Unmanned serving trolley suitable for underground coal mine

Abstract

The invention discloses an unmanned meal delivery trolley suitable for an underground coal mine. The unmanned meal delivery trolley comprises a meal delivery trolley body, a power system and a meal delivery system, wherein the power system and the meal delivery system are applied to the meal delivery trolley body; the power system is used for receiving a target control instruction, determining a target position, generating a set navigation path and controlling the serving trolley body to run to the target position; the meal delivery system is used for providing meal delivery service when the meal delivery car body travels to the target position; on the basis of the meal delivery system, under the condition that the meal delivery trolley travels to the target position, the target object at the target position is automatically recognized, the meal delivery service is provided for the target object, and therefore human input can be reduced, the meal delivery efficiency can be improved, and due to the fact that the meal delivery trolley can conduct meal delivery without relying on manual work, the meal delivery efficiency is improved. The meal delivery based on the meal delivery trolley can improve the safety coefficient of meal delivery in a complex working environment, such as an underground working environment of a coal mine, and the safety risk is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of underground food delivery vehicles, and in particular to an unmanned food delivery vehicle applicable to coal mines underground. Background Art

[0002] The working environment in coal mines underground is complex, with various harsh conditions such as high temperature, high humidity, and harmful gases, posing threats to the health and safety of personnel. In the field of coal mining, work safety has always been of top priority. With the development of technology, the working environment in coal mines underground is gradually transforming towards intelligence and automation to reduce the direct exposure of manpower to high-risk environments and improve production efficiency.

[0003] Due to the relatively complex working environment in coal mines underground, in related technologies, food delivery often relies on manual methods. This method not only has low efficiency but also has certain safety hazards. Existing technologies such as the patent with the publication number CN110096055A disclose an intelligent food delivery navigation method and navigation module, including the following steps: S1. Control the food delivery robot to move along the magnetic track towards the target table according to the pre-planned path; S2. Determine whether there are obstacles in front of the food delivery robot; if there are, plan an obstacle avoidance path and then go to step S3; if not, go to step S4; S3. Control the food delivery robot to leave the magnetic track according to the obstacle avoidance path, avoid the obstacle, and then return to the magnetic track again; S4. Control the food delivery robot to continue moving along the pre-planned path until it reaches the target table.

[0004] Based on the above, the prior art also discloses the obstacle avoidance logic of food delivery robots, that is, whether there are obstacles is identified through a sensor array. If there are, the pre-planned path is changed; if not, the robot walks along the pre-planned path. However, when this application is applied to the environment in coal mines underground, due to the large number of obstacles, many road branches, and the possible existence of flammable and explosive substances such as gas and coal dust in the environment in coal mines underground, when traditional unmanned vehicles are applied to the environment in coal mines underground, the improvement of their food delivery efficiency is not significant compared with the manual food delivery method. At the same time, it may occur that obstacles block the pre-planned path, resulting in the truncation of the pre-planned path and inability to pass. In this case, the food delivery vehicle needs to be braked. And because the food delivery vehicle is loaded with food inside, it is also necessary to avoid emergency braking causing the food to spill and affecting the food delivery service experience. Summary of the Invention

[0005] The main purpose of the present invention is to provide an unmanned food delivery vehicle applicable to coal mines underground, aiming to solve the existing technical problems.

[0006] To achieve the above object, the present invention provides an unmanned food delivery vehicle applicable to coal mines underground, including a food delivery vehicle body and a power system and a food delivery system applied to the food delivery vehicle body;

[0007] The power system is used to receive a target control instruction, determine a target position, generate a predefined navigation path, and control the food delivery vehicle body to travel to the target position;

[0008] The power system includes an obstacle avoidance module and a braking module. The obstacle avoidance module is used to control the food delivery vehicle body to avoid obstacles. The braking module is used to generate a braking instruction according to the obstacle information or the target position matching information, control the food delivery vehicle body to start braking based on the initial braking acceleration, divide the braking process based on an equal-length time period, iteratively calculate the state information of the food delivery vehicle body at the end node of each time period according to the initial speed of the food delivery vehicle body, output the braking acceleration of the next time period based on the state information of the food delivery vehicle body, and control the food delivery vehicle body to brake smoothly.

[0009] The food delivery system is used to provide a food delivery service when the food delivery vehicle body travels to the target position.

[0010] Further, the obstacle avoidance module includes an environment perception unit and an obstacle avoidance path planning unit. The environment perception unit is used to collect the obstacle information and the target position matching information during the travel of the food delivery vehicle body. The obstacle avoidance path planning unit is used to plan an obstacle avoidance path;

[0011] The power system further includes a navigation module; the navigation module is used to determine a predefined navigation path;

[0012] Among them, the method for controlling the food delivery vehicle body to avoid obstacles includes,

[0013] When there is an obstacle on the predefined navigation path, the environment perception unit collects the obstacle information and sends it to the obstacle avoidance path planning unit;

[0014] The obstacle avoidance path planning unit generates an obstacle avoidance path based on the obstacle information; the obstacle information carries the obstacle volume and position information;

[0015] Send the obstacle avoidance path to the navigation module;

[0016] The navigation module generates a real-time navigation path based on the fusion of the obstacle avoidance path and the predefined navigation path.

[0017] Further, the power system further includes a motion execution mechanism. The motion execution mechanism is used to receive the predefined navigation path and the real-time navigation path, and drive the food delivery vehicle body to travel to the target position based on the predefined navigation path and the real-time navigation path.

[0018] Further, the method for the food delivery vehicle body to start braking includes,

[0019] Obtain the current real-time speed V(t) of the food delivery vehicle body based on the motion execution mechanism;

[0020] Construct a braking logic algorithm, which is expressed by the formula:

[0021]

[0022] Among them, a(t) is the braking acceleration calculated by the braking logic algorithm; K p is the proportional gain, which is used to determine the proportional relationship between the braking acceleration and the speed error; K i is the integral gain, which is used to eliminate the error changing with time; K d is the differential gain, which is used to predict the change trend of the error; e(t) is the difference between the target speed and the real-time speed; represents the cumulative error, which is expressed by E(t); is the error change rate;

[0023] Set the time period T for the iterative update of the braking acceleration a(t);

[0024] e(t) = V(t) - Vtarget = V(t)

[0025]

[0026] Among them, Vtarget is the target speed; t represents any period, and t - T represents the previous period;

[0027] Based on the above formula, calculate the braking acceleration a(t) that changes with time;

[0028] For the real-time speed of the above food delivery vehicle body and the cumulative braking distance of the food delivery vehicle body, it is expressed as:

[0029] V(t) = V(t - T) - a(t - T)·T

[0030]

[0031] Among them, S(t) is the cumulative braking distance at the cut-off time t.

[0032] Furthermore, the power system further includes an environmental parameter acquisition module, and the environmental parameter acquisition module is used to detect the environmental parameters in the area where the food delivery vehicle body is located and send the acquired environmental parameters to the explosion-proof module;

[0033] The environmental parameters include at least one of the following: temperature parameter, humidity parameter, and gas concentration parameter; the gas concentration parameter includes methane gas concentration.

[0034] Further, the food delivery system includes an explosion-proof module, and the explosion-proof module includes a power supply unit, a main control unit, a display unit, and an analysis unit; the main control unit includes an intrinsically safe circuit board, the power supply unit includes an intrinsically safe power supply, and the intrinsically safe power supply is connected to the intrinsically safe circuit board;

[0035] The analysis unit is configured to determine whether there are potential hazards in the area where the food delivery vehicle body is located based on the environmental parameters, and includes the following steps:

[0036] If the methane gas concentration exceeds the threshold, a warning prompt is generated, and

[0037] Obtain the change trend of the methane gas concentration with the driving of the food delivery vehicle, determine the position with the maximum methane gas concentration as the methane leakage point, construct an excessive methane coverage area based on the methane leakage point, and determine whether the target position is within the excessive methane coverage area:

[0038] If the target position is within this range, an evacuation prompt is generated synchronously;

[0039] Both the warning prompt and the evacuation prompt are sent by the analysis unit to the display unit.

[0040] Further, the food delivery system further includes an identity recognition module; the main control unit is connected to the identity recognition module;

[0041] When the food delivery vehicle body travels to the target position, the target object at the target position is subjected to identity recognition processing based on the identity recognition module; the target object is the object to be provided with food delivery service;

[0042] When the identity recognition is successful, an identity confirmation message is generated, otherwise it is not generated.

[0043] Further, the food delivery vehicle body includes n storage compartments, n≥1; the explosion-proof module further includes a storage compartment control unit, and the storage compartment control unit includes m intrinsically safe motors, m≥1;

[0044] The main control unit is connected to the storage compartment control unit and is further configured to control the opening and closing states of the n storage compartments based on the m intrinsically safe motors;

[0045] Among them, the method for controlling the opening and closing states of the storage compartments based on the storage compartment control unit includes,

[0046] The main control unit generates an identity confirmation message based on the identity recognition module;

[0047] Based on the identity confirmation message, obtain the mapping relationship between the food requirements of the target object and the storage compartments;

[0048] Send a first control instruction to the storage compartment control unit based on the mapping relationship; the first control instruction is used to indicate the storage compartment to be opened.

[0049] Determine whether the meal has been taken out. If it has been taken out, send a second control instruction to the storage compartment control unit; if it has not been taken out, do not send it. The second control instruction is used to indicate the storage compartment to be closed.

[0050] Further, the main control unit is further configured to receive a touch control signal returned by the display unit; the touch control signal is a signal generated by a target object based on touching the display unit.

[0051] Further, the meal delivery system further includes a status indication module, and the status indication module is used to indicate the operating status of the power supply unit and / or the storage compartment control unit.

[0052] The beneficial effects of the present invention are as follows:

[0053] On the one hand, the power system of the present invention can intelligently control the meal delivery vehicle to drive to the target position when receiving a target control instruction including position information of the target position. On the other hand, based on its meal delivery system, when the meal delivery vehicle drives to the target position, it can automatically identify the target object at the target position and provide a meal delivery service to the target object, thereby reducing labor input and improving meal delivery efficiency. Moreover, since the meal delivery vehicle can deliver meals without relying on manual labor, delivering meals based on this meal delivery vehicle can also improve the safety factor when delivering meals in a complex working environment, such as a coal mine underground working environment, and reduce safety risks. Description of the Drawings

[0054] Figure 1 It is a schematic structural diagram of a meal delivery vehicle provided by an embodiment of the present disclosure;

[0055] Figure 2 It is an electrical block diagram of a meal delivery vehicle provided by an embodiment of the present disclosure;

[0056] Figure 3 It is a flowchart of the meal delivery process of the meal delivery vehicle provided by an embodiment of the present disclosure;

[0057] Figure 4 It is a flowchart of a method for delivering meals underground in a coal mine provided by an embodiment of the present disclosure;

[0058] Figure 5 It is a schematic structural diagram of the meal delivery vehicle body provided by an embodiment of the present disclosure. Detailed Embodiments

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0060] Embodiment 1: Please refer to Figure 1 and 2 , the present invention provides an unmanned food delivery vehicle applicable to coal mines underground, including a food delivery vehicle body and a power system and a food delivery system applied to the food delivery vehicle body; the power system is used to receive a target control instruction, determine a target position and generate a predetermined navigation path, and control the food delivery vehicle body to travel to the target position; the food delivery system is used to provide a food delivery service when the food delivery vehicle body travels to the target position; the power system includes an obstacle avoidance module, and the obstacle avoidance module is used to control the food delivery vehicle body to avoid obstacles; the obstacle avoidance module includes an environment perception unit, and the environment perception unit is used to collect obstacle information and target position matching information during the travel of the food delivery vehicle body; the power system further includes a braking module, and the braking module is used to generate a braking instruction according to the obstacle information or the target position matching information, control the food delivery vehicle body to start braking based on the initial braking acceleration, and divide the braking process based on an equal-length time period, iterate and calculate the state information of the food delivery vehicle body at the end node of each time period according to the initial speed of the food delivery vehicle body, output the braking acceleration of the next time period based on the state information of the food delivery vehicle body, and control the food delivery vehicle body to brake smoothly; the state information of the food delivery vehicle body includes the real-time speed and the cumulative braking distance.

[0061] In an embodiment of the present invention, when the food delivery vehicle body performs unmanned food delivery, since the established navigation path for food delivery is constructed by the navigation module based on the current position of the food delivery vehicle body, which can be understood as the position where the food delivery vehicle body loads the food, and the target position. Due to the changeable environment in the coal mine, there may be changes in environmental information and obstacles in the established navigation path. For example, there may be scattered coal mines on the established navigation path, and the path may be blocked by collapsed coal mines due to terrain changes. If the established navigation path is truncated due to coal mine collapse, it is necessary to control the food delivery vehicle body to start braking based on the braking module to avoid collision problems caused by the food delivery vehicle body not braking in time. In this embodiment, emergency braking will cause the food in the food delivery vehicle to spill, resulting in a poor food delivery service experience. Based on this, in this embodiment, when generating a braking instruction according to obstacle information or target position matching information, the entire braking process can be divided based on an equal-length time period, and the state information of the food delivery vehicle body is collected at the end node of each time period. The state information of the food delivery vehicle body includes the real-time speed and the cumulative braking distance. To ensure the smooth braking of the food delivery vehicle body, the braking acceleration of adjacent time periods should not have too large a span. Based on the state information of the food delivery vehicle body, the braking acceleration of the next time period is calculated, and the braking force of the food delivery vehicle body is controlled based on the calculated braking acceleration, so as to avoid food spillage and affect the service experience. Among them, the obstacle information refers to the information generated when an obstacle is recognized during the process of the food delivery vehicle body driving along the established navigation path, and the target position matching information refers to the information generated when the food delivery vehicle body is about to reach the target position;

[0062] In addition, it should be noted that in some embodiments, the environment perception unit may include multiple environment perception sensors, such as radar, camera, and infrared sensors, etc., to detect the obstacles and environmental change information around the vehicle in real time. The obstacle information obtained based on the environment perception unit is not only used to participate in the obstacle avoidance of the food delivery vehicle body, but also the obstacle information can be recorded and stored in the data storage module. By interconnecting the data storage module with the control device through the communication module, it is possible to record the obstacles when they are discovered, and the background management personnel can record the obstacle information based on the control device and optionally clean up the obstacles to ensure the normal passage of the coal mine underground passage.

[0063] It should be noted that the target control instruction can be an instruction for indicating the target position of the food delivery vehicle body sent by a control device corresponding to the food delivery vehicle body. Such a control device can be, for example, a device running a control application of the food delivery vehicle body, such as a mobile phone, a computer, a server, etc., and no special limitation is made here. It can be understood that when the target control instruction is issued by a control device corresponding to the food delivery vehicle body, the food delivery vehicle body can also include a communication module. In some embodiments, the communication module can be set in the power system, or can also be set as needed, and no special limitation is made here. In some embodiments, the target control instruction can also be issued by an operator by directly setting it on the food delivery vehicle body, and no special limitation is made here.

[0064] The position information of the target position can be two-dimensional coordinates or three-dimensional coordinates, or can also be identification information of a fixed food delivery position. For example, the position information can be two-dimensional coordinates indicating the position of the target position on a two-dimensional navigation map, or can be three-dimensional coordinates indicating the position of the target position on a three-dimensional navigation map. Or, it can be the identification name of a certain fixed food delivery point. For example, when there are three food delivery points, namely Food Delivery Point 1, Food Delivery Point 2, and Food Delivery Point 3, set in the underground of a coal mine, the position information can be "Food Delivery Point 1" to instruct the food delivery vehicle body to drive to Food Delivery Point 1 and provide food delivery services for the target object at Food Delivery Point 1.

[0065] Embodiment 2: The power system further includes a navigation module; the navigation module is used to determine a predetermined navigation path; the obstacle avoidance module further includes an obstacle avoidance path planning unit for planning an obstacle avoidance path.

[0066] The method for controlling the food delivery vehicle body to avoid obstacles is as follows:

[0067] When there is an obstacle on the predetermined navigation path, the environmental perception unit collects the obstacle information and sends it to the obstacle avoidance path planning unit.

[0068] The obstacle avoidance path planning unit generates an obstacle avoidance path based on the obstacle information; the obstacle information carries the volume and position information of the obstacle.

[0069] Send the obstacle avoidance path to the navigation module.

[0070] The navigation module generates a real-time navigation path based on the fusion of the obstacle avoidance path and the predetermined navigation path.

[0071] Due to the ever-changing environment in the coal mine underground, there may be changes in environmental information and obstacles in the established navigation path. For example, there may be scattered coal mines on the established navigation path, and the path may be blocked by collapsed coal mines due to terrain changes. When the obstacle does not block the entire established navigation path, the obstacle avoidance module can analyze the walkable area around the obstacle based on the identified obstacle information and generate an obstacle avoidance path. The obstacle avoidance path is an alternative path for a section of the path with obstacles in the established navigation path. Integrating the obstacle avoidance path into the established navigation path can update the established navigation path, that is, generate a real-time navigation path, and then send the real-time navigation path to the motion execution mechanism, so that the meal delivery vehicle body has the obstacle avoidance ability. Further, it can be understood that assuming an obstacle is identified at any position in the established navigation path and the obstacle does not affect passing through this area, the obstacle avoidance module generates an alternative path adjacent to the obstacle based on the volume, position of the obstacle, and the walkable area around the obstacle, and sends the alternative path to the navigation module to update the established navigation path to generate a real-time navigation path; among them, the navigation module can locate the real-time position of the meal delivery vehicle based on various technologies such as an inertial navigation module (INS, Inertial Navigation System), a lidar (LiDAR, Light Detection and Ranging), and ultrasonic sensors, and realize the position of the meal delivery vehicle body in specific working conditions such as the coal mine working environment and provide navigation services;

[0072] In addition, when the meal delivery vehicle body is applied to underground coal mine operations, the navigation module can automatically plan the optimal real-time navigation path according to the underground road information, the obstacle avoidance path sent by the obstacle avoidance path planning unit, and the target position, so as to ensure that the vehicle can provide meal delivery services efficiently and safely;

[0073] In one embodiment, the power system further includes a motion execution mechanism, which is used to receive the established navigation path and the real-time navigation path, and drive the meal delivery vehicle body to the target position based on the established navigation path and the real-time navigation path.

[0074] In some embodiments, the motion execution mechanism may include a drive system and a chassis stability system. Among them, the drive system can be a high-performance motor or a hydraulic drive system, and is used to provide motion control for the forward, backward, and turn signals of the meal delivery vehicle body; the chassis stability system can include a suspension system, a tire anti-skid system, etc., to ensure that the meal delivery vehicle body can maintain a stable driving posture under different geological conditions.

[0075] It can be understood that as Figure 2As shown, the power system further includes a power supply system, which may include a battery pack and an energy management system. Among them, the battery pack can be a high-capacity and high-energy-density battery pack to provide continuous power supply for the food delivery vehicle body; the energy management system can be used to intelligently detect the battery state and optimize energy distribution to extend the vehicle's cruising range.

[0076] In one embodiment, the method for starting and braking the food delivery vehicle body is as follows:

[0077] Obtain the current real-time speed V(t) of the food delivery vehicle body based on the motion execution mechanism;

[0078] Construct a braking logic algorithm, expressed by the formula:

[0079]

[0080] where a(t) is the braking acceleration calculated by the braking logic algorithm; K p is the proportional gain, used to determine the proportional relationship between the braking acceleration and the speed error; K i is the integral gain, used to eliminate the error changing with time; K d is the differential gain, used to predict the change trend of the error; e(t) is the difference between the target speed and the real-time speed; represents the cumulative error, denoted by E(t); is the error change rate;

[0081] Set the time period T for iterative update of the braking acceleration a(t);

[0082] e(t) = V(t) - Vtarget = V(t)

[0083]

[0084] where Vtarget is the target speed; t represents any period, and t - T represents the previous period;

[0085] Based on the above formula, calculate the braking acceleration a(t) that changes with time;

[0086] For the real-time speed of the food delivery vehicle body and the cumulative braking distance of the food delivery vehicle body, it is expressed as:

[0087] V(t) = V(t - T) - a(t - T)·T

[0088]

[0089] where S(t) is the cumulative braking distance at time t.

[0090] When the food delivery vehicle body recognizes that the established navigation path is truncated, it controls the food delivery vehicle body to start braking based on the braking module, thereby avoiding the collision problem caused by the failure of the food delivery vehicle body to brake in time. In addition, since the food delivery vehicle body is loaded with meals, if the food delivery vehicle body brakes suddenly when it is too close to the truncated position, it will inevitably cause the meals loaded in the food delivery vehicle body to fall over. To avoid the above problems, in an embodiment of the present invention, when the food delivery vehicle body recognizes that the established navigation path is truncated, a braking logic algorithm is started. Based on the braking logic algorithm and the initial speed of the food delivery vehicle body, the braking acceleration for the next time period is determined at the end node of each time period. By iteratively updating the braking acceleration of the food delivery vehicle body, the phased adjustment of the braking acceleration of the food delivery vehicle body is realized, and the braking of the food delivery vehicle body during the entire braking process is kept stable and smooth, thereby avoiding the meals in the food delivery vehicle body from falling over due to sudden braking;

[0091] Exemplarily, assume that when the food delivery vehicle body recognizes that the established navigation path is truncated, the initial speed of the food delivery vehicle body is V(0) = 1 m / s;

[0092] Taking 3 time periods as an example, based on testing, set K p = 0.2, K i = 0.2, K d = 0.1;

[0093] The first time period, i.e., t = T = 0.5 s;

[0094] Calculate the current error e(T):

[0095] e(T) = V(T) - Vtarget = V(T) - 0 = 0.9 m / s

[0096] At the end of the first time period, the speed of the food delivery vehicle body changes from V(0) to V(T), so the current error e(T) at this time = V(T);

[0097] Calculate the integral term E(T):

[0098] E(T) = E(T - T) + V(T - T)·T = E(0) + V(0)·T = 0.5

[0099] Since E(t) represents the cumulative error, so E(0) = 0, then E(T) = V(0)·T;

[0100] Calculate the differential term

[0101]

[0102] Since at the end of the first time period, the speed of the food delivery vehicle body changes from V(0) to V(T);

[0103] Based on the above, the braking acceleration a(T) is expressed as:

[0104]

[0105] where K p 、K i and K d are not limited in units and are used to maintain dimensional consistency. At the start of the above first time period, the speed of the food delivery vehicle body and the cumulative braking distance of the food delivery vehicle body. Let a(0) = 0.2 and it is expressed as:

[0106] V(T) = V(0) - a(0)·T = 1 - 0.2·0.5 = 0.9m / s

[0107]

[0108] Since it is calculated from the first time period, the braking acceleration is the previous time period, that is, the initial braking acceleration, which is the preset value a(0). Therefore, the cumulative braking distance is 0, so S(0) = 0. Based on the above formula calculation, that is to say, 1s before the first time period, based on the preset braking acceleration, the speed of the food delivery vehicle body drops to 0.8m / s and the cumulative braking distance is 0.9m;

[0109] And so on:

[0110] The second time period, i.e., t = 2T;

[0111] Calculate the current error e(2T):

[0112] e(2T) = V(2T) - Vtarget = V(2T) = 0.77m / s

[0113] Calculate the integral term E(2T):

[0114] E(2T) = E(T) + V(T)·T = (V(0) + V(T))·T = 0.95 Calculate the differential term

[0115]

[0116] Based on the above, the braking acceleration a(2T) is expressed as:

[0117]

[0118] where the speed and the cumulative braking mileage at the start of the second time period are expressed as:

[0119] V(2T) = V(T) - a(T)·T = 0.9 - 0.26·0.5 = 0.77 m / s

[0120]

[0121] The third time period, i.e., t = 3T;

[0122] V(3T) = 0.611

[0123] e(3T) = 0.611

[0124] E(3T) = 1.155

[0125]

[0126] a(3T) = 0.3214

[0127] S(3T) = 1.23775

[0128] The fourth time period, i.e., t = 4T;

[0129] V(4T) = 0.4503

[0130] e(4T) = 0.4503

[0131] E(4T) = 1.38015

[0132]

[0133] a(4T) = 0.33395

[0134] S(4T) = 1.503075

[0135] The fifth time period, i.e., t = 5T;

[0136] V(5T) = 0.283325

[0137] e(5T) = 0.283325

[0138] E(5T) = 1.5218125

[0139]

[0140] a(5T) = 0.32888

[0141] S(5T) = 1.68648125

[0142] The sixth time period, i.e., t = 6T;

[0143] V(6T) = 0.118885

[0144] e(6T) = 0.118885

[0145] E(6T) = 1.663475

[0146]

[0147] a(6T) = 0.323584

[0148] S(6T) = 1.78703375

[0149] The seventh time period, i.e., t = 7T;

[0150] V(7T) = -0.042907

[0151] Based on this, it shows that in the seventh time period, the speed of the food delivery vehicle body drops to 0;

[0152] S(7T) = 1.80602825

[0153] Based on the above, when the food delivery vehicle body recognizes that the established navigation path is truncated, it immediately activates the braking logic algorithm, divides the time period according to the current real-time speed of the food delivery vehicle body, and optimizes and adjusts the braking acceleration for the next time period according to the speed of the food delivery vehicle body at the end of each time period, so as to ensure that the span of the braking acceleration of the food delivery vehicle body in each time period is relatively small and will not cause the food in the food delivery vehicle body to spill; it should be noted that within each of the above time periods, the cumulative braking distance of the food delivery vehicle body is calculated. The cumulative braking distance can be understood as the moving distance of the food delivery vehicle body from the start of braking to when the speed drops to 0. Since when the food delivery vehicle body recognizes that the established navigation path is truncated, if its distance from the truncated position is relatively close, special attention needs to be paid to the cumulative braking distance, and after each time period, compare whether the cumulative braking distance exceeds the maximum braking distance to prevent the food delivery vehicle body from colliding with the truncated position or falling into the truncated position before it stops; when the cumulative braking distance gradually approaches the maximum braking distance, the prediction algorithm can be used, that is, simulate the braking acceleration of the next time period according to the braking acceleration of the previous time period, to verify whether the cumulative braking distance of the food delivery vehicle body in the next time period exceeds the maximum braking distance. If so, increase the braking acceleration of the food delivery vehicle body in the next time period, otherwise keep it unchanged;

[0154] It should also be noted that the braking module brakes the food delivery vehicle body based on the braking logic algorithm. In addition to dealing with obstacles, it also includes braking when the food delivery vehicle body is about to reach the target position. Based on the above, the environmental perception unit collects obstacle information and target position matching information. The target position matching information is used for braking when the food delivery vehicle body is about to reach the target position. It can be understood that the target position can be preset as a simulated obstacle, and the braking acceleration during the entire braking process of the food delivery vehicle body can be iteratively updated according to the same braking logic algorithm, that is, the braking acceleration is adjusted to ensure that the food delivery vehicle body can reach the target position smoothly and achieve braking. Based on this, in one embodiment, it can be understood that when the food delivery vehicle travels based on the established navigation path or the real-time navigation path, a maximum driving speed is set. Based on this braking logic algorithm, the acceleration of the food delivery vehicle body can be adjusted periodically until the speed of the food delivery vehicle body reaches the set maximum driving speed. Similarly, maintain the set maximum driving speed until it is about to reach the target position, and then start the braking logic algorithm to adjust the braking acceleration of the food delivery vehicle body.

[0155] In one embodiment, the power system further includes an environmental parameter collection module. The environmental parameter collection module is used to detect the environmental parameters in the area where the food delivery vehicle body is located and send the collected environmental parameters to the explosion-proof module.

[0156] The environmental parameters include at least one of the following: temperature parameter, humidity parameter, and gas concentration parameter; the gas concentration parameter includes methane gas concentration.

[0157] Due to the complex environment in the coal mine underground and due to irresistible factors, environmental changes may occur. For the gas concentration parameter, in this embodiment, it is mainly used to represent methane. In addition, it also includes the gas concentrations of carbon monoxide, carbon dioxide, hydrogen sulfide, nitrogen, and oxygen.

[0158] Among them, when the methane concentration exceeds 0.5mg / L, an explosion may occur. For the working environment in the coal mine underground, the methane concentration exceeding the threshold is the most dangerous. If an explosion occurs, huge losses will be caused in an instant. Based on this, in this embodiment, the gas concentration parameter is mainly used to represent the gas concentration of methane; while carbon monoxide and hydrogen sulfide are highly toxic and easily cause casualties; high concentrations of carbon dioxide and nitrogen will cause oxygen deficiency. After the environmental parameter collection module collects the environmental parameters in the area where the food delivery vehicle body is located, the collected environmental parameters are sent to the explosion-proof module as a prerequisite for the explosion protection of the food delivery vehicle body.

[0159] Embodiment 3: The food delivery system includes an explosion-proof module. The explosion-proof module includes a power supply unit, a main control unit, and a display unit; the main control unit includes an intrinsically safe circuit board, and the power supply unit includes an intrinsically safe power supply. The intrinsically safe power supply is connected to the intrinsically safe circuit board.

[0160] The explosion-proof module further includes an analysis unit for judging whether there are potential hazards in the area where the meal delivery vehicle body is located based on environmental parameters, including:

[0161] If the methane gas concentration exceeds the threshold, a warning prompt is generated, and

[0162] Obtain the change trend of the methane gas concentration with the driving of the meal delivery vehicle, determine the position with the maximum methane gas concentration as the methane leakage point, construct an excessive methane coverage area based on the methane leakage point, and judge whether the target position is within the excessive methane coverage area:

[0163] If the target position is within this range, an evacuation prompt is generated synchronously;

[0164] Both the warning prompt and the evacuation prompt are sent by the analysis unit to the display unit.

[0165] Due to the complex environment in the coal mine underground, there are many road branches, and there may also be flammable and explosive substances such as gas and coal dust. Therefore, considering specific working conditions, for example, when the meal delivery vehicle body is applied to underground coal mine operations, since there may be flammable and explosive substances such as methane and coal dust in the coal mine underground, for this reason, to improve the safety during the meal delivery process, the meal delivery vehicle body provided by the embodiments of the present disclosure further includes an explosion-proof module. In this explosion-proof module, by using an intrinsically safe circuit board as the main control unit of the meal delivery vehicle body and constructing a power supply unit of the meal delivery vehicle body based on an intrinsically safe power supply, the safety of the meal delivery vehicle body under dangerous working conditions can be greatly improved, thereby ensuring the efficient and safe provision of meal delivery services to the target object; based on the above, the acquisition of environmental parameters in the coal mine underground is a prerequisite for maintaining underground operations, and since the meal delivery vehicle body needs to move, it is also necessary to pay attention to whether the meal delivery vehicle body will pass through areas with potential hazards during the movement process, or whether the meal delivery vehicle body stays in areas with potential hazards. If there are potential hazard areas, such as high-concentration methane, there may be an explosion risk. Through the acquisition of environmental parameters, abnormal environmental parameters can be effectively identified and corresponding treatment measures can be taken to reduce the risk.

[0166] In one embodiment, during the driving process of the food delivery vehicle body based on a predefined navigation path or a real-time navigation path, if the collected methane gas concentration exceeds the standard, it indicates that there may be a significant risk of explosion when delivering food at this location. Therefore, the food delivery vehicle body can generate a warning prompt and an evacuation prompt based on the display unit to warn the miners waiting to pick up the food and guide them to respond quickly, including adjusting the ventilation equipment and immediately evacuating this area. Specifically, after comparing the methane gas concentration with the concentration threshold, if it is determined that the methane gas concentration exceeds the concentration threshold, it means that the methane gas concentration exceeds the standard. In this case, since methane gas has fluidity, after identifying that the methane gas concentration exceeds the standard, it is still impossible to determine whether the target location is within the range of the excessive methane gas. Therefore, it is also necessary to obtain the methane gas concentration that changes with the displacement of the food delivery vehicle body and determine the maximum methane gas concentration as the vehicle body moves. The position point where the maximum methane gas concentration is located is taken as the methane leakage point, and then based on the position point of the excessive methane gas concentration initially identified by the food delivery vehicle body, a coverage area of the excessive methane gas based on the methane leakage point is constructed, generally in a hemispherical structure, and it is analyzed whether the target location is within the coverage area of the excessive methane gas. If the target location is within this range, an evacuation prompt is generated synchronously, indicating that food delivery cannot be carried out at the target location. If the methane gas concentration does not exceed the threshold, normal food delivery services are provided.

[0167] In one embodiment of the present invention, the main control unit and the power supply unit in the food delivery system of the food delivery vehicle body can be intrinsically safe electrical units. It should be noted that intrinsic safety, also known as inherently safe, is an explosion-proof type of electrical equipment. This type limits various parameters of the electrical equipment circuit or takes protective measures to limit the spark discharge energy and heat energy of the circuit, so that the electric sparks and thermal effects generated under normal working conditions and specified fault conditions cannot ignite the explosive mixture in the surrounding environment.

[0168] In one embodiment, the food delivery system further includes an identity recognition module; the main control unit is connected to the identity recognition module.

[0169] When the food delivery vehicle body reaches the target location, the identity recognition module performs identity recognition processing on the target object at the target location; the target object is the object to be provided with food delivery services.

[0170] If the identity recognition is successful, an identity confirmation message is generated; otherwise, it is not generated.

[0171] To ensure that the food delivery vehicle body can accurately deliver the meals to the hands of the target object, identity recognition is also required. In this embodiment, the identity recognition module can be used to perform identity recognition processing on the target object. This identity recognition processing can, for example, identify the target object by collecting the identity recognition card held by the target object, or it can also perform identity recognition processing on the target object in other ways, and no special limitation is made here.

[0172] In some embodiments, considering the working conditions in the coal mine underground, the face of the target object, such as a miner, may often be polluted by dust from coal mines, etc., and the light conditions underground are often poor. Therefore, in order to enable the food delivery vehicle body to accurately identify the target object to improve the accuracy of the food delivery service, the identity recognition module can be a module integrated with three-dimensional (3D) face recognition service. With the consent of the target object to authorize the collection of their facial images, this identity recognition module can collect the facial images of the target object through an image acquisition device, such as a camera, and perform face recognition processing on the facial images based on the 3D face recognition algorithm. Compared with other identity recognition processing, using the identity recognition module integrated with 3D face recognition service to perform identity recognition processing on the target object enables the food delivery vehicle body to easily identify the target object and is almost not affected by the intensity of light, so as to accurately identify the identity of the target object for accurate food delivery service. Specifically, based on the image acquisition device to collect the facial images of the miners, if the recognition is successful, an identity confirmation message is sent, otherwise not sent, indicating that the recognition is not successful;

[0173] The target object refers to the object to which the food delivery service is to be provided. This target object can, for example, be a miner working underground in a coal mine. Of course, in actual implementation, the target object can be set according to needs. For example, it can also be an animal to which the food delivery service is to be provided, and no special limitation is made here.

[0174] In one embodiment, the food delivery vehicle body includes n storage compartments, where n≥1; the explosion-proof module also includes a storage compartment control unit, and the storage compartment control unit includes m intrinsically safe motors, where m≥1;

[0175] The main control unit is connected to the storage compartment control unit and is also used to control the opening and closing states of the n storage compartments based on the m intrinsically safe motors;

[0176] The method for controlling the opening and closing states of the storage compartments based on the storage compartment control unit is as follows:

[0177] The main control unit is based on the identity confirmation information generated by the identity recognition module;

[0178] Based on the identity confirmation information, obtain the mapping relationship between the food needs of the target object and the storage compartments;

[0179] Send a first control instruction to the storage compartment control unit based on the mapping relationship; the first control instruction is used to indicate the storage compartment to be opened;

[0180] Determine whether the meal has been taken out. If it has been taken out, send a second control instruction to the storage compartment control unit; if it has not been taken out, do not send it. The second control instruction is used to indicate the storage compartment to be closed.

[0181] In the embodiments of the present disclosure, each storage compartment can be used to store food so as to accurately provide food for the target object when the meal delivery vehicle body reaches the target location. Specifically, when the main control unit receives the identity confirmation information generated by the identity recognition module, it obtains the mapping relationship between the food requirements of the target object and the storage compartments. In one embodiment, the mapping relationship between the target object and the storage compartments includes one-to-one and one-to-many mapping relationships. Specifically, when the food requirement of the target object is A, the storage compartment corresponding to the food requirement of A will be opened after successful recognition. If the food requirement of the target object is A + B, the storage compartments with food requirements of A and B respectively will be opened after successful identity recognition.

[0182] In some embodiments, the temperatures of the n storage compartments are different. That is, considering that different foods have different temperature requirements during transportation, therefore, the n storage compartments of the meal delivery vehicle body provided in the embodiments of the present disclosure can be storage compartments in different temperature zones respectively. For example, they can respectively include storage compartments for storing frozen, refrigerated, hot food, etc. In some embodiments, the temperature of each storage compartment can be set to better adapt to the storage requirements of different foods, so that the meal delivery vehicle body can provide food with better taste for the target object.

[0183] Specifically, the meal delivery vehicle body can include, for example, 4 storage compartments, and can include 2 storage compartment control units including intrinsically safe motors. Each storage compartment control unit can independently control the opening and closing states of 2 storage compartments. Of course, in actual implementation, the number of storage compartments and storage compartment control units can also be set as needed. For example, m can be equal to n, that is, m = n. In this implementation case, the main control unit can independently control the opening and closing states of each storage compartment based on m intrinsically safe motors.

[0184] That is, considering that the meal delivery vehicle body may provide meal delivery services for multiple objects at the same or different locations, therefore, to avoid the situation where the food is contaminated due to multiple openings and closings of only one storage compartment, the meal delivery vehicle body provided in the embodiments of the present disclosure can include multiple storage compartments to achieve separate storage of food, avoid frequent opening of the same storage compartment and cause food contamination, ensure the safety and hygiene of food, and at the same time can also meet the dietary needs of different target objects under different working conditions to improve the work efficiency and satisfaction of the target objects.

[0185] In this embodiment, the main control unit can also be configured to send a first control instruction to the storage compartment control unit corresponding to the storage compartment of the target object when receiving the identity confirmation information sent by the identity recognition module. In actual implementation, it can be set that when the food delivery vehicle body determines the identity of the target object, the storage compartment corresponding to the target object is automatically opened to reduce the manual operation of the target object and improve their dining satisfaction. It can be understood that when the food delivery vehicle body is set to automatically open the storage compartment, when the food delivery vehicle body detects that the target object has taken the food, the main control unit can send a second control instruction to the storage compartment control unit corresponding to the storage compartment of the target object.

[0186] In one embodiment, the main control unit is further configured to receive a touch control signal returned by the display unit; the touch control signal is a signal generated by the target object based on touching the display unit.

[0187] It should be noted that in actual implementation, to avoid misoperation, the control mode of the storage compartment can also be set to "automatic mode" or "manual mode" in advance. If it is in "manual mode", when the main control unit determines the identity information of the target object, it also needs to receive an instruction issued by the target object through the display unit, that is, a touch control signal generated by the target object touching the display unit, or an instruction generated by the interaction button corresponding to the storage compartment. Here, the display unit is a touch screen. After the display unit generates a touch control signal, it will be sent to the main control unit, and the main control unit will send a corresponding control instruction to the storage compartment control unit corresponding to the storage compartment based on the identity confirmation information of the target object to control the opening and closing state of the storage compartment.

[0188] In addition, in the manual mode, it can also include n interaction buttons for opening or closing the n storage compartments. Based on the operation of the interaction buttons by the target object, interaction control information is generated and sent to the main control unit. Each interaction button corresponds to each storage compartment one by one.

[0189] In one embodiment, the food delivery system further includes a status indication module, and the status indication module is used to indicate the operating status of the power supply unit and / or the storage compartment control unit.

[0190] Please refer to Figure 2 , the power supply unit in the electrical system of the food delivery system of the food delivery vehicle body provided by the embodiments of the present disclosure can use intrinsically safe 12V as the main external power supply, and ensure voltage stability and protect system safety through a voltage regulation / protection circuit;

[0191] The main control unit can be connected to the screen driver board of the display unit through the RS485 interface. This screen driver board can be connected to the display screen in the display unit through the LVDS interface, so as to realize information display and touch control. The display screen is the above-mentioned display unit and touch screen. In addition, the main control unit can communicate with the face recognition core board in the identity recognition module through the UART interface to cooperate with the image acquisition device, such as a 3D camera, to perform identity recognition processing on the target object.

[0192] In addition, as Figure 2 shown, the electrical system can also include multiple interface circuits for signal interaction with external devices or sensors. For example, the status indication module can include status indicator lights for displaying the operating status of the power supply unit, the operating status of the motors in each storage compartment control unit, etc., to facilitate the user and the control application corresponding to the food delivery vehicle body to detect the operating status of the food delivery vehicle body.

[0193] Embodiment 4: As Figure 3 shown, before the food delivery vehicle body provided based on the embodiment of the present disclosure executes the food delivery operation, it also needs to perform self-check. It can first execute step S41 to start the self-check and system initialization process. In this step S41, the main control unit can perform the self-check process, and then, initialize each peripheral device of the vehicle, such as the image acquisition device, the display unit, etc., and can also set the operating mode of the food delivery vehicle body to "manual mode" or "automatic mode".

[0194] After step S41, execute step S42 to detect the health status of the display unit and the image acquisition device. In this step S42, the food delivery vehicle body can perform fault detection on its display unit and image acquisition device. If any unit is found to have a fault, it can generate and send a fault message to the operation and maintenance user corresponding to the food delivery vehicle body. For example, execute step S421 to detect whether there is a fault in the display unit; if so, execute step S422, and the status indication module indicates a display unit fault; if not, step S423 can be executed to detect whether there is a fault in the image acquisition device; if so, execute step S424, and the status indication module indicates an image acquisition device fault; if not, execute the subsequent steps.

[0195] After step S42, the food delivery vehicle body can perform the food delivery service. When the food delivery vehicle body travels to the target position, step S43 can be executed to determine whether it is in the "automatic mode"; if so, step S44 can be executed to perform identity recognition processing on the target object to determine whether the recognition is successful; if the recognition is successful, step S45 is executed, and the display unit marks the opening / closing area for the user to select; when the user confirms the selection, step S46 is executed to control the corresponding storage compartment control unit to open / close the corresponding storage compartment; during the execution of step S46, step S47 can be executed to detect whether there is a fault in the motor of the storage compartment control unit; if so, step S48 is executed, and the status indication module indicates a fault in the storage compartment control unit; if not, step S49 is executed to detect whether the click of the storage compartment control unit is in place; if it is in place, step S50 is executed, and the display unit displays the current open / closed state of the storage compartment.

[0196] It can be understood that after step S43, if it is determined that the food delivery vehicle body is not in the "automatic mode", step S51 can be executed to receive the control instruction sent by the interaction button for controlling the storage compartment of the target object; then, based on this control instruction, the process after step S45 is executed, and the detailed processing is not described here.

[0197] It can be seen that based on the food delivery vehicle body provided by the embodiments of the present disclosure, by integrating multiple subsystems such as high-precision navigation, intelligent obstacle avoidance, a stable motion execution mechanism, and safety environment monitoring, it is possible to accurately identify the target object, improve the food delivery accuracy of the food delivery vehicle body, as well as improve the food delivery efficiency and safety factor. In particular, it can improve its food delivery efficiency and safety factor in complex working conditions, such as the working environment underground in coal mines.

[0198] Corresponding to the food delivery vehicle provided in the above embodiments, the embodiments of the present disclosure also provide a method for delivering food underground in a coal mine. Please refer to Figure 4 , which is a flowchart of a method for delivering food underground in a coal mine provided by the embodiments of the present disclosure. This method can be applied to the food delivery vehicle provided in any of the above embodiments. As Figure 4 shown, this method includes the following steps S51 - S52.

[0199] Step S51, when receiving the target control instruction, control the food delivery vehicle to travel to the target position, and the target control instruction includes the position information of the target position;

[0200] Step S52, when it is determined that the food delivery vehicle has traveled to the target position, identify the target object within the target position range and provide food delivery service to the target object.

[0201] Based on the meal delivery method provided by the embodiments of the present disclosure, the meal delivery efficiency and safety in the underground coal mine working environment can be improved, and the work efficiency and satisfaction of miners can be enhanced.

[0202] Embodiment 5: Please refer to Figure 5 , the meal delivery vehicle body has traveling wheels for self - movement, and a meal - loading space for accommodating meals is provided inside it.

[0203] It should be noted that if there are directional indications such as up, down, left, right, front, rear... involved in the embodiments of the present invention, the directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture as shown in the drawings. If the specific posture changes, the directional indications will also change accordingly.

[0204] In addition, if there are descriptions such as "first", "second", etc. involved in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second" may explicitly or implicitly include at least one such feature. In addition, the meaning of "and / or" appearing throughout the text includes three parallel solutions. Taking "A and / or B" as an example, it includes solution A, or solution B, or the solution where A and B are satisfied simultaneously. In addition, "a plurality" means more than two. In addition, the technical solutions between various embodiments can be combined with each other, but it must be based on the fact that those skilled in the art can implement it. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist.

[0205] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. An unmanned food delivery vehicle applicable to underground coal mines, characterized in that , including the food delivery vehicle body and a power system and a food delivery system applied to the food delivery vehicle body; The power system is used to receive a target control instruction, determine a target position and generate a predetermined navigation path, and control the food delivery vehicle body to travel to the target position; The power system includes an obstacle avoidance module and a braking module. The obstacle avoidance module is used to control the food delivery vehicle body to avoid obstacles. The braking module is used to generate a braking instruction according to the obstacle information or the target position matching information, control the food delivery vehicle body to start braking based on the initial braking acceleration, divide the braking process based on an equal-length time period, iteratively calculate the state information of the food delivery vehicle body at the end node of each time period according to the initial speed of the food delivery vehicle body, and output the braking acceleration of the next time period based on the state information of the food delivery vehicle body to control the food delivery vehicle body to brake smoothly. The food delivery system is used to provide a food delivery service when the food delivery vehicle body travels to the target position.

2. The driverless food delivery vehicle applicable to underground coal mines according to claim 1, wherein: The obstacle avoidance module includes an environment perception unit and an obstacle avoidance path planning unit. The environment perception unit is used to collect the obstacle information and the target position matching information during the driving process of the food delivery vehicle body. The obstacle avoidance path planning unit is used to plan an obstacle avoidance path; The power system further includes a navigation module; the navigation module is used to determine a predetermined navigation path; Among them, the method for controlling the food delivery vehicle body to avoid obstacles includes, When there is an obstacle on the predetermined navigation path, the environment perception unit collects the obstacle information and sends it to the obstacle avoidance path planning unit; The obstacle avoidance path planning unit generates an obstacle avoidance path based on the obstacle information; the obstacle information carries the obstacle volume and position information; Send the obstacle avoidance path to the navigation module; The navigation module generates a real-time navigation path based on the fusion of the obstacle avoidance path and the predetermined navigation path.

3. The driverless food delivery vehicle applicable to underground coal mines according to claim 2, wherein: The power system further includes a motion execution mechanism. The motion execution mechanism is used to receive the predetermined navigation path and the real-time navigation path, and drive the food delivery vehicle body to travel to the target position based on the predetermined navigation path and the real-time navigation path.

4. The driverless food delivery vehicle applicable to underground coal mines according to claim 1, wherein: The method for the food delivery vehicle body to start braking includes, Obtain the current real-time speed V(t) of the food delivery vehicle body based on the motion execution mechanism; Construct a braking logic algorithm, and the formula is expressed as: Among them, a(t) is the braking acceleration calculated by the braking logic algorithm; K p is the proportional gain, used to determine the proportional relationship between the braking acceleration and the speed error; K i is the integral gain, used to eliminate the error varying with time; K d is the derivative gain, used to predict the change trend of the error; e(t) is the difference between the target speed and the real-time speed; represents the cumulative error, denoted by E(t); is the error change rate; Set the time period T for the iterative update of the braking acceleration a(t); e(t) = V(t) - Vtarget = V(t) Among them, Vtarget is the target speed; t represents any period, and t - T represents the previous period; Based on the above formula, calculate the braking acceleration a(t) that changes with time; For the real-time speed of the food delivery vehicle body and the cumulative braking distance of the food delivery vehicle body, it is expressed as: V(t) = V(t - T) - a(t - T)·T Among them, S(t) is the cumulative braking distance at the cut-off time t.

5. The driverless food delivery vehicle applicable to underground coal mines according to claim 3, wherein: The power system further includes an environmental parameter collection module. The environmental parameter collection module is used to detect the environmental parameters in the area where the food delivery vehicle body is located, and send the collected environmental parameters to the explosion-proof module; The environmental parameters include at least one of the following: temperature parameter, humidity parameter, and gas concentration parameter; the gas concentration parameter includes methane gas concentration.

6. The driverless food delivery vehicle applicable to underground coal mines according to claim 1, wherein: The food delivery system includes an explosion-proof module, and the explosion-proof module includes a power supply unit, a main control unit, a display unit, and an analysis unit; the main control unit includes an intrinsically safe circuit board, the power supply unit includes an intrinsically safe power supply, and the intrinsically safe power supply is connected to the intrinsically safe circuit board; The analysis unit is used to judge whether there are potential hazards in the area where the food delivery vehicle body is located based on the environmental parameters, including the following steps: If the methane gas concentration exceeds the threshold value, a warning prompt is generated, and Obtain the change trend of the methane gas concentration with the driving of the food delivery vehicle, determine the position with the maximum methane gas concentration as the methane leakage point, construct an excessive methane coverage area according to the methane leakage point, and judge whether the target position is within the excessive methane coverage area: If the target position is within this range, an evacuation prompt is generated synchronously; Both the warning prompt and the evacuation prompt are sent by the analysis unit to the display unit.

7. The driverless food delivery vehicle applicable to underground coal mines according to claim 6, characterized in that: The food delivery system further includes an identity recognition module; the main control unit is connected to the identity recognition module; When the food delivery vehicle body travels to the target position, the target object at the target position is subjected to identity recognition processing based on the identity recognition module; The target object is the object to be provided with food delivery service; When the identity recognition is successful, an identity confirmation message is generated, otherwise it is not generated.

8. The driverless food delivery vehicle applicable to underground coal mines according to claim 1, wherein: The food delivery vehicle body includes n storage compartments, n≥1; the explosion-proof module further includes a storage compartment control unit, and the storage compartment control unit includes m intrinsically safe motors, m≥1; The main control unit is connected to the storage compartment control unit and is also used to control the opening and closing states of the n storage compartments based on the m intrinsically safe motors; Among them, the method for controlling the opening and closing states of the storage compartments based on the storage compartment control unit includes, The main control unit generates an identity confirmation message based on the identity recognition module; Based on the identity confirmation message, obtain the mapping relationship between the food requirements of the target object and the storage compartments; Send a first control command to the storage compartment control unit based on the mapping relationship; the first control command is used to indicate the storage compartment to be opened; Judge whether the meal has been taken out. If it has been taken out, send a second control command to the storage compartment control unit. If it has not been taken out, do not send it; the second control command is used to indicate the storage compartment to be closed.

9. The driverless food delivery vehicle applicable to underground coal mines according to claim 8, characterized in that: The main control unit is also used to receive the touch control signal returned by the display unit; the touch control signal is a signal generated by the target object based on touching the display unit.

10. The driverless food delivery vehicle applicable to underground coal mines according to claim 9, wherein: The food delivery system further includes a status indication module, and the status indication module is used to indicate the operating status of the power supply unit and / or the storage compartment control unit.

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