Indoor intelligent fire extinguishing robot and chassis control method

Abstract

The application relates to an indoor intelligent fire extinguishing robot and a chassis control method, which comprise a running system, a power supply system, a fire extinguishing system, a visual control system and a central controller; the running system is used for advancing, retreating and differential steering of the fire extinguishing robot; the power supply system is used for supplying power to the running system, the fire extinguishing system and the visual control system; the fire extinguishing system is used for extinguishing a fire source area; the visual control system is used for judging whether an obstacle can be normally passed when the robot runs, and if the obstacle cannot be normally passed, the local path needs to be re-planned to run to the fire disaster area, and the visual control system is used for identifying a fire source so that a fire extinguisher can be accurately sprayed to the fire source part; and the central controller is used for controlling the running system, the power supply system, the fire extinguishing system and the visual control system. The application has the advantages that rear wheel active steering and front wheel steering as an auxiliary are adopted, the differential steering has a small steering radius, and good steering stability is achieved.

Description

Technical Field

[0001] This invention belongs to the field of fire safety, specifically relating to an indoor intelligent fire extinguishing robot and its chassis control method. Background Technology

[0002] With economic development, the use of flammable and explosive materials such as petroleum and chemicals has increased, leading to a greater risk of fire. Modern buildings are taller and have more complex interior structures. Although each floor utilizes space to strategically place fire extinguishers and ceiling sprinklers, the effectiveness of these systems is significantly reduced at night due to fewer patrol personnel, potentially missing the optimal window for firefighting. Furthermore, sprinklers may not completely extinguish fires, all of which increase the difficulty of firefighting and make it more dangerous for firefighters to enter buildings. Firefighting robots, which can replace firefighters in dangerous firefighting tasks, have garnered widespread attention from all sectors of society.

[0003] Currently, firefighting robots are mainly used outdoors, while indoor firefighting robots are not yet mature enough.

[0004] Chinese patent CN202210741781.4 uses a traditional Ackermann steering chassis with front wheels as steering drive wheels and rear wheels as directional wheels. This results in a larger turning radius, but it also causes inconvenience when walking in narrow spaces such as corridors.

[0005] Patent CN202221743874.2 uses a tracked chassis, which can turn on the spot, but due to the relatively heavy body, it is not very suitable for indoor fire fighting.

[0006] A chassis with swivel wheels at the front and differential steering at the rear is relatively flexible, but in areas where fires occur, the roads may become uneven due to debris, resulting in poor directional stability of the chassis. Summary of the Invention

[0007] In view of the above problems, the purpose of this invention is to provide an indoor intelligent fire extinguishing robot and its chassis control method, which adopts a composite steering intelligent chassis with differential steering at the rear wheels and front wheels assisting the rear wheels in rotation. This achieves a smaller turning radius and enables in-situ turning while maintaining high directional stability, thus overcoming the shortcomings of the prior art.

[0008] The present invention provides a chassis control method for an indoor intelligent fire extinguishing robot, which specifically includes the following steps:

[0009] Step S1: The firefighting robot is driven using a composite steering intelligent chassis, which includes a differential steering rear motor wheel and a front steering wheel that assists the rear motor wheel in turning.

[0010] Step S2: Differential steering is achieved by controlling the speed difference between the left and right rear motor wheels using the central controller. The required speeds u for the left and right motor wheels are... ri The calculation is as follows: based on the actual turning radius. When the central controller receives the control trajectory, it calculates the turning radius R at that point. s Combined with the speed command u r Given the chassis wheelbase L, calculate the required speed u for the left and right wheels. ri Based on the minimum distance l from the rear axle center to the trajectory r Speed ​​compensation is achieved through a proportional controller, with a compensation value δ. i =a i k s l r K s For the compensation coefficient, a i a is the direction coefficient. i =-1, 1;

[0011] but:

[0012]

[0013] Among them, u d1 u d2 These represent the speeds of the left and right wheels, respectively. When i = 1, it is the speed of the left wheel, and when i = 2, it is the speed of the right wheel.

[0014] Step S3: Use a PI controller to control the rear motor wheel, wherein the PI controller uses the fruit fly optimization algorithm to control the theoretical angle of rotation of the steering wheel of the rear motor wheel;

[0015] Step S31: When the central controller receives the speed command u ri At that time, by comparing with the actual wheel speed u d In comparison, after passing through the PI controller, the output torque T ei ;where K p K i These are the proportional coefficient and the integral coefficient, respectively. Since the robot is moving within an indoor corridor and its speed does not exceed 15 km / h, and air resistance and ramp resistance are negligible, the robot's motion equation is:

[0016]

[0017] Where, m b The total weight of the firefighting robot is m. w f is the weight of the steering wheel and the motor wheel. r This is the rolling resistance coefficient;

[0018] Step S32: By monitoring the remaining amount of fire extinguishing agent in the fire extinguisher, the current total weight m of the fire extinguishing robot can be calculated b , and then the initial proportional coefficient K p and integral coefficient K i are obtained;

[0019] Step S33: Use the following formula as the improved speed formula:

[0020]

[0021] Step S34: The iteration steps of the fruit fly algorithm are as follows:

[0022] Step S341: Initialize the population size PA of the fruit fly population, the maximum running generation number Nmax, the initial range LR of the fruit fly individual, the fruit fly individual position X axis , Y axis , and the initial speed V x and V y ; C xi is the learning factor, r1, r2 are random numbers in the range of [0, 1], the position of the i-th particle is X i , Y i , X best , Y best represents the position corresponding to the best value found by the i-th individual running to the current generation number.

[0023] Step S342: Give the inertia weight w and calculate the flight speed of the fruit fly to update the position of the fruit fly;

[0024] Step S343: Calculate the distance Disti of the fruit fly individual from the origin and the smell concentration judgment value S;

[0025] Step S344: Calculate the smell concentration felt by each fruit fly individual using the smell concentration judgment value Si and the fitness function, and select the minimum value of the smell concentration in the fruit fly individual, and record the position information of the corresponding fruit fly individual;

[0026] Step S345: Determine whether the optimal value of the smell concentration of the fruit fly individual obtained by this optimization is better than the optimal smell concentration of the current fruit fly population. If it is not better than the current value, go to the second step; otherwise, update the optimal smell concentration of the fruit fly population and the best position of the fruit fly individual;

[0027] Step S346: Determine whether the current has reached the stopping condition of the algorithm. If yes, the algorithm stops running, and the optimal smell concentration of the fruit fly population is the required solution. If not, continue running from the second step;

[0028] Step S4: Keep the fruit fly algorithm after iteration to the PI controller to control the motor wheel;

[0029] Step S5: the PI controller calculates the actual wheel speed u di , and obtains the steering wheel rotation theoretical angle θ:

[0030]

[0031] Another object of the present application is to provide a control method for an indoor intelligent fire extinguishing robot, which specifically comprises the following steps:

[0032] Step S1: alarm the room fire through the smoke alarm in the room;

[0033] Step S2: use the fire source positioning module of the indoor intelligent fire extinguishing robot to detect and determine the specific position of the fire source area;

[0034] Step S3: use the communication module to determine the route of the fire extinguishing robot to the fire source area, and use the upper computer to transmit the driving command to the central controller of the fire extinguishing robot;

[0035] Step S4: after the central controller in step S3 receives the planned path, use the central control controller to control the chassis to walk to the target area according to the path;

[0036] Step S5: in the process of driving, use the laser radar of the visual control system to scan the surrounding environment, if an obstacle is encountered, the front camera and the rear camera are used to judge whether it can pass through the obstacle normally, if it can pass through, it is normally operated according to the original route, if it cannot pass through, the central controller implements the obstacle avoidance instruction and re-plans the local path, so that the fire extinguishing robot reaches the fire area smoothly;

[0037] Step S6: in the process of driving, use the rear motor wheel of the driving system to turn, wherein, because the quality of the fire extinguishing agent will change, the torque is calculated through the driving equation, and then the PI controller with iterative artificial bee optimization algorithm is used to control the rotation speed of the left and right rear wheels of the motor wheel; in the indoor fire scene, because the road will be damaged or have sundries, it will cause the fire extinguishing robot to be unstable in the driving process, and the front steering wheel is used to assist steering, so as to further improve the steering stability;

[0038] Step S7: when the fire extinguishing robot reaches the fire source position, the fire extinguishing system starts to work, the nozzle of the fire extinguishing device aims at the fire source through the direction controller, the electromagnetic valve is powered on, and changes from the closed state to the open state, at this time, the fire extinguishing agent starts to be sprayed, after the fire source is extinguished, the central controller receives the stop spraying instruction, and the electromagnetic valve is powered off to restore the closed state;

[0039] Step S8: the central controller receives the return instruction and returns according to the specified route.

[0040] The third object of the present application is to provide an indoor intelligent fire extinguishing robot, comprising a driving system, a power supply system, a fire extinguishing system, a visual control system, and a central controller.

[0041] The driving system is used for the forward movement, backward movement and differential steering of the fire extinguishing robot, and comprises motor wheels composed of left and right rear wheels, a motor controller for controlling the motor wheels, a front steering wheel for assisting steering, and a steering wheel controller for controlling the front steering wheel.

[0042] The power supply system is used for supplying power to the driving system, the fire extinguishing system, and the visual control system.

[0043] The fire extinguishing system is used for extinguishing fire in the fire source area, and comprises a fire extinguisher, a solenoid valve for controlling the switch of the fire extinguisher, and a fire spraying control panel for controlling the fire extinguisher.

[0044] The visual control system is used for determining whether the robot can normally pass through obstacles encountered during driving, and if not, re-planning a local path to drive to the fire area, and for identifying the fire source to accurately spray the fire extinguisher to the fire source position.

[0045] The central controller is used for controlling the driving system, the power supply system, the fire extinguishing system, and the visual control system.

[0046] As a preferred embodiment of the present application, the upper layer of the composite steering intelligent chassis is provided with a heat sink for heat dissipation of components, a DC-DC converter for converting battery voltage, a start switch for controlling the opening and closing of the central controller, and the central controller.

[0047] As a preferred embodiment of the present application, the fire extinguisher penetrates through the entire vehicle body and is always in an open state.

[0048] The advantages and positive effects of the present application are:

[0049] 1、The present application considers that the weight of the fire extinguishing agent accounts for a large proportion, adopts the PI (proportion-integral) control of the improved fruit fly optimization algorithm, and calculates the PI coefficient according to the residual amount of the fire extinguishing agent, so that the chassis has better control results under different working conditions.

[0050] 2、The present application aims at the traditional differential steering chassis, and the straight line driving is unstable and the error is large when steering due to the factors such as the wheel speed difference of left and right wheels and ground disturbance. The present application becomes an integrated chassis on the basis of the original, and the advantage is that the rear wheel is actively steered, and the front wheel steering is used as auxiliary, so that the differential steering has a small steering radius and good control stability. BRIEF DESCRIPTION OF DRAWINGS

[0051] Other objects and results of the present application will be more apparent and easy to understand by referring to the following description in conjunction with the accompanying drawings, and with a more comprehensive understanding of the present application. In the drawings:

[0052] Figure 1 The overall structure schematic diagram of the indoor intelligent fire extinguishing robot in the embodiment of the present application.

[0053] Figure 2 The overall structure front view of the indoor intelligent fire extinguishing robot in the embodiment of the present application.

[0054] Figure 3 The overall structure top view of the indoor intelligent fire extinguishing robot in the embodiment of the present application.

[0055] Figure 4 The overall structure side view of the indoor intelligent fire extinguishing robot in the embodiment of the present application.

[0056] Figure 5 The control schematic diagram of the indoor intelligent fire extinguishing robot in the embodiment of the present application.

[0057] Figure 6 The control logic diagram of the indoor intelligent fire extinguishing robot in the embodiment of the present application.

[0058] The figure mark: rear wheel 1, bottom plate 2, battery 3, laser radar 4, front end camera 5, axle fixing plate 6, rear wheel 7, lower layer bottom plate 8, upper layer bottom plate 9, fire spraying control plate 10, development board 11, fire extinguisher 12, rear end camera 13, front wheel controller 14, transparent small fixing 15, motor controller 16, NX plate 17, DC-DC converter 18, front wheel 19, radiator 20, central controller 21, electromagnetic valve 22, switch 23. DETAILED DESCRIPTION

[0059] In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It can be apparent, however, that such embodiment(s) can be practiced without

[0060] Embodiment 1

[0061] Figures 1-4 An overall configuration diagram according to an embodiment of the present application is shown.

[0062] As Figures 1-4As shown, the indoor intelligent fire extinguishing robot provided by the embodiment of the application comprises rear wheels 1, a bottom plate 2, a battery 3, a laser radar 4, a front-end camera 5, an axle fixing plate 6, rear wheels 7, a lower layer bottom plate 8, an upper layer bottom plate 9, a fire spraying control board 10, a development board 11, a fire extinguisher 12, a rear-end camera 13, a front wheel controller 14, a transparent small fixing block 15, a motor controller 16, an NX board 17, a DC-DC converter 18, front wheels 19, a radiator 20, a central controller 21, a solenoid valve 22 and a switch 23. The lower layer bottom plate 8 in the bottom plate 2 is provided with one front wheel 19 and two rear wheels 1 and 7, the motors of the rear wheels 1 and 7 are controlled by the motor controller 16 placed on the upper layer of the bottom plate, the front wheel 19 is a universal wheel, and the front wheel 19 is controlled by the front wheel controller 14. The motor controller 16 controls the rear wheels 1 and 7 to give relevant instructions, but since there may be protruding and unstable places on the road in a fire, which may cause unstable driving tracks, the front wheel controller 14 also controls the front wheel 19 to assist the rear wheels in active steering, so as to keep the fire extinguishing robot driving stable. The upper layer bottom plate 9 of the bottom plate 2 is provided with the radiator 20, the DC-DC converter 18, the switch 23, the central controller 21, the transparent small fixing block 15 and the battery 3. The radiator 20 is used for component heat dissipation, the DC-DC converter is used for battery voltage conversion, and the switch is used for controlling the central controller to open and close. The lower layer bottom plate 8 and the upper layer bottom plate 9 are connected and supported by a support column, and the front-end camera 5 and the laser radar 4 are placed on the lower layer bottom plate 8. The rear-end camera 13, the fire spraying control board 10, the motor controller 16 and the NX board 17 are placed on the upper layer bottom plate 9. When the fire extinguishing robot travels according to the designated planning path, the laser radar 4 starts to sense the obstacles in the environment, at this time, the front-end camera 5 and the rear-end camera 13 judge whether it can pass through, if it cannot pass through, first, the central controller 21 receives the obstacle avoidance instruction to bypass the obstacle, and the host computer re-plans the path to drive to the fire source area at this time. The fire extinguisher 12 penetrates through the whole vehicle body and is always in an open state, the fire extinguisher threaded port is connected with the solenoid valve 22 through a double-thread pipe, the solenoid valve 22 is in a normally closed state, when the solenoid valve 22 is powered, the fire extinguishing agent is sprayed to extinguish the fire. The chassis control module is composed of a motor controller and two wheel motors. The forward movement, backward movement and differential steering of the fire extinguishing robot are realized. The fire extinguishing system control module mainly comprises an stm32 single-chip microcomputer and a solenoid valve. After receiving the signal sent by the industrial computer, the solenoid valve is opened. After receiving the reset signal of the industrial computer, the solenoid valve is closed.

[0063] Embodiment 2

[0064] Figure 6 The overall structure schematic diagram according to the embodiment of the application is shown.

[0065] As Figure 6As shown, the control method of the indoor intelligent fire extinguishing robot provided by the embodiment of the application specifically comprises the following steps:

[0066] Step S1: When a certain room is on fire, the room fire is alarmed by a smoke alarm in the room;

[0067] Step S2: The specific position of the fire source area is detected and determined by using a fire source positioning module of the indoor intelligent fire extinguishing robot;

[0068] Step S3: The route of the fire extinguishing robot to the fire source area is determined by using a communication module, and the driving command is transmitted to the central controller of the fire extinguishing robot by using the upper computer;

[0069] Step S4: After the central controller in step S3 receives the planned path, the central control controller is used to control the chassis to walk to the target area according to the path;

[0070] Step S5: In the process of driving, the surrounding environment is scanned by using the laser radar of the visual control system, if an obstacle is encountered, the front camera and the rear camera are used to judge whether the obstacle can be normally passed, if the obstacle can be passed, the original route is normally run, if the obstacle cannot be passed, the central controller implements the obstacle avoidance instruction and re-plans a local path, so that the fire extinguishing robot smoothly reaches the fire area;

[0071] Step S6: In the process of driving, the rear end motor wheel of the driving system is used for steering, wherein, because the quality of the fire extinguishing agent will change, the torque is calculated by using a driving equation, and the speed of the left rear wheel and the right rear wheel of the motor wheel is controlled by using a PI controller with an iterative artificial bee optimization algorithm; In the indoor fire scene, because the road will be damaged or have sundries, the fire extinguishing robot will be unstable in the driving process, the front steering wheel is used for auxiliary steering, and the steering stability is further improved;

[0072] Step S7: When the fire extinguishing robot reaches the fire source position, the fire extinguishing system starts to work, the nozzle of the fire extinguishing device aims at the fire source by using a direction controller, the electromagnetic valve is powered on, and changes from a closed state to an open state, at this time, the fire extinguishing agent starts to be sprayed, after the fire source is extinguished, the central controller receives a stop spraying instruction, the electromagnetic valve is powered off to restore the closed state;

[0073] Step S8: The central controller receives a return instruction and returns according to the specified route.

[0074] Embodiment 3

[0075] Figure 5 The overall structure schematic diagram according to the embodiment of the application is shown.

[0076] As Figure 5As shown, the chassis control method of the indoor intelligent fire extinguishing robot provided by the embodiment of the application specifically comprises the following steps:

[0077] Step S1: using a composite steering intelligent chassis in the fire extinguishing robot to travel, wherein the composite steering intelligent chassis comprises a rear motor wheel with differential steering and a front steering wheel assisting the rotation of the rear motor wheel;

[0078] Step S2: using a central controller to control the speed difference of the left rear motor wheel and the right rear motor wheel to perform differential steering, wherein the required speeds u ri of the left and right motor wheels are calculated as follows: according to the actual steering radius R When the central controller receives the control trajectory, the steering radius R s of the point is calculated, and in combination with the speed instruction u r and the chassis wheelbase L, the required speeds u ri of the left and right wheels are calculated, according to the minimum distance l r from the rear axle center to the trajectory, the speed is compensated through a proportional controller, and the compensation value δ i = a i k s l r , K s is a compensation coefficient, a i is a direction coefficient, and a i =-1, 1;

[0079] Then:

[0080]

[0081] Wherein, u d1 and u d2 are the speeds of the left and right wheels, i=1 is the speed of the left wheel, and i=2 is the speed of the right wheel;

[0082] Step S3: using a PI controller to control the rear motor wheel, wherein the PI controller adopts an improved PI (proportional-integral) control of the rear motor wheel of the steering wheel rotation theory angle of the fruit fly optimization algorithm;

[0083] Step S31: when the central controller receives the speed instruction u ri , the actual wheel speed u d is compared, and the output torque T ei is output through the PI controller; wherein K p and K i are proportional and integral coefficients, respectively, Since the speed does not exceed 15km\h when walking in the indoor corridor, the air resistance and the slope resistance are ignored; and the travel equation of the robot is:

[0084]

[0085] wherein m b is the total weight of the fire extinguishing robot, m w is the weight of the steering wheel and the motor wheel, f r is the rolling resistance coefficient;

[0086] Step S32: Since the weight of the fire extinguisher is a large part of the fire extinguishing robot, its mass change is sufficient to affect the change of the total mass of the robot, so the selection of the proportional coefficient K p and the integral coefficient K i is particularly important. By monitoring the remaining amount of fire extinguishing agent in the fire extinguisher, the current total weight m b of the fire extinguishing robot can be calculated, and the initial proportional coefficient K p and the integral coefficient K i are obtained;

[0087] Step S33: When a fire occurs, time is of the essence, so it is necessary to quickly and accurately travel according to the specified trajectory. The fruit fly algorithm has a simple structure and extremely fast operation speed, but the search direction has great randomness. If the fruit fly group is in a local optimization position at the beginning, it cannot run out of this local optimization position, and the optimization result is unstable. Therefore, an improved fruit fly optimization algorithm is used. In the particle swarm algorithm, each generation of particles will use flight speed as the position update method, and the flight speed is affected by the current speed, self-memory and optimal position. This position update method can effectively avoid the blindness of the search direction. The following formula is used as the improved speed formula:

[0088]

[0089] Step S34: The iteration steps of the improved fruit fly algorithm are as follows:

[0090] Step S341: Initialize the population size PA of the fruit fly population, the maximum number of iterations Nmax, the initial range LR of the fruit fly individual, the initial position X axis , Y axis of the fruit fly individual, and the initial speed V x and V y ; C xi is the learning factor, r1 and r2 are random numbers in the range of [0, 1], the position of the i-th particle is X i , Y i , X best , Y best indicates the position corresponding to the best value found by the i-th individual when running to the current number of iterations.

[0091] Step S342: give the inertia weight w and calculate the flying speed of fruit fly, so as to update the position of fruit fly;

[0092] Step S343: calculate the distance Disti of fruit fly individual from the origin and the smell concentration judgment value S;

[0093] Step S344: calculate the smell concentration felt by each fruit fly individual by using the smell concentration judgment value Si and the fitness function, and select the minimum value of the smell concentration of fruit fly individual, and record the position information of the corresponding fruit fly individual;

[0094] Step S345: judge whether the optimal value of the smell concentration of the fruit fly individual obtained by this optimization is better than the optimal smell concentration of the current fruit fly population, if not, go to the second step; otherwise, update the optimal smell concentration of the fruit fly population and the best position of the fruit fly individual;

[0095] Step S346: judge whether the current reaches the stopping condition of the algorithm, if yes, the algorithm stops running, at this time the optimal smell concentration of the fruit fly population is the required solution, if not, continue to run from the second step;

[0096] Step S4: keep the fruit fly algorithm after iteration to the PI controller control motor wheel;

[0097] Step S5: the PI controller calculates and obtains the theoretical angle θ of the steering wheel rotation according to the actual wheel speed u di

[0098]

[0099] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any skilled person in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.​

Claims

1. A chassis control method of an indoor intelligent fire extinguishing robot, characterized in that, The method comprises the following steps: Step S1: driving by using a composite type steering intelligent chassis in the fire extinguishing robot, wherein the composite type steering intelligent chassis comprises a differential steering rear motor wheel and a front steering wheel assisting the rotation of the rear motor wheel; Step S2: control the speed difference of the left and right rear motor wheels to perform differential steering using the central controller, wherein the required speeds u ri of the left and right motor wheels are calculated as follows: according to the actual steering radius When the central controller receives the control trajectory, the steering radius R s of the point is calculated r , the required speeds u ri of the left and right wheels are calculated in combination with the speed command u r and the chassis wheelbase L, the speeds are compensated by a proportional controller according to the minimum distance l r from the rear axle center to the trajectory, the compensation value δ i = a i k s l r , K s is the compensation coefficient, a i is the direction coefficient, a i =-1, 1; Then: wherein, u d1 , u d2 are the left and right wheel speeds, respectively, with i = 1 for the left wheel speed and i = 2 for the right wheel speed. Step S3: controlling the rear motor wheel by using a PI controller, wherein the PI controller adopts a PI control of the steering wheel rotation theoretical angle of the rear motor wheel by using a fruit fly optimization algorithm; Step S31: When the central controller receives the speed command u ri , the actual wheel speed u d is compared with the PI controller, and the output torque T ei is output; where K p , K i are the proportional coefficient and integral coefficient, Since walking in the indoor corridor, the speed does not exceed 15km\h, air resistance and slope resistance are ignored; the travel equation of the robot is: wherein m b is the total weight of the fire-fighting robot, m w is the weight of the steering wheel and the motor wheel, f r is the rolling resistance coefficient; Step S32: By monitoring the remaining amount of extinguishing agent in the fire extinguisher, the current total weight m of the fire extinguishing robot can be calculated b , and then the initial proportional coefficient K p and the integral coefficient K i are obtained Step S33: using the following formula as an improved speed formula: Step S34: the fruit fly algorithm iteration steps are as follows: Step S341: initialize the population size PA of the fruit fly population, the maximum running generation number Nmax, the initial range LR of the fruit fly individual, the fruit fly individual position X axis , Y axis , and the initial speed V x and V y ; C xi is a learning factor, r1, r2 are random numbers in the range of [0, 1], the position of the i-th particle is X i , Y i , X best , Y best represents the position corresponding to the best value found by the i-th individual running to the current generation number; Step S342: giving an inertia weight w and calculating the flight speed of the fruit fly to update the position of the fruit fly; Step S343: calculating the distance Disti of the fruit fly individual from the origin and the taste concentration judgment value S; Step S344: calculating the taste concentration felt by each fruit fly individual by using the taste concentration judgment value Si and the fitness function, and selecting the minimum value of the taste concentration in the fruit fly individual, and recording the position information of the corresponding fruit fly individual; Step S345: judging whether the optimal value of the fruit fly individual obtained by the current optimization is better than the optimal taste concentration of the current fruit fly population, if not, turning to the second step; otherwise, updating the optimal taste concentration of the fruit fly population and the best position of the fruit fly individual; Step S346: judging whether the current reaches the stopping condition of the algorithm, if yes, the algorithm stops running, at this time the optimal taste concentration of the fruit fly population is the required solution, if not, continuing to run from the second step; Step S4: keeping the fruit fly algorithm iteration to the PI controller controlling the rear motor wheel; Step S5: The PI controller calculates the theoretical angle of rotation θ of the steering wheel based on the actual wheel speed u di , and obtains the theoretical angle of rotation θ of the steering wheel.

2. The indoor intelligent fire extinguishing robot used for the chassis control method of the indoor intelligent fire extinguishing robot according to claim 1, characterized in that, It comprises: a driving system, a power supply system, a fire extinguishing system, a visual control system, and a central controller; The driving system is used for the forward movement, backward movement and differential steering of the fire extinguishing robot, and comprises a motor wheel composed of left and right rear wheels, a motor controller for controlling the motor wheel, a front steering wheel for assisting steering, and a steering wheel controller for controlling the front steering wheel, the motor wheel is installed at the rear end of the composite type steering intelligent chassis, the front steering wheel is installed at the middle part of the front end of the composite type steering intelligent chassis, the motor controller is internally provided with a PI controller, and the PI controller is used for PI control of the steering wheel rotation theoretical angle of the rear motor wheel by using the fruit fly optimization algorithm after iteration; The power supply system is used for supplying power to the driving system, the fire extinguishing system and the visual control system; The fire extinguishing system is used for extinguishing the fire source area, and comprises a fire extinguisher, an electromagnetic valve for controlling the switch of the fire extinguisher, and a fire spraying control panel for controlling the fire extinguisher, the fire extinguisher is installed at the middle part of the composite type steering intelligent chassis, the upper end of the fire extinguisher is provided with the electromagnetic valve, and the front end of the fire extinguisher is provided with the direction controller; the electromagnetic valve, the direction controller and the fire spraying control panel are connected with the central controller on the chassis through pipes, and the direction controller is used for controlling the spraying direction of the fire extinguisher; The visual control system is used for judging whether the robot can pass the obstacle normally when the robot encounters the obstacle during the running process, and if not, the robot needs to re-plan the local path to run to the fire area, and is used for identifying the fire source to make the fire extinguisher accurately spray to the fire source position. The central controller is used for controlling the running system, the power supply system, the fire extinguishing system and the visual control system.

3. The indoor intelligent fire extinguishing robot used for the chassis control method of the indoor intelligent fire extinguishing robot according to claim 1, characterized in that, The upper layer of the composite type steering intelligent chassis is provided with a radiator for heat dissipation of components, a DC-DC converter for converting the battery voltage, a starting switch for controlling the opening and closing of the central controller, and the central controller.

4. The indoor intelligent fire extinguishing robot used for the chassis control method of the indoor intelligent fire extinguishing robot according to claim 1, characterized in that, The fire extinguisher penetrates through the whole vehicle body and is always in an open state. The threaded port of the fire extinguisher is connected with a solenoid valve through a double-end threaded pipe. The solenoid valve is in a normally closed state. When the solenoid valve is powered, the fire extinguishing agent is sprayed to extinguish the fire.

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