CN103699136A - Intelligent household service robot system and service method based on leapfrogging algorithm - Google Patents

Abstract

The invention provides an intelligent household service robot system and a service method based on a leapfrogging algorithm. The method is characterized by comprising the following steps of a robot receives a command from a service object by utilizing a voice recognition module or a wireless communication module, determines a to-be-extracted target and the position of the service object, and locates the target and the service object by utilizing an environment map; the rotor makes a route planning of the robot by utilizing the leapfrogging algorithm according to the environmental map, and calculates all optimal position points through which the robot passes from the current position of the robot to the target and controls a motor controller to drive the robot to move forwards; a mechanical hand is driven to move to a target position to grab the target when the robot arrives in the target, the robot automatically moves to the service object, and completes the service work. The intelligent household service robot system is simple in structure and good in intellectuality and flexibility, the operation time and the storage quantity can be saved, the route planning accuracy of the robot can be improved, and the working efficiency of the household service robot can be improved.

Description

Intelligent home service robot system and method for servicing based on the algorithm that leapfrogs

Technical field

The present invention relates to home services robot, belong to the path planning field of robot in circumstances not known, is the application that Robotics combines with swarm intelligence technology, particularly the Intelligent home service robot system and method based on the algorithm that leapfrogs.

Background technology

Along with the development of service robot technology and domestic. applications science and technology, home services robot more and more receives people's concern, also more and more presses close to daily life, has broad application prospects.

In the research of mobile robot's correlation technique, path planning is an important step and key subject, is the hot issue of mobile robot's research field, is also a problem very with challenge in Mobile Robotics Navigation simultaneously.At present, the method for path planning has a variety of, such as Artificial Potential Field Method, genetic algorithm, neural network, ant group algorithm etc.But there are several large defects in traditional Artificial Potential Field Method: has trap district; Between close barrier, can not find path; In slype, swing; When there is barrier impact point vicinity, robot cannot arrive impact point; Genetic algorithm has good ability of searching optimum, but arithmetic speed slow, occupy storage space and greatly, be easily absorbed in the shortcomings such as precocious; Neural network has good learning ability, but when barrier is more and environment is dynamic, the huge and neuronic threshold value of network structure need to constantly change over time; Ant group algorithm speed of convergence is slow, is easily absorbed in local optimum.

The algorithm (SFLA) that leapfrogs is a kind of Meta-heuristics collaboratively searching swarm intelligence algorithm based on colony that the people such as Eusuff proposed in 2003.This algorithm combines mould because of the advantage of algorithm and particle swarm optimization algorithm.The algorithm application that leapfrogs, it on path planning, is a new trial.By imitating the behavior of frog predation, can make robot find a path that arrives target, but this algorithm is easily absorbed in local optimum.

Summary of the invention

The invention provides a kind of Intelligent home service robot system and method based on the algorithm that leapfrogs.To indoor environment information obtain with process after, adopt the improved algorithm that leapfrogs to carry out path planning to robot, make robot after receiving command adapted thereto, can oneself cook up an avoiding obstacles and arrive target location, capture the needed target of service object, and deliver in service object's hand, finish the work.

The technical scheme that the present invention realizes foregoing invention object is: the Intelligent home service robot system based on the algorithm that leapfrogs, is characterized in that: comprise

The one left and right robot that drives walking of taking turns by controlled motion, robot has the mechanical arm being driven by motor driver;

Described robot front end carries airborne camera, for scanning the elevation information of target object;

Described robot dead ahead arranges one or more ultrasonic sensors, is used for the barrier that sniffing robot advances in process;

Described robot receives service object's instruction by wireless communication module or sound identification module, determine target;

Also comprise that one is arranged on indoor roof for taking the camera of indoor environment picture, camera sends to robot by Wi-Fi by the picture of shooting; After robot processes picture, set up indoor grille map, and carry out target, service object and robot self-position and locate, then by the improved algorithm that leapfrogs, carry out path planning, according to the barrier, target location and the self-position that calculate optimum position that robot will pass through and robot probe and arrive, calculate the angular velocity of the left and right wheels of robot, control arrives impact point place.

2. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs, is characterized in that: comprise the steps:

(1) robot carries memory device, ultrasonic sensor, airborne camera, sound identification module, wireless communication module, motor driver and mechanical arm;

(2) camera of being installed by indoor roof obtains indoor environment image, and sends and to process to robot, sets up environmental map, completes robot initial position location;

(3) robot sets up displacement and learns model, and its motion state variable is (x, y, θ) ^t, wherein (x, y) is the coordinate of robot in plane coordinate system, the deflection that θWei robot advances;

(4) robot utilizes sound identification module or wireless communication module to receive the instruction from service object, determines and needs the target of crawl and service object's position, and utilize environmental map to carry out target and service object location;

(5) robot, according to environmental map, utilizes the path planning of the improved algorithmization robot that leapfrogs, and calculates all optimum positions point that will pass through from robot current location to target;

(6) robot, according to displacement model and the next optimum position point that will arrive, calculates its left and right angular velocity of taking turns, and controls motor driver drive machines people and travels forward;

(7) robot judges whether to arrive target, if do not return to step (6), if arrive target, utilizes airborne camera to carry out stereoscanning, obtains target vertical height overhead, and driving device hands movement captures target to target location;

(8) robot captures after target, automatically runs to service object place, completes services.

3. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 1, it is characterized in that: described step (2) indoor roof is provided with camera indoor environment image is obtained, and transmission is processed to robot, set up environmental map, complete robot initial position location and refer to:

(2a) indoor roof is provided with camera and carries out indoor environment image taking, and the picture photographing is sent to robot through wireless communication module, robot receives after picture, first with measure-alike grid, image is divided, and set up environment grating map according to the conventional body form of having stored in advance and the color pattern knowledge on floor, if not containing any barrier, be free grid, otherwise be barrier grid in some grids; Free space and barrier all can be expressed as the set of grid block, and barrier grid collection is designated as to O;

(2b) adopt method of direct coordinate to identify grid: to take the grating map upper left corner as true origin, level is X-axis positive dirction to right, direction is Y-axis positive dirction straight down, a unit length between each grid zone on respective coordinates axle, any one grid is all used rectangular coordinate (x, y) unique identification, thus environmental map is represented with a two-dimemsional number matrix map (M, N):

4. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 1, is characterized in that: the concrete steps of described step (3) are:

(3a) establish x, y is respectively horizontal stroke, the ordinate of robot in plane coordinate system, the deflection of θWei robot, and v is the speed of robot barycenter, the angular velocity of ωShi robot, the nonholonomic constraint that obtains robot motion is the kinematic function of robot center of mass motion is:

$\left\{\begin{array}{c}\stackrel{\·}{x}=v\left(t\right)\cos \mathrm{\θ}\left(t\right)\\ \stackrel{\·}{y}=v\left(t\right)\sin \mathrm{\θ}\left(t\right)\\ \stackrel{\·}{\mathrm{\θ}}=\mathrm{\ω}\left(t\right)\end{array}\right.---\left(1\right)$

(3b) by formula (1), can be obtained robot motion's discrete time model, as follows:

$\left\{\begin{array}{c}x\left(t_{k+1}\right)=x\left(t_k\right)+\mathrm{\ΔT}\·v\left(t_k\right)\·\cos (\mathrm{\θ}\left(t_k\right)+\mathrm{\ΔT\ω}\left(t_k\right)/2)\\ y\left(t_{k+1}\right)=y\left(t_k\right)+\mathrm{\ΔT}\·v\left(t_k\right)\·\sin (\mathrm{\θ}\left(t_k\right)+\mathrm{\ΔT\ω}\left(t_k\right)/2)\\ \mathrm{\θ}\left(t_{k+1}\right)=\mathrm{\θ}\left(t_k\right)+\mathrm{\ΔT\ω}\left(T_k\right)\end{array}\right.---\left(2\right)$

According to the motion principle of rigid body kinematics, the angular velocity that moves through left and right wheels of robot is controlled, that is:

$\left[\begin{array}{c}\stackrel{\·}{x}\\ \stackrel{\·}{y}\\ \stackrel{\·}{\mathrm{\θ}}\end{array}\right]=\left[\begin{array}{cc}\frac{r\cos \mathrm{\θ}}{2}& \frac{r\sin \mathrm{\θ}}{2}\\ \frac{r\sin \mathrm{\θ}}{2}& \frac{r\sin \mathrm{\θ}}{2}\\ \frac{r}{d}& -\frac{r}{d}\end{array}\right]\left[\begin{array}{c}{\mathrm{\ω}}_R\\ {\mathrm{\ω}}_L\end{array}\right]---\left(3\right)$

ω wherein _land ω _rthe left and right angular velocity of taking turns that is respectively robot, r is the radius of wheels of robot, d is the distance length of axle between two wheels.

5. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 1, is characterized in that: the concrete steps in described step (5) are:

(4a) parameter initialization: establishing the total number of frog in population is N, and sub-population number is k, and in sub-population, the number of frog is n, meets N=k*n; Local Search iterations is L, and global iterative number of times is G, and the maximum step-length of displacement that frog allows is S _max;

(4b) generate initial frog group: generate at random N frog as initial frog group P={X ₁, X ₂... X _n, j frog represents j solution, uses X _j=(x _j1, x _j2... x _js) represent, wherein, 0≤j≤N, s represents the dimension of each solution;

(4c) calculate fitness value: definition fitness function is as follows:

$f\left(X_i\right)={\mathrm{\ω}}_1\·e^{-\min \left|\right|X_i-Q_j\left|\right|}+{\mathrm{\ω}}_2\·\left|\right|X_i-T\left|\right|---\left(4\right)$

According to formula (4), calculate the fitness value of every frog, wherein ω ₁, ω ₂for constant, || || be the Euclidean distance of calculating between the two, O _jwhat represent is barrier, and T represents target location; Work as X _ifrom target close to time, || X _ithe value of-T|| is less, works as X _ifrom barrier away from time, min||X _i-O _j|| value will become greatly, thereby make f (X _i) value diminish;

(4d) divide frog group: N frog sorted to bad by good according to fitness value, remember that the best frog of overall fitness is X _g; Adopt the method for random packet that whole frog group is divided into k group, each group comprises n frog, meets N=kn;

(4e) Local Search: remember that in every sub-population, the best frog of fitness is X _b=(x _b1, x _b2..., x _bs), the poorest frog of fitness is X _ω=(x _{ω 1}, x _{ω 2}..., x _{ω s}), then in antithetical phrase population, the individual intermediate value strategy that adopts of the frog of poor fitness upgrades operation, repeats renewal process, until reach after the iterations L of setting, just stops the Local Search of each sub-population;

(4f) after Local Search completes, the frog of all groups is mixed again, write down the frog of current the best, then execution step (4d) and step (4e), repeats this operation until reach the global iterative number of times G of setting.

6. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 5, is characterized in that: in described step (4d), the method for random packet refers to:

In whole frog group, a front k frog enters respectively k group at random, every frog can only enter Yi Ge group, then, k+1 only enters k group at random to 2k frog, and every frog can only enter Yi Ge group, 2k+1 only enters k group at random to 3k frog, every frog can only enter Yi Ge group, the like, until all frogs are all assigned.

7. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 5, is characterized in that: in described step (4e), to the individual intermediate value policy update that adopts of the poorest frog, concrete steps are as follows:

(6a) central point of establishing each group is X _z=(x _z1, x _z2..., x _zs),

$x_{\mathrm{zj}}=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}/n---\left(5\right)$

S=rand×(X _z-X _ω) (6)

newX _ω=X _ω+S,-S _max≤S≤S _max (7)

Wherein, rand represents the random number between 0 and 1, and S represents the adjustment vector of frog individuality, S _maxrepresent that frog allows mobile maximum step-length, newX _ωrepresent to upgrade the poorest later solution;

(6b) recalculate the fitness value of resulting new explanation, judge whether it is improved, if improved, use newX _ωreplace X _ω; If do not improve, use whole population optimum solution X _greplace the X in formula (6) _zagain upgrade the poorest solution; If new explanation does not still improve, to the poorest solution X _ωupgrade at random.

8. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 4, is characterized in that: in described step (6), concrete steps are as follows:

(7a) robot calculates and arrives all optimum positions that impact point will pass through according to the algorithm that leapfrogs, and robot, according to current location and next step position, utilizes formula (1) and formula (2) to calculate

with

(7b) robot basis calculates

with

the angular velocity omega that utilizes formula (3) to calculate the left and right wheels of robot _land ω _r, control motion.

Tool of the present invention has the following advantages:

(1), the Intelligent home service robot system that proposes of the present invention, adopt indoor roof that camera collection indoor environment information is installed, set up environmental map, simple in structure, can effectively complete home services work;

(2), the present invention adopts the algorithm that leapfrogs to realize indoor service robot path planning, expanded the range of application of bionics techniques, improved functional reliability and the security of home services robot;

(3), the present invention adopts random packet method and intermediate value strategy to improve the algorithm that leapfrogs, and strengthened the optimizing ability of algorithm, preferably balance global search and the local search ability of algorithm;

(4), the present invention proposes the Intelligent home service robot system and method based on the algorithm that leapfrogs, this method can be imitated the feature of frog predation, have good intelligent, dirigibility, can save operation time and memory space, and greatly improved robot path planning's accuracy, improved home services robot work efficiency.

Accompanying drawing explanation

Fig. 1 is hardware device compositional block diagram of the present invention;

Fig. 2 is the robot path planning's process flow diagram based on the algorithm that leapfrogs in the present invention;

Fig. 3 is the improved algorithm flow chart that leapfrogs in the present invention;

Fig. 4 is the Intelligent home service robot principle of work schematic diagram based on the algorithm that leapfrogs in the present invention.

Embodiment

Below in conjunction with accompanying drawing, the present invention is described further.

Implement a kind of hardware device composition frame chart of the present invention as shown in Figure 1, comprise robot, several ultrasonic sensors, memory device, airborne camera, sound identification module, motor driver, mechanical arm, wireless communication module.Robot carries memory device, ultrasonic sensor, airborne camera, sound identification module, wireless communication module, the equipments such as motor driver and mechanical arm.Wherein, robot carries two wheels, is used for the operation of control; Ultrasonic sensor is evenly distributed in the dead ahead of robot, is used for the barrier that sniffing robot advances in process; Robot receives service object's instruction by wireless communication module or sound identification module, determine target.The camera that is arranged on indoor roof is taken indoor environment picture, by Wi-Fi, send to robot, after robot processes, set up indoor grille map, and carry out target, service object and robot self-position location, then by the improved algorithm that leapfrogs, carry out path planning, according to the barrier that calculates optimum position that robot will pass through and robot probe and arrive, the information such as target location and self-position, calculate the angular velocity of the left and right wheels of robot, thereby control arrives impact point place, again by the self-contained airborne camera of robot, the elevation information of scanning target object, driving device hand captures object, then planning arrives service object's path, object is handed over to service object's hand, finish the work.

The present invention is the Intelligent home service robot system and method based on the algorithm that leapfrogs, and its idiographic flow as shown in Figure 2, comprises the steps:

(1) robot carries memory device, ultrasonic sensor, airborne camera, sound identification module, wireless communication module, the equipments such as motor driver and mechanical arm;

(2) camera of being installed by indoor roof obtains indoor environment image, and sends and to process to robot, sets up environmental map, completes robot initial position location;

(3) robot sets up displacement and learns model, and its motion state variable is (x, y, θ) ^t, wherein (x, y) is the coordinate of robot in plane coordinate system, the deflection that θWei robot advances;

(4) robot utilizes sound identification module or wireless communication module to receive the instruction from service object, determines and needs the target of crawl and service object's position, and utilize environmental map to carry out target and service object location;

(5) robot, according to environmental map, utilizes the path planning of the improved algorithmization robot that leapfrogs, and calculates all optimum positions point that will pass through from robot current location to target;

(6) robot, according to displacement model and the next optimum position point that will arrive, calculates the angular velocity of its left and right wheels, controls motor driver drive machines people and travels forward;

(7) robot judges whether to arrive target, if do not return to step (6), if arrive target, utilizes airborne camera to carry out stereoscanning, obtains target vertical height overhead, and driving device hands movement captures target to target location;

(8) robot captures after target, automatically runs to service object place, completes services.

The searching method of the improved algorithm that leapfrogs in the present invention, its idiographic flow as shown in Figure 3, comprises the steps:

(1) parameter initialization.If the total number of frog is N in population, sub-population number is k, and in sub-population, the number of frog is n, meets N=k*n.Local Search iterations is L, and global iterative number of times is G, and the maximum step-length of displacement that frog allows is S _max.

(2) generate initial frog group.N frog of random generation is as initial frog group P={X ₁, X ₂... X _n, j (0≤j≤N) frog represents j solution, uses X _j=(x _j1, x _j2... x _js) represent, s represents the dimension of each solution.

(3) calculate fitness value.Definition fitness function is as follows:

$f\left(X_i\right)={\mathrm{\ω}}_1\·e^{-\min \left|\right|X_i-Q_j\left|\right|}+{\mathrm{\ω}}_2\·\left|\right|X_i-T\left|\right|---\left(4\right)$

According to formula (4), calculate the fitness value of every frog, wherein ω ₁, ω ₂for constant, || || be the Euclidean distance of calculating between the two, O _jwhat represent is barrier, and T represents target location; Work as X _ifrom target close to time, || X _ithe value of-T|| is less, works as X _ifrom barrier away from time, min||X _i-O _j|| value will become greatly, thereby make f (X _i) value diminish.

(4) divide frog group.N frog sorted to bad by good according to fitness value, remember that the best frog of overall fitness is X _g.Adopt the method for random packet that whole frog group is divided into k group, each group comprises n frog, meets N=kn.

(5) Local Search.Remember that in every sub-population, the best frog of fitness is X _b=(x _b1, x _b2..., x _bs), the poorest frog of fitness is X _ω=(x _{ω 1}, x _{ω 2}..., x _{ω s}), then in antithetical phrase population, the individual intermediate value strategy that adopts of the frog of poor fitness upgrades operation, repeats renewal process, until reach after the iterations L of setting, just stops the Local Search of each sub-population.

(6) after Local Search completes, the frog of all groups is mixed again, write down the frog of current the best, then execution step (4d) and step (4e), repeats this operation until reach the global iterative number of times G of setting.

In described step (4), the method for random packet refers to:

In whole frog group, a front k frog enters respectively k group at random, every frog can only enter Yi Ge group, then, k+1 only enters k group at random to 2k frog, and every frog can only enter Yi Ge group, 2k+1 only enters k group at random to 3k frog, every frog can only enter Yi Ge group, the like, until all frogs are all assigned.

In described step (5), to the individual intermediate value policy update that adopts of the poorest frog, concrete steps are as follows:

(5a) central point of establishing every sub-population is X _z=(x _z1, x _z2..., x _zs),

$x_{\mathrm{zj}}=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}/n---\left(5\right)$

S=rand×(X _z-X _ω) (6)

newX _ω=X _ω+S,-S _max≤S≤S _max (7)

Wherein, rand represents the random number between 0 and 1, and S represents the adjustment vector of frog individuality, S _maxrepresent that frog allows mobile maximum step-length, newX _ωrepresent to upgrade the poorest later solution.

(5b) recalculate the fitness value of resulting new explanation, judge whether it is improved, if improved, use newX _ωreplace X _ω; If do not improve, use whole population optimum solution X _greplace the X in formula (6) _zagain upgrade the poorest solution; If new explanation does not still improve, to the poorest solution X _ωupgrade at random.

Intelligent home service robot system and method schematic diagram based on the algorithm that leapfrogs in the present invention as shown in Figure 4, triangle represents robot, projected square part is barrier, circular portion is impact point, asterisk is the optimum position that the every step of algorithm produces that leapfrogs, the structure of the fitness function in algorithm leapfrogs, the fitness value that can guarantee target position point is minimum, and the fitness value of barrier position is maximum, according to the movement locus of this model robot, one will be like this and barrier can be automatically got around, avoid bumping against with barrier, can arrive fast the optimal path of desired target again.Robot arrives target place, takes needed object, and then former road is returned, and object is delivered in service object's hand, finishes the work.

The Intelligent home service robot system that the present invention proposes, adopt indoor roof that camera collection indoor environment information is installed, set up environmental map, simple in structure, do not need to increase too many equipment, by the employing algorithm that leapfrogs, realize indoor service robot path planning, expanded the range of application of bionics techniques, functional reliability and the security of home services robot have been improved, by the algorithm that leapfrogs is improved, strengthened the optimizing ability of algorithm, preferably balance global search and the local search ability of algorithm.The Intelligent home service robot system and method based on the algorithm that leapfrogs that the present invention proposes, can imitate the feature of frog predation, have good intelligent, dirigibility, can save operation time and memory space, and greatly improved robot path planning's accuracy, improved home services robot work efficiency, can better complete the work of home services robot.

Claims (8)

1. the Intelligent home service robot system based on the algorithm that leapfrogs, is characterized in that: comprise

The one left and right robot that drives walking of taking turns by controlled motion, robot has the mechanical arm being driven by motor driver;

Described robot front end carries airborne camera, for scanning the elevation information of target object;

Described robot dead ahead arranges one or more ultrasonic sensors, is used for the barrier that sniffing robot advances in process;

Described robot receives service object's instruction by wireless communication module or sound identification module, determine target;

Also comprise that one is arranged on indoor roof for taking the camera of indoor environment picture, camera sends to robot by Wi-Fi by the picture of shooting; After robot processes picture, set up indoor grille map, and carry out target, service object and robot self-position and locate, then by the improved algorithm that leapfrogs, carry out path planning, according to the barrier, target location and the self-position that calculate optimum position that robot will pass through and robot probe and arrive, calculate the angular velocity of the left and right wheels of robot, control arrives impact point place.

2. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs, is characterized in that: comprise the steps:

(1) robot carries memory device, ultrasonic sensor, airborne camera, sound identification module, wireless communication module, motor driver and mechanical arm;

(2) camera of being installed by indoor roof obtains indoor environment image, and sends and to process to robot, sets up environmental map, completes robot initial position location;

(3) robot sets up displacement and learns model, and its motion state variable is (x, y, θ) ^t, wherein (x, y) is the coordinate of robot in plane coordinate system, the deflection that θWei robot advances;

(4) robot utilizes sound identification module or wireless communication module to receive the instruction from service object, determines and needs the target of crawl and service object's position, and utilize environmental map to carry out target and service object location;

(5) robot, according to environmental map, utilizes the path planning of the improved algorithmization robot that leapfrogs, and calculates all optimum positions point that will pass through from robot current location to target;

(6) robot, according to displacement model and the next optimum position point that will arrive, calculates its left and right angular velocity of taking turns, and controls motor driver drive machines people and travels forward;

(7) robot judges whether to arrive target, if do not return to step (6), if arrive target, utilizes airborne camera to carry out stereoscanning, obtains target vertical height overhead, and driving device hands movement captures target to target location;

(8) robot captures after target, automatically runs to service object place, completes services.

3. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 1, it is characterized in that: described step (2) indoor roof is provided with camera indoor environment image is obtained, and transmission is processed to robot, set up environmental map, complete robot initial position location and refer to:

(2a) indoor roof is provided with camera and carries out indoor environment image taking, and the picture photographing is sent to robot through wireless communication module, robot receives after picture, first with measure-alike grid, image is divided, and set up environment grating map according to the conventional body form of having stored in advance and the color pattern knowledge on floor, if not containing any barrier, be free grid, otherwise be barrier grid in some grids; Free space and barrier all can be expressed as the set of grid block, and barrier grid collection is designated as to O;

(2b) adopt method of direct coordinate to identify grid: to take the grating map upper left corner as true origin, level is X-axis positive dirction to right, direction is Y-axis positive dirction straight down, a unit length between each grid zone on respective coordinates axle, any one grid is all used rectangular coordinate (x, y) unique identification, thus environmental map is represented with a two-dimemsional number matrix map (M, N):

4. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 1, is characterized in that: the concrete steps of described step (3) are:

(3a) establish x, y is respectively horizontal stroke, the ordinate of robot in plane coordinate system, the deflection of θWei robot, and v is the speed of robot barycenter, the angular velocity of ωShi robot, the nonholonomic constraint that obtains robot motion is

the kinematic function of robot center of mass motion is:

$\left\{\begin{array}{c}\stackrel{\·}{x}=v\left(t\right)\cos \mathrm{\θ}\left(t\right)\\ \stackrel{\·}{y}=v\left(t\right)\sin \mathrm{\θ}\left(t\right)\\ \stackrel{\·}{\mathrm{\θ}}=\mathrm{\ω}\left(t\right)\end{array}\right.---\left(1\right)$

(3b) by formula (1), can be obtained robot motion's discrete time model, as follows:

$\left\{\begin{array}{c}x\left(t_{k+1}\right)=x\left(t_k\right)+\mathrm{\ΔT}\·v\left(t_k\right)\·\cos (\mathrm{\θ}\left(t_k\right)+\mathrm{\ΔT\ω}\left(t_k\right)/2)\\ y\left(t_{k+1}\right)=y\left(t_k\right)+\mathrm{\ΔT}\·v\left(t_k\right)\·\sin (\mathrm{\θ}\left(t_k\right)+\mathrm{\ΔT\ω}\left(t_k\right)/2)\\ \mathrm{\θ}\left(t_{k+1}\right)=\mathrm{\θ}\left(t_k\right)+\mathrm{\ΔT\ω}\left(T_k\right)\end{array}\right.---\left(2\right)$

According to the motion principle of rigid body kinematics, the angular velocity that moves through left and right wheels of robot is controlled, that is:

$\left[\begin{array}{c}\stackrel{\·}{x}\\ \stackrel{\·}{y}\\ \stackrel{\·}{\mathrm{\θ}}\end{array}\right]=\left[\begin{array}{cc}\frac{r\cos \mathrm{\θ}}{2}& \frac{r\sin \mathrm{\θ}}{2}\\ \frac{r\sin \mathrm{\θ}}{2}& \frac{r\sin \mathrm{\θ}}{2}\\ \frac{r}{d}& -\frac{r}{d}\end{array}\right]\left[\begin{array}{c}{\mathrm{\ω}}_R\\ {\mathrm{\ω}}_L\end{array}\right]---\left(3\right)$

ω wherein _land ω _rthe left and right angular velocity of taking turns that is respectively robot, r is the radius of wheels of robot, d is the distance length of axle between two wheels.

5. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 1, is characterized in that: the concrete steps in described step (5) are:

(4a) parameter initialization: establishing the total number of frog in population is N, and sub-population number is k, and in sub-population, the number of frog is n, meets N=k*n; Local Search iterations is L, and global iterative number of times is G, and the maximum step-length of displacement that frog allows is S _max;

(4b) generate initial frog group: generate at random N frog as initial frog group P={X ₁, X ₂... X _n, j frog represents j solution, uses X _j=(x _j1, x _j2... x _js) represent, wherein, 0≤j≤N, s represents the dimension of each solution;

(4c) calculate fitness value: definition fitness function is as follows:

$f\left(X_i\right)={\mathrm{\ω}}_1\·e^{-\min \left|\right|X_i-Q_j\left|\right|}+{\mathrm{\ω}}_2\·\left|\right|X_i-T\left|\right|---\left(4\right)$

According to formula (4), calculate the fitness value of every frog, wherein ω ₁, ω ₂for constant, || || be the Euclidean distance of calculating between the two, O _jwhat represent is barrier, and T represents target location; Work as X _ifrom target close to time, || X _ithe value of-T|| is less, works as X _ifrom barrier away from time, min||X _i-O _j|| value will become greatly, thereby make f (X _i) value diminish;

(4d) divide frog group: N frog sorted to bad by good according to fitness value, remember that the best frog of overall fitness is X _g; Adopt the method for random packet that whole frog group is divided into k group, each group comprises n frog, meets N=kn;

(4e) Local Search: remember that in every sub-population, the best frog of fitness is X _b=(x _b1, x _b2..., x _bs), the poorest frog of fitness is X _ω=(x _{ω 1}, x _{ω 2}..., x _{ω s}), then in antithetical phrase population, the individual intermediate value strategy that adopts of the frog of poor fitness upgrades operation, repeats renewal process, until reach after the iterations L of setting, just stops the Local Search of each sub-population;

(4f) after Local Search completes, the frog of all groups is mixed again, write down the frog of current the best, then execution step (4d) and step (4e), repeats this operation until reach the global iterative number of times G of setting.

6. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 5, is characterized in that: in described step (4d), the method for random packet refers to:

In whole frog group, a front k frog enters respectively k group at random, every frog can only enter Yi Ge group, then, k+1 only enters k group at random to 2k frog, and every frog can only enter Yi Ge group, 2k+1 only enters k group at random to 3k frog, every frog can only enter Yi Ge group, the like, until all frogs are all assigned.

7. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 5, is characterized in that: in described step (4e), to the individual intermediate value policy update that adopts of the poorest frog, concrete steps are as follows:

(6a) central point of establishing each group is X _z=(x _z1, x _z2..., x _zs),

$x_{\mathrm{zj}}=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}/n---\left(5\right)$

S=rand×(X _z-X _ω) (6)

newX _ω=X _ω+S,-S _max≤S≤S _max (7)

Wherein, rand represents the random number between 0 and 1, and S represents the adjustment vector of frog individuality, S _maxrepresent that frog allows mobile maximum step-length, newX _ωrepresent to upgrade the poorest later solution;

(6b) recalculate the fitness value of resulting new explanation, judge whether it is improved, if improved, use newX _ωreplace X _ω; If do not improve, use whole population optimum solution X _greplace the X in formula (6) _zagain upgrade the poorest solution; If new explanation does not still improve, to the poorest solution X _ωupgrade at random.

8. the Intelligent home service robot method of servicing based on the algorithm that leapfrogs according to claim 4, is characterized in that: in described step (6), concrete steps are as follows:

(7a) robot calculates and arrives all optimum positions that impact point will pass through according to the algorithm that leapfrogs, and robot, according to current location and next step position, utilizes formula (1) and formula (2) to calculate

with

(7b) robot basis calculates

with

the angular velocity omega that utilizes formula (3) to calculate the left and right wheels of robot _land ω _r, control motion.

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