotics is applied in power industry, task completes speed efficiently, efficiently both can to have utilized robot, can also solve the problem that cost of human resources goes up at a high speed.Utilize crusing robot on transmission line of electricity, to carry out robotization inspection, not only can be applied in that some natural conditions are relatively severe, the mankind cannot or the immalleable area of the mankind, can also high reliability complete complicated work.In addition, utilize some special sensing equipments, can find the incipient fault that common patrol officer cannot find, for preventing and solve the fault of power circuit and reducing the road that risk has been pointed out a novelty.

But for crusing robot, patrol and examine in process and will run into various barriers, how effectively to avoid these barriers, also there is no at present a kind of practicable air navigation aid.

Summary of the invention

The technical problem to be solved in the present invention is to provide a kind of air navigation aid of effectively keeping away the electric inspection process robot that barrier rate is high.

In order to solve the problems of the technologies described above, the invention provides the air navigation aid of a kind of electric inspection process robot, comprise the steps:

Step 1, sets up electric inspection process robot motion's fuzzy controller, and the input variable of definite fuzzy controller and output variable, and concrete steps are:

(1-1) scope of electric inspection process robot the place ahead 180 degree is divided into dead ahead, left front and right front three parts, by sensor, measure respectively the obstacle information of 3 directions, be dead ahead obstacle information F, left front obstacle information L and right front obstacle information R, and as the input variable of fuzzy controller;

(1-2) set up electric inspection process robot and the straight line path of patrolling and examining impact point, and the relative angle θ between straight line path and the working direction of electric inspection process robot is as the input variable of fuzzy controller;

(1-3) by next step steering angle of electric inspection process robot output variable as fuzzy controller;

Step 2, sets the fuzzy set of input variable and output variable, and sets the fuzzy set of the acceptance level of output variable, and concrete steps are:

(2-1) setting dead ahead obstacle information F, left front obstacle information L and this each self-corresponding fuzzy set of three input variables of right front obstacle information R is all small distance s, middle distance m and greatly apart from l;

(2-2) fuzzy set of setting relative angle θ is honest PL, just little PS, zero Z, negative little NS and negative large NL;

(2-3) set steering angle fuzzy subset be large right-hand rotation RLT, right-hand rotation RT, do not turn NT, left-hand rotation LT and the LLT that turns left greatly;

(2-4) set steering angle acceptance level α _ifuzzy subset, α _i=1 represents not allow, α _i=2 represent neutrality, α _i=3 represent to allow, acceptance level α _ithe degree that is allowed to more greatly or accepts is higher, wherein, i=1,2,3,4,5, respectively corresponding large right-hand rotation RLT, right-hand rotation RT, do not turn NT, left-hand rotation LT and the LLT that turns left greatly;

Step 3, establishes qualitative reasoning principle according to fuzzy control theory, according to the input variable of dimmed controller and output variable, sets up fuzzy control rule, and concrete steps are:

(3-1) determine that keeping away of dead ahead, left front and right front hinders rule, because dead ahead obstacle information F, left front obstacle information L and right front obstacle information R are to having three fuzzy subset s, m and l, F, L and fuzzy subset corresponding to R are carried out to permutation and combination, have 3 ³=27 rules, every rule is all corresponding to the acceptance level α of these five actions of RLT, RT, NT, LT and LLT _i;

(3-2) determine the barrier rule of keeping away of relative angle, because relative angle θ is to having five fuzzy subset PL, PS, Z, NS and NL, have 5 rules, every rule is all corresponding to the acceptance level α of these five actions of RLT, RT, NT, LT and LLT _i;

Step 4, determines the membership function of input language variable and output language variable, and concrete steps are:

(4-1) domain using dead ahead obstacle information F, left front obstacle information L and right front obstacle information R as degree of membership respectively, determines the membership function of dead ahead obstacle information F, left front obstacle information L and right front obstacle information R;

(4-2) domain using relative angle θ as degree of membership, determines the membership function of relative angle θ;

(4-3) by steering angle as the domain of degree of membership, determine steering angle membership function;

Step 5, carries out defuzzification, according to maximum membership degree method, puts to the vote, and electric inspection process robot is carried out to corresponding actions, completes the navigation of electric inspection process robot, and concrete steps are:

(5-1) according to maximum membership degree method, put to the vote, obtain steering angle clear amount;

(5-2) by the steering angle obtaining clear amount carry out yardstick conversion, obtain electric inspection process robot actual be used for action steering angle be the angle that electric inspection process robot is about to need adjustment, complete the navigation of electric inspection process robot.

As further restriction scheme of the present invention, the range information that obstacle information is barrier.

Beneficial effect of the present invention is: the method that adopts fuzzy controller, not only can provide a kind of practicable air navigation aid for electric inspection process robot, and adopt fuzzy controller to be optimized guidance path, improve the barrier ability of keeping away of electric inspection process robot.

Accompanying drawing explanation

Fig. 1 is method flow diagram of the present invention;

Fig. 2 is three direction obstacle information degree of membership schematic diagram of the present invention;

Fig. 3 is relative angle degree of membership schematic diagram of the present invention;

Fig. 4 is steering angle degree of membership schematic diagram of the present invention.

Embodiment

As shown in Figure 1, the air navigation aid of electric inspection process of the present invention robot, comprises the steps:

Step 1, sets up electric inspection process robot motion's fuzzy controller, and the input variable of definite fuzzy controller and output variable, and concrete steps are:

(1-1) scope of electric inspection process robot the place ahead 180 degree is divided into dead ahead, left front and right front three parts, by sensor, measure respectively the obstacle information of 3 directions, be dead ahead obstacle information F, left front obstacle information L and right front obstacle information R, when actual acquisition, can adopt range sensor to gather dead ahead obstacle distance, left front obstacle distance and right front obstacle distance, the input variable using dead ahead obstacle distance, left front obstacle distance and right front obstacle distance as fuzzy controller;

(1-2) set up electric inspection process robot and the straight line path of patrolling and examining impact point, and the relative angle θ between straight line path and the working direction of electric inspection process robot is as the input variable of fuzzy controller;

(1-3) by next step steering angle of electric inspection process robot output variable as fuzzy controller;

Step 2, sets the fuzzy set of input variable and output variable, and sets the fuzzy set of the acceptance level of output variable, and concrete steps are:

(2-1) setting dead ahead obstacle information F, left front obstacle information L and this each self-corresponding fuzzy set of three input variables of right front obstacle information R is all small distance s, middle distance m and greatly apart from l;

(2-2) fuzzy set of setting relative angle θ is honest PL, just little PS, zero Z, negative little NS and negative large NL;

(2-3) set steering angle fuzzy subset be large right-hand rotation RLT, right-hand rotation RT, do not turn NT, left-hand rotation LT and the LLT that turns left greatly;

(2-4) set steering angle acceptance level α _ifuzzy subset, α _i=1 represents not allow, α _i=2 represent neutrality, α _i=3 represent to allow, acceptance level α _ithe degree that is allowed to more greatly or accepts is higher, wherein, i=1,2,3,4,5, represent respectively RLT, RT, NT, LT and LLT;

Step 3, establishes qualitative reasoning principle according to fuzzy control theory, according to the input variable of dimmed controller and output variable, sets up fuzzy control rule, and concrete steps are:

(3-1) determine that keeping away of dead ahead, left front and right front hinders rule, because dead ahead obstacle information F, left front obstacle information L and right front obstacle information R are to having three fuzzy subset s, m and l, F, L and fuzzy subset corresponding to R are carried out to permutation and combination, have 3 ³=27 rules, every rule is all corresponding to the acceptance level α of these five actions of RLT, RT, NT, LT and LLT _i, for example, if { L=l, F=m, R=s}, { α ₁=3, α ₂=2, α ₃=1, α ₄=1, α ₅=1};

(3-2) determine the barrier rule of keeping away of relative angle, because relative angle θ is to having five fuzzy subset PL, PS, Z, NS and NL, have 5 rules, every rule is all corresponding to the acceptance level α of these five actions of RLT, RT, NT, LT and LLT _i, for example, if { θ=PS}, { α ₁=2, α ₂=3, α ₃=2, α ₄=1, α ₅=1};

Step 4, determines the membership function of input language variable and output language variable, and concrete steps are:

(4-1) domain using dead ahead obstacle information F, left front obstacle information L and right front obstacle information R as degree of membership respectively, determine the membership function of dead ahead obstacle information F, left front obstacle information L and right front obstacle information R, as shown in Figure 2, because F, L and R have l, m and tri-fuzzy variables of s, wherein the value of s is $s=\left\{\begin{array}{c}1.0,x\∈[\mathrm{0,1})\\ 2-x,x\∈[\mathrm{1,2})\end{array}\right.,$ The value of m is $m=\left\{\begin{array}{c}x-1,x\∈[1,2)\\ 3-x,x\∈[2,3)\end{array}\right.,$ The value of l is $l=\left\{\begin{array}{c}x-2,x\∈\left[\mathrm{2,3}\right)\\ 1.0,x\∈[3,\∞)\end{array}\right.,$ X represents the size of the value of F, L or R, the value of working as F, L and R is [0,1) when interior, F, L and R are under the jurisdiction of the degree maximum of s, when the value of F, L and R is [1,2) while increasing in, the degree that F, L and R are under the jurisdiction of s reduces gradually, and the degree that is under the jurisdiction of m is increasing gradually, when the value of F, L and R is [2,3) while increasing in, the degree that F, L and R are under the jurisdiction of m reduces gradually, and the degree that is under the jurisdiction of l is increasing gradually, when the value of F, L and R is [3, while increasing ∞), F, L and R are under the jurisdiction of the degree maximum of l;

(4-2) domain using relative angle θ as degree of membership, determines the membership function of relative angle θ, and as shown in Figure 3, relative angle θ has NL, NS, Z, PS and five fuzzy variables of PL, and wherein the value of NL is $\mathrm{NL}=\left\{\begin{array}{c}1.0,y\∈(-\∞,-\frac{\mathrm{\π}}{2})\\ -\frac{4}{\mathrm{\π}}y-1,y\∈[-\frac{\mathrm{\π}}{2},-\frac{\mathrm{\π}}{4})\end{array}\right.,$ The value of NS is $\mathrm{NS}=\left\{\begin{array}{c}\frac{4}{\mathrm{\π}}y+2,y\∈[-\frac{\mathrm{\π}}{2},-\frac{\mathrm{\π}}{4})\\ -\frac{4}{\mathrm{\π}}y,y\∈[-\frac{\mathrm{\π}}{4},0)\end{array}\right.\text{,}$ The value of Z is $Z=\left\{\begin{array}{c}\frac{4}{\mathrm{\π}}y+1,y\∈[-\frac{\mathrm{\π}}{4},0)\\ -\frac{4}{\mathrm{\π}}y+1,y\∈[0,\frac{\mathrm{\π}}{4})\end{array}\right.,$ The value of PS is $\mathrm{PS}=\left\{\begin{array}{c}\frac{4}{\mathrm{\π}}y,y\∈[0,\frac{\mathrm{\π}}{4})\\ -\frac{4}{\mathrm{\π}}y+2,y\∈[\frac{\mathrm{\π}}{4},\frac{\mathrm{\π}}{2})\end{array}\right.,$ The value of PL is $\mathrm{PL}=\left\{\begin{array}{c}\frac{4}{\mathrm{\π}}y-1,y\∈[\frac{\mathrm{\π}}{4},\frac{\mathrm{\π}}{2})\\ 1.0,y\∈[\frac{\mathrm{\π}}{2},+\∞)\end{array}\right.,$ Y represents the size of the value of θ, and the value as θ exists when interior, it is maximum that θ is under the jurisdiction of the degree of NL, when the value of θ exists during interior increase, the degree that θ is under the jurisdiction of NL reduces gradually, and the degree that is under the jurisdiction of NS increases gradually, when the value of θ exists during interior increase, the degree that θ is under the jurisdiction of NS reduces gradually, and the degree that is under the jurisdiction of Z increases gradually, when the value of θ exists during interior increase, the degree that θ is under the jurisdiction of Z reduces gradually, and the degree that is under the jurisdiction of PS increases gradually, when the value of θ exists during interior increase, the degree that θ is under the jurisdiction of PS reduces gradually, and the degree that is under the jurisdiction of PL increases gradually, when the value of θ exists during interior increase, θ is under the jurisdiction of the degree maximum of PL;

(4-3) by steering angle as the domain of degree of membership, determine steering angle membership function, as shown in Figure 4, steering angle have LLT, LT, NT, RT and five fuzzy variables of RLT, wherein the value of LLT is LLT=-2z-1, and z ∈ [1 ,-0., 5) value of LT is .NT value is the value of RT is the value of RLT is RLT=2z-1, z ∈ [0.5,1], and z represents steering angle the size of quantized value, when quantized value value [1 ,-0.5) in while increasing, the degree that is under the jurisdiction of LLT reduces gradually, and the degree that is under the jurisdiction of LT increases gradually, when quantized value value [0.5,0) in while increasing, the degree that is under the jurisdiction of LT reduces gradually, and the degree that is under the jurisdiction of NT increases gradually, when quantized value value [0,0.5) in while increasing, the degree that is under the jurisdiction of NT reduces gradually, and the degree that is under the jurisdiction of RT increases gradually, when quantized value value while increasing in [0.5,1], the degree that is under the jurisdiction of RT reduces gradually, and the degree that is under the jurisdiction of RLT increases gradually;

Step 5, carries out defuzzification to each fuzzy variable, according to maximum membership degree method, puts to the vote, and electric inspection process robot is carried out to corresponding actions, completes the navigation of electric inspection process robot, and concrete steps are:

(5-1) according to maximum membership degree method, put to the vote, obtain steering angle clear amount;

(5-2) by the steering angle obtaining clear amount carry out yardstick conversion, obtain electric inspection process robot actual be used for action steering angle be the angle that electric inspection process robot is about to need adjustment, complete the navigation of electric inspection process robot.

Membership function of the present invention is determined all and is determined in conjunction with method experience of the present invention according to existing membership function theoretical method.

Claims (2)

1. The air navigation aid of 1.Yi Zhong electric inspection process robot, is characterized in that, comprises the steps:

   Step 1, sets up electric inspection process robot motion's fuzzy controller, and the input variable of definite fuzzy controller and output variable, and concrete steps are:

   (1-1) scope of electric inspection process robot the place ahead 180 degree is divided into dead ahead, left front and right front three parts, by sensor, measure respectively the obstacle information of 3 directions, be dead ahead obstacle information F, left front obstacle information L and right front obstacle information R, and as the input variable of fuzzy controller;

   (1-2) set up electric inspection process robot and the straight line path of patrolling and examining impact point, and the relative angle θ between straight line path and the working direction of electric inspection process robot is as the input variable of fuzzy controller;

   (1-3) by next step steering angle of electric inspection process robot output variable as fuzzy controller;

   Step 2, sets the fuzzy set of input variable and output variable, and sets the fuzzy set of the acceptance level of output variable, and concrete steps are:

   (2-1) setting dead ahead obstacle information F, left front obstacle information L and this each self-corresponding fuzzy set of three input variables of right front obstacle information R is all small distance s, middle distance m and greatly apart from l;

   (2-2) fuzzy set of setting relative angle θ is honest PL, just little PS, zero Z, negative little NS and negative large NL;

   (2-3) set steering angle fuzzy subset be large right-hand rotation RLT, right-hand rotation RT, do not turn NT, left-hand rotation LT and the LLT that turns left greatly;

   (2-4) set steering angle acceptance level α _ifuzzy subset, α _i=1 represents not allow, α _i=2 represent neutrality, α _i=3 represent to allow, acceptance level α _ithe degree that is allowed to more greatly or accepts is higher, wherein, i=1,2,3,4,5, respectively corresponding large right-hand rotation RLT, right-hand rotation RT, do not turn NT, left-hand rotation LT and the LLT that turns left greatly;

   Step 3, establishes qualitative reasoning principle according to fuzzy control theory, according to the input variable of dimmed controller and output variable, sets up fuzzy control rule, and concrete steps are:

   (3-1) determine that keeping away of dead ahead, left front and right front hinders rule, because dead ahead obstacle information F, left front obstacle information L and right front obstacle information R are to having three fuzzy subset s, m and l, F, L and fuzzy subset corresponding to R are carried out to permutation and combination, have 3 ³=27 rules, every rule is all corresponding to the acceptance level α of these five actions of RLT, RT, NT, LT and LLT _i;

   (3-2) determine the barrier rule of keeping away of relative angle, because relative angle θ is to having five fuzzy subset PL, PS, Z, NS and NL, have 5 rules, every rule is all corresponding to the acceptance level α of these five actions of RLT, RT, NT, LT and LLT _i;

   Step 4, determines the membership function of input language variable and output language variable, and concrete steps are:

   (4-1) domain using dead ahead obstacle information F, left front obstacle information L and right front obstacle information R as degree of membership respectively, determines the membership function of dead ahead obstacle information F, left front obstacle information L and right front obstacle information R;

   (4-2) domain using relative angle θ as degree of membership, determines the membership function of relative angle θ;

   (4-3) by steering angle as the domain of degree of membership, determine steering angle membership function;

   Step 5, carries out defuzzification, according to maximum membership degree method, puts to the vote, and electric inspection process robot is carried out to corresponding actions, completes the navigation of electric inspection process robot, and concrete steps are:

   (5-1) according to maximum membership degree method, put to the vote, obtain steering angle clear amount;

   (5-2) by the steering angle obtaining clear amount carry out yardstick conversion, obtain electric inspection process robot actual be used for action steering angle be the angle that electric inspection process robot is about to need adjustment, complete the navigation of electric inspection process robot.
2. 2. the air navigation aid of electric inspection process according to claim 1 robot, is characterized in that: the range information that described obstacle information is barrier.