Boxed emulsion explosive unloading, stacking and carrying method and system

Abstract

The present application relates to a kind of box emulsion explosive unloading stacking handling method and system, handling method includes: handling stacking robot scans box emulsion explosive in transport vehicle cabin, obtains the information of box emulsion explosive placement position;Handling stacking robot moves to optimal unloading position according to the information of box emulsion explosive placement position;Handling stacking robot obtains the information of box emulsion explosive placement position again;According to the information of box emulsion explosive placement position, box emulsion explosive is grabbed using mechanical arm;Mechanical arm shifts box emulsion explosive to receiving transport vehicle;Receiving transport vehicle collects environmental parameters;Real-time analysis processing environmental parameters, the optimal transport path from current position to warehouse designated position is planned;Receiving transport vehicle moves to warehouse, and unloading operation is carried out.The present application realizes the automation operation of box emulsion explosive from unloading to the whole process of stacking handling by machine vision technology and automatic control system, reduces manual intervention, improves operation efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of box-packed emulsion explosive unloading, stacking and handling of civil explosive storage, in particular to a box-packed emulsion explosive unloading, stacking and handling method and system. BACKGROUND

[0002] In the field of explosive production and logistics transportation, the unloading, stacking and handling of box-packed emulsion explosives are crucial. The traditional operation mode mainly relies on manual operation, which has many problems. When unloading manually, workers need to manually move the box-packed explosives from the transport vehicle one by one, which is labor-intensive and inefficient. During the stacking process, the stacking is stacked relying on manual experience, which is not easy to ensure the neatness and accuracy of the stacking, and may also cause the instability of the explosive box during storage, which poses a safety hazard. In addition, during the process of manually handling the explosive box, due to the particularity of the explosive, any carelessness may cause serious safety accidents, posing a great threat to the safety of personnel and enterprise property. SUMMARY

[0003] In order to solve the above problems existing in the prior art, the present application provides a box-packed emulsion explosive unloading, stacking and handling method, comprising:

[0004] S1, a handling and stacking robot scans the box-packed emulsion explosives in the vehicle compartment of the transport vehicle, and obtains the placement position information of the box-packed emulsion explosives.

[0005] S2, the handling and stacking robot adjusts the speed and direction in real time according to the placement position information of the box-packed emulsion explosives, and moves to the best unloading position.

[0006] S3, the handling and stacking robot uses the second image acquisition unit on the mechanical arm to obtain the placement position information of the box-packed emulsion explosives again, including the two-dimensional plane coordinates, depth information and attitude angle information of the box-packed emulsion explosives.

[0007] S4, according to the placement position information of the box-packed emulsion explosives obtained in S3 and the preset stacking rules and sequence, a mechanical arm action instruction is generated, and the box-packed emulsion explosives are grabbed by the mechanical arm.

[0008] S5, the mechanical arm transfers the box-packed emulsion explosives to the receiving transport vehicle and keeps the box-packed emulsion explosives in a horizontal state, and repeats S3-S5 until the transfer of the box-packed emulsion explosives is completed.

[0009] S6, the receiving transport vehicle collects environmental parameters, including terrain, obstacles and warehouse entrance position information.

[0010] S7, the environmental parameters are analyzed and processed in real time, and the optimal transport path from the current position to the designated position of the warehouse is planned in combination with the map and the operation task requirements.

[0011] S8, the receiving and transporting vehicle moves to the designated position of the warehouse and performs unloading operation.

[0012] Further, in S8, the tray rack lifting mechanism on the receiving and transporting vehicle performs lifting operation according to the operation requirement, and if cooperating with the unloading forklift, the height of the tray rack is adjusted according to the height of the forklift tine, and if cooperating with the carrying and stacking robot, the height of the tray rack is adjusted in real time according to the operation height of the mechanical arm.

[0013] Further, in S2, the speed and direction are adjusted in real time by the dynamic path planning and attitude optimization algorithm, the input parameters of the dynamic path planning and attitude optimization algorithm include the box emulsion explosive placement position information data, the input environment parameters and the mechanical arm movement constraint conditions; the box emulsion explosive placement position information data includes two-dimensional plane coordinates x and y, height information z, attitude angle θ, vehicle compartment boundary coordinate information and obstacle position information; the environment parameters include ground friction coefficient μ, site slope α and obstacle dynamic information; the mechanical arm movement constraint conditions include the length of the large arm L1, the length of the small arm L2, the maximum speed of the joint motor ωmax and the maximum clamping force of the mechanical arm Fmax; an improved A* algorithm is adopted, and the cost function of the A* algorithm is f1(n)=g1(n)+h1(n)+λ·SafetyCost(n), in the cost function, g1(n) represents the actual movement cost from the starting point to node n, h1(n) is a heuristic function, SafetyCost(n) is a safety coefficient, which is dynamically adjusted according to the minimum distance between the box emulsion explosive and the obstacle, λ is a dynamic weight coefficient, which is used to balance the priority of the basic cost (such as distance, energy consumption) and the safety cost of the path; the path is dynamically adjusted, and the path is recalculated according to the cost function at a preset interval.

[0014] Further, it also includes mechanical arm attitude optimization, which is based on inverse kinematics and energy minimization, and the inverse kinematics is solved according to two-dimensional plane coordinates x and y, height information z and attitude angle θ, to calculate the pitch angle φ1 of the large arm and the pitch angle φ2 of the small arm, and the calculation method of the pitch angle of the large arm and the small arm is as follows:

[0015]

[0016] φ2=θ-φ1

[0017] The solution that minimizes the total energy consumption of the joint motor is adopted, that is: where k i is the efficiency coefficient of motor i.

[0018] Further, the mechanical arm clamping force Fgrip is self-adaptive, and the clamping force is dynamically adjusted according to the weight m of the box emulsion explosive and the friction coefficient μbox, and the specific operation process is: grip Fgrip=min(1.5·m·g·μbox F max )。

[0019] Further, when the static electricity accumulation exceeds the threshold Q max or the obstacle distance is less than the safety distance, the emergency stop or the path adjustment is triggered.

[0020] Further, in S7, a multi-objective dynamic path planning and cooperative control algorithm is adopted to plan the path, input parameters of the multi-objective dynamic path planning and cooperative control algorithm are environment parameters, state parameters of the receiving and transporting vehicle and task constraints; the environment parameters include terrain elevation h x and O y , warehouse entrance coordinates W x and W y , and dynamic obstacle velocity vectors v x ,v y ; the state parameters of the receiving and transporting vehicle include the current position X current ,Y current of the receiving and transporting vehicle, the tire rotation speed ω tire , and the pallet rack height H pallet ; the task constraints are the topological structure of the preset map, including the path node N i , and the safety distance threshold d safe ; the dynamic path planning module is based on the improved D*Lite algorithm, and the adaptive cost function is f2(n)=g2(n)+ε·h2(n)+γ·DynamicRisk(n), wherein g2(n) is the actual path length considering the tire wear coefficient μ tire , h2(n) is a heuristic function, DynamicRisk(n) is a dynamic risk assessment, ε is a weight coefficient of the heuristic function h(n) and is used to balance the efficiency and optimality of path search, γ is a weight coefficient of the dynamic risk cost DynamicRisk(n) and is used to quantify the influence of environmental dynamic risk on path selection; the path is updated at a preset interval.

[0021] Further, a multi-objective optimization based on the NSGA-II framework is further included, optimization objectives are minimum transportation time, minimum energy consumption, and maximum safety coefficient; the minimum transportation time is calculated in the manner of wherein L i is the length of the segmented path, and vi is the driving speed of the segmented path; the minimum energy consumption is calculated in the manner of ω i is the energy consumption weight coefficient of the segmented path; the maximum safety coefficient is calculated in the manner of d obstacle is the minimum distance between the boxed emulsion explosive and the obstacle; the constraint condition of the objective function is that the rotation angle θ pallet≤45° / s, maximum tire rotation speed ω tire ≤2 rad / s; output parameter is tire steering angle θ steer ∈ [-30°, 30°] and rotation speed ω tire ∈ [0.5, 2] rad / s, pallet frame action instruction includes lifting height H pallet ∈ [0.5, 2.0] m and rotation angle θ pallet ∈ [0°, 360°].

[0022] The application also provides a box emulsion explosive unloading, stacking and carrying system, which uses the method described above and comprises a carrying and stacking robot and a receiving transport vehicle. The carrying and stacking robot comprises a first mobile base and a mechanical arm, the first mobile base being provided with a first control unit and a first image acquisition unit; the mechanical arm comprises a rotating base, a large arm, a small arm and a grabbing claw, the rotating base being fixed on the first mobile base, and the grabbing claw being provided with a second image acquisition unit; the receiving transport vehicle comprises a second mobile base and a pallet frame, the second mobile base being provided with a second control unit and a third image acquisition unit, and the pallet frame being used for placing a pallet.

[0023] The receiving transport vehicle further comprises a rotating mechanism arranged on the mobile base, the pallet frame being provided with two groups of symmetrically arranged rotating mechanisms, and further comprising a pallet frame lifting mechanism, one end of the pallet frame lifting mechanism being connected to the pallet frame and the other end being connected to the rotating mechanism, and the pallet frame lifting mechanism being used for lifting the pallet frame.

[0024] The application realizes automatic operation of the whole process from unloading to stacking and carrying of the box emulsion explosive by means of machine vision technology and an automatic control system, greatly reduces manual intervention and effectively improves work efficiency. With the aid of precise visual positioning components and precise action control of the mechanical arm, the position and angle of the box emulsion explosive in the stacking process are ensured to be accurate and correct, and the stacks are neat and uniform, which is conducive to improving the utilization rate of storage space and subsequent management convenience.

[0025] The application reduces the link of manual direct contact with the explosive and reduces the risk of safety accidents caused by human negligence or improper operation, thereby providing more reliable safety protection for the explosive carrying operation. The multi-directional movement capability of the carrying and stacking robot and the synergistic effect of various functional mechanisms of the receiving transport vehicle enable the system to flexibly adapt to different work scenes and diversified actual needs. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and other drawings can also be obtained by those skilled in the art without any creative effort.

[0027] Figure 1 is a schematic diagram of the box palletizing robot in the present application;

[0028] Figure 2 is a schematic diagram of the box palletizing robot in the present application;

[0029] In the figure: 1, box palletizing robot, 11, first moving base, 12, mechanical arm, 101, grabbing claw, 102, grabbing claw clamping motor, 103, grabbing claw rotating motor, 104, grabbing claw pitch motor, 105, small arm, 106, small arm pitch motor, 107, large arm, 108, large arm pitch motor, 109, rotating base, 110, connecting device, 111, first image acquisition unit, 112, first control unit, 114, McHale steering wheel, 2, box palletizing robot, 201, box emulsion explosive pile straightening mechanism, 203, third image acquisition unit, 204, tire, 205, second control unit, 206, rotating mechanism, 207, tray, 208, tray rack lifting mechanism, 209, middle rigid support frame, 210, tray rack. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0031] The box emulsion explosive unloading and stacking handling system of the embodiment comprises a handling and stacking robot 1 and a receiving transport vehicle 2. The handling and stacking robot 1 comprises a mechanical arm 12 and a first mobile base 11 for movement, and the bottom of the first mobile base 11 is equipped with four Mecanum steering wheels 114. The ability of flexible movement in multiple directions in a complex site environment enables it to adapt to various unloading and stacking operation scenarios and realize accurate positioning and movement in a plane. The first control unit 112 of the handling and stacking robot 1 can receive signals from various sensors and the first and second image acquisition units, and accurately control the steering angle, rotational speed and other key parameters of the Mecanum steering wheels 114 according to preset algorithms and programs. The first image acquisition unit 111 has high-precision image acquisition and processing functions, the lens thereof can comprehensively cover the working area, and can quickly and accurately identify and obtain key information such as the position, posture and quantity of the emulsion explosive boxes loaded in the vehicle compartment of the factory transport vehicle. Moreover, the first image acquisition unit 111 is connected to the first control unit 112 of the first mobile base 11 through a high-speed data transmission line, so as to ensure that the collected information can be transmitted to the first control unit 112 in real time and accurately, and provide indispensable data support for subsequent unloading and stacking operations.

[0032] The mechanical arm 12 for grabbing the pallet on the first mobile base 11 is installed on the upper part of the first mobile base 11 through the connecting device 110. The connecting device 110 not only effectively guarantees the stability of the mechanical arm 12 during operation, but also has the ability to withstand various forces generated by the mechanical arm 12 during grabbing and transporting the box emulsion explosive. The rotary base 109 is installed on the connecting device 110. This mechanism uses high-precision rotary support and drive motor to ensure that the mechanical arm 12 can realize continuous and stable 360° rotation in the horizontal plane, so as to realize flexible grabbing and placing of the box emulsion explosive in a larger range. The large arm 107 is connected to the rotary base 109 at one end and connected to the small arm 105 at the other end. The large arm pitch motor 108 can convert the rotary motion of the motor into the pitch motion of the large arm 107 in the vertical plane, thereby adjusting the angle of the large arm 107 to meet the grabbing requirements of explosives boxes at different heights. The same connection and transmission mode is adopted between the small arm 105 and the large arm 107. The small arm pitch motor 106 drives the small arm 105 to pitch relative to the large arm 107, further accurately adjusting the grabbing position. The grabbing claw 101 as a component directly contacting the box emulsion explosive, the grabbing claw rotating motor 103 can make the grabbing claw 101 realize 360° rotation in the horizontal direction to adjust the grabbing direction; the grabbing claw pitch motor 104 controls the grabbing claw 101 to pitch in the vertical direction; the grabbing claw clamping motor 102 can provide sufficient clamping force for the grabbing claw 101 to ensure that the explosive box will not slip during transportation, and the clamping force can be accurately adjusted according to the weight, material and other factors of the explosive box. The second image acquisition unit installed at the grabbing claw 101 can more accurately obtain the position information of the explosive box during grabbing operation, and closely cooperate with the first control unit 112 to realize efficient and accurate unloading and stacking of the box emulsion explosive.

[0033] The tires 204 of the box emulsion explosive receiving and transporting vehicle 2 are installed below the second mobile base to provide support and movement ability for the receiving and transporting vehicle 2. The tires 204 have sufficient carrying capacity, wear resistance and grip, and can adapt to different road conditions and transportation environments. The second mobile base serves as the basic frame of the receiving and transporting vehicle 2 and has sufficient strength and rigidity to support the components above, such as the tray rack 210, the tray rack lifting mechanism 208, the rotating mechanism 206, etc. The tray rack 210 is used to place the tray 207, and the tray 207 is used to place the box emulsion explosive.

[0034] Further, the tray rack lifting mechanism 208 is installed on the rotating mechanism 206 and driven by electricity, which can realize the precise lifting movement of the tray rack 210 in the vertical direction to adapt to different shelf height operation scenarios and ensure the height adaptability when cooperating with the unloading forklift or mechanical arm 12. The rotating mechanism 206 is located on the second mobile base and is supported and driven by high-strength rotary support and driving device, so that the tray rack 210 can rotate 360° on the horizontal plane, which greatly facilitates the stacking operation in different directions and effectively improves the operation efficiency and flexibility. When the stacking operation in the tray 207 above one side of the tray rack 210 is completed, the rotating mechanism 206 can rotate it to the other side, and the other side can continue the stacking operation, without the need for the receiving and transporting vehicle 2 to turn around or reposition, which fully utilizes the space on both sides of the vehicle and increases the single transportation loading capacity. The third image acquisition unit 203 is installed on both sides of the second mobile base and is used to acquire the surrounding environment information of the vehicle, including the terrain, obstacles, positions of other equipment, etc., to provide environmental perception data for the movement and operation of the vehicle. The second control unit 205 is installed on the lower end shelf of the second mobile base and is responsible for receiving the information of the third image acquisition unit 203 and deeply analyzing and processing according to the preset algorithm and rules, and then accurately controlling the movement of the vehicle, the lifting and rotation of the tray rack 210, etc. Further, the box emulsion explosive stacking and aligning mechanism 201 can be installed on both sides of the tray rack 210, which can quickly start and perform clamping action after the mechanical arm 12 completes the stacking operation. The clamping action pushes the clamping arm to move to both sides of the stack through the high-precision linear driving device. The contact part of the mechanism with the box emulsion explosive adopts soft material with certain friction, which can not only ensure that enough clamping force is applied to the stack to tightly arrange the explosive boxes in each layer and control the neatness of the stack within the specified error range, but also avoid scratching or damaging the surface of the explosive box. The middle rigid support frame 209 is located above the rotating mechanism 206 and is closely connected with the tray rack 210, which provides additional support for the tray rack 210 and enhances the stability of the tray rack 210 when carrying explosive boxes, preventing deformation or shaking of the tray rack 210 during rotation, lifting or transportation.

[0035] The box emulsion explosive unloading, stacking and transporting method of the present embodiment includes the following steps:

[0036] S1: The transporting and stacking robot 1 is started, the four Mecanum steering wheels 114 at the bottom of the first mobile base 11 are in the initial state, and the first control unit 112 starts to receive signals from various sensors and the first image acquisition unit 111. The first image acquisition unit 111 scans the box emulsion explosive in the vehicle compartment of the factory transport vehicle at high resolution and high frame rate, obtains the two-dimensional plane coordinates, depth information, attitude angle and other placement position information of the explosive box, and transmits them to the first control unit 112 in real time through wireless communication.

[0037] S2: The first control unit 112 accurately calculates the steering angle, rotation speed and other parameters of the Macpherson steering wheel 114 according to a preset algorithm and program in combination with the received position information, controls the first mobile base 11 to move to the unloading position, and adjusts the speed and direction in real time according to the updated information of the first image acquisition unit 111 during the movement process, so as to ensure accurate parking at the optimal unloading position.

[0038] Specifically, the automatic control system presets an algorithm for dynamic path planning and posture optimization (DPPOA) to calculate a path, wherein the input parameters of the dynamic path planning and posture optimization (DPPOA) include data collected by the first image acquisition unit 111, environmental parameters collected by various sensors and input in advance, and movement constraint conditions of the mechanical arm 12 of the carrying and stacking robot 1. The data collected by the first image acquisition unit 111 include two-dimensional plane coordinates x, y, height information z, and attitude angle θ of the emulsion explosive box, and transport vehicle compartment boundary coordinates and obstacle positions such as unloaded areas. The environmental parameters include ground friction coefficient μ, site slope α, and dynamic information of on-site obstacles such as personnel or other equipment collected by the first image acquisition unit 111. The movement constraint conditions of the mechanical arm 12 include lengths L1 and L2 of the large arm 107 and the small arm 105, maximum rotation speed ω of the joint motor, and maximum clamping force F of the grabbing claw 101. max max .

[0039] Specific operation model is as follows: the path planning module adopts an improved A* algorithm, and a cost function of the A* algorithm is f1(n)=g1(n)+h1(n)+λ·SafetyCost(n), wherein g1(n) represents actual movement cost from a starting point to a node n (considering steering energy consumption of the Macpherson wheel), h1(n) is a heuristic function (Euclidean distance to a target position), and SafetyCost(n) is a safety coefficient which is dynamically adjusted according to the minimum distance between the explosive box and the obstacle (the closer the distance, the higher the cost). The path planning is dynamically adjusted, and the first control unit 112 receives new data of the first image acquisition unit 111 every 200 ms, and recalculates the path according to the cost function.

[0040] The posture optimization module of the mechanical arm 12 is based on inverse kinematics and energy minimization, the inverse kinematics solves to calculate the pitch angles (φ1, φ2) of the large arm 107 and the small arm 105 according to the target position (x, y, z) and the attitude angle θ, and the calculation method of the pitch angles of the large arm 107 and the small arm 105 is as follows:

[0041]

[0042] and adopts a solution that minimizes the total energy consumption of the joint motor, that is: wherein k​i Efficiency coefficient of the motor i.

[0043] The mechanical arm 12 can realize self-adaptation of clamping force. The function is according to the weight m and material (friction coefficient μ box The dynamic adjustment of clamping force, and the specific operation process is: F grip = min (1.5·m·g·μ box , F max ).

[0044] The output parameters after the above model algorithm are the control instructions of the first mobile chassis and the action instructions of the mechanical arm 12, and the safety warning signal. The control instructions of the first mobile chassis include the steering angles (β1, β2, β3, β4) and the rotating speeds (v1, v2, v3, v4) of the Mecollum wheels. The control instructions of the first mobile chassis function to ensure the vehicle to move smoothly along the optimal path and avoid obstacles. The action instructions of the mechanical arm 12 are the pitch angles (φ1, φ2) of the large arm 107 and the small arm 105 and the size of the clamping force. The output parameters function to accurately grasp the explosive boxes and stack them to the designated position, and avoid sliding or damage. The safety warning signal triggers emergency stop or adjusts the path when detecting that the static electricity accumulation exceeds the threshold (Q max ) or the distance of the obstacle is less than the safety distance, to ensure safety.

[0045] The innovation of the algorithm lies in introducing the real-time updated safety cost function in the path planning, preferentially selecting the path away from personnel and obstacles; the mechanical arm 12 movement not only considers the position accuracy, but also reduces the motor loss through energy minimization; and the clamping force can be dynamically adjusted according to the characteristics of the explosive box, taking into account safety and stability.

[0046] S3: After the first mobile base 11 reaches the designated unloading position, the mechanical arm 12 starts work; the second image acquisition unit at the grabbing claw 101 accurately positions the explosive box again, and transmits the position information to the first control unit 112.

[0047] S4: The first control unit 112 generates the action instructions of the mechanical arm 12 according to the position and posture of the explosive box, the preset stacking rules and sequence. The large arm pitch motor 108 is started to adjust the angle of the large arm 107 to make the grabbing claw 101 reach the height position of the explosive box. The small arm pitch motor 106 drives the small arm 105 to pitch to further accurately adjust the grabbing position. The grabbing claw rotating motor 103 adjusts the grabbing direction, and the grabbing claw clamping motor 102 provides the clamping force to grab the explosive box.

[0048] S5: After the completion of the grab, the base 109 drives the mechanical arm 12 to rotate in the horizontal plane, moves the explosive box to the designated stacking position above the tray 207 of the receiving transport vehicle 2, and adjusts the posture of the large arm 107 and the small arm 105 again. The grabber pitch motor 104 controls the vertical pitch of the grabber 101 to accurately place the explosive box on the tray 207. Repeat the grabbing and stacking action to complete a tray 207 stacking operation.

[0049] S6: The third image acquisition unit 203 of the receiving transport vehicle 2 is installed on both sides of the second mobile base, continuously acquiring surrounding environmental parameters, including terrain, obstacles, warehouse entrance position and other equipment position information, and feeding back to the second control unit 205 in real time.

[0050] S7: The second control unit 205 has an algorithm and logic judgment module built-in, which analyzes and processes environmental information, combines preset maps and task requirements, plans the optimal transportation path from the current position to the warehouse, controls the rotation direction and speed of the tire 204, and makes the receiving transport vehicle 2 drive along the planned path to the warehouse. Adjust the path in time according to the monitoring information of the third image acquisition unit 203 during transportation.

[0051] Specifically, the second control unit 205 has a multi-objective dynamic path planning and cooperative control algorithm (MD-PCCA) built-in, and the input parameters of the multi-objective dynamic path planning and cooperative control algorithm (MD-PCCA) are environmental perception data, vehicle state parameters and task constraints. The environmental perception data is the real-time environmental information collected by the visual positioning component, that is, the terrain elevation h, the obstacle coordinates (O x ,O y ), the warehouse entrance position information (W x ,W y ), and the speed vector v x ,v y of dynamic obstacles such as personnel or other mobile equipment. The vehicle state parameters are the current position (X current ,Y current ) of the receiving transport vehicle 2, the tire 204 rotation speed (ω tire ), and the tray rack 210 height (H pallet ). The task constraints are the topological structure of the preset map (such as path nodes N i , safety distance threshold d safe ≥1.5m).

[0052] The specific operation model is as follows: the dynamic path planning module (based on the improved D*Lite algorithm), and its adaptive cost function is: f2(n) = g2(n) + ε·h2(n) + γ·DynamicRisk(n), wherein g2(n) represents the actual path length (considering the tire 204 wear coefficient μtire ), h2(n) represents a heuristic function (Manhattan distance modified by terrain slope), DynamicRisk(n) represents dynamic risk assessment (collision probability prediction according to obstacle speed). And the model can realize real-time replanning, updating the path every 100ms, responding to sudden obstacles.

[0053] A multi-objective optimization module based on the NSGA-II framework, the optimization objectives are minimum transportation time, minimum energy consumption, and maximum safety factor. The minimum transportation time calculation method is wherein, L i is the length of the segmented path; the minimum energy consumption calculation method is The maximum safety factor calculation method is The constraint condition of the above objective function is: to prevent tipping, the rotation angle of the tray rack 210 is limited to θ pallet ≤45° / s; the maximum rotation speed of the tire 204 is ω tire ≤2 rad / s.

[0054] The state code of the synchronous communication protocol is: the handling robot gives the receiving transport vehicle 2: STATUS_CODE={READY, MOVING, EMERGENCY_STOP}; the receiving transport vehicle 2 gives the handling robot: PATH_UPDAT={NEW_OBSTACLE, REROUTE_SUGGESTION}.

[0055] Through the algorithm, vehicle control instructions, tray rack 210 action instructions, and safety warning signal output parameters can be obtained. The vehicle control instructions ensure that the transport vehicle moves smoothly along the optimal path and avoids dynamic obstacles. The specific output parameters are the tire 204 steering angle θ steer ∈[-30°, 30°] and the rotation speed ω tire ∈[0.5, 2] rad / s. The tray rack 210 action instructions ensure that it adapts to different working scenarios during work, specifically including the lifting height H pallet ∈[0.5, 2.0] m and the rotation angle θ pallet ∈[0°, 360°]. The safety warning signal can ensure that the path is re-planned or the operation is stopped when static electricity and other signals are detected.

[0056] The algorithm introduces a collision probability prediction based on a velocity vector, which is superior to traditional static obstacle avoidance algorithms, and for the first time optimizes time, energy consumption, and safety in explosive transport.

[0057] S8: After the receiving and transporting vehicle 2 reaches the warehouse or designated stacking area, the tray frame lifting mechanism 208 is operated according to the actual operation requirements. If it is cooperated with the unloading forklift, the height of the tray frame 210 is adjusted according to the height of the forklift tines; if it is cooperated with the carrying and stacking robot 1, the height is adjusted in real time according to the operation height of the mechanical arm 12.

[0058] S9: In the stacking operation, when one side of the tray frame 210 completes the stacking operation, the rotating mechanism 206 rotates the tray frame 210 to the other side through the rotating support and driving device, and the other side continues the stacking operation, without the receiving and transporting vehicle 2 turning around or repositioning.

[0059] S10: After the mechanical arm 12 completes the stacking operation of one tray frame 210, the box-packed emulsion explosive stack alignment mechanism 201 is quickly started. The clamping arm is pushed to move to both sides of the stack by the high-precision linear driving device, and the clamping force is applied to the stack by using the soft and frictional material at the contact position, so that the explosive boxes are tightly arranged, the alignment degree is controlled within the specified error range, and the surface of the explosive box is prevented from being scratched. The middle rigid support frame 209 provides additional support for the tray frame 210, enhances its stability, and prevents deformation or shaking.

[0060] S11: The carrying and stacking robot 1 and the receiving and transporting vehicle 2 work cooperatively through the communication of the first control unit 112 and the second control unit 205. After the carrying and stacking robot 1 completes the stacking operation of one tray frame 210, it informs the receiving and transporting vehicle 2 to operate. When the receiving and transporting vehicle 2 is transporting or operating, it feeds back the state information to the carrying and stacking robot 1. The operator can also remotely monitor and intervene to ensure the safe and efficient operation of the system, and realize the automation of the whole process of unloading, stacking and carrying of the box-packed emulsion explosive.

[0061] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A method of unloading, stacking and handling of box emulsion explosives, characterized in that, The method comprises the following steps: S1, the carrying and stacking robot scans the box emulsion explosive in the vehicle compartment of the transport vehicle, and obtains the placement position information of the box emulsion explosive; S2, the carrying and stacking robot adjusts the speed and direction in real time according to the placement position information of the box emulsion explosive, and moves to the optimal unloading position; S3, the carrying and stacking robot obtains the placement position information of the box emulsion explosive again by using the second image acquisition unit on the mechanical arm, including the two-dimensional plane coordinates, depth information and attitude angle information of the box emulsion explosive; S4, according to the placement position information of the box emulsion explosive obtained in S3 and the preset stacking rules and sequence, the mechanical arm action instruction is generated, and the box emulsion explosive is grabbed by using the mechanical arm; S5, the mechanical arm transfers the box emulsion explosive to the receiving transport vehicle, and keeps the box emulsion explosive in a horizontal state, and repeats S3-S5 until the transfer of the box emulsion explosive is completed; S6, the receiving transport vehicle collects environmental parameters, including terrain, obstacles and warehouse entrance position information; S7, the environmental parameters are analyzed and processed in real time, the optimal transport path from the current position to the specified position of the warehouse is planned combined with the map and the task requirements; S8, the receiving transport vehicle moves to the specified position of the warehouse and performs unloading operation.

2. The box emulsion unloading and stacking method according to claim 1, wherein In S8, the tray rack lifting mechanism on the receiving transport vehicle performs lifting operation according to the operation demand, and if it cooperates with the unloading forklift, the height of the tray rack is adjusted according to the height of the forklift tines; if it cooperates with the carrying and stacking robot, the height of the tray rack is adjusted in real time according to the operation height of the mechanical arm.

3. The box emulsion unloading and stacking method according to claim 1, wherein In S2, speed and direction are adjusted in real time through dynamic path planning and attitude optimization algorithms. The input parameters of the dynamic path planning and attitude optimization algorithms include the placement information data of the boxed emulsion explosives, input environmental parameters, and robotic arm motion constraints. The placement information data of the boxed emulsion explosives includes two-dimensional plane coordinates x and y, height information z, attitude angle θ, boundary coordinate information of the transport vehicle, and obstacle position information. Environmental parameters include the ground friction coefficient μ, site slope α, and obstacle dynamic information. The robotic arm motion constraints include the length of the upper arm L1, the length of the lower arm L2, and the maximum speed ω of the joint motor. max and the maximum clamping force F of the robotic arm max The improved A* algorithm is adopted, and the cost function of the A* algorithm is: f1(n)=g1(n)+h1(n)+λ·SafetyCost(n). In the cost function, g1(n) represents the actual movement cost from the starting point to node n, h1(n) is a heuristic function, SafetyCost(n) is the safety factor, which is dynamically adjusted according to the minimum distance between the boxed emulsion explosive and the obstacle, and λ is a dynamic weight coefficient. The path planning is dynamically adjusted, and the path is recalculated according to the cost function at preset intervals.

4. The box emulsion unloading and stacking method according to claim 3, wherein The method also includes mechanical arm posture optimization based on inverse kinematics and energy minimization. The inverse kinematics solves the pitch angle φ1 of the large arm and the pitch angle φ2 of the small arm according to the two-dimensional plane coordinates x and y, the height information z and the attitude angle θ. The calculation method of the pitch angle of the large arm and the small arm is as follows: φ2=θ-φ1 The solution that minimizes the total energy consumption of the joint motors is adopted, i.e. where k i is the efficiency coefficient of motor i.

5. The box emulsion unloading and stacking method according to claim 4, wherein Clamping force F of the mechanical arm grip Adaptive, according to the weight m of the boxed emulsion explosive and the friction coefficient μ box Dynamic adjustment of the clamping force, the specific operation process is: grip = min (1.5·m·g·μ box , F max ).

6. The box emulsion unloading and stacking method according to claim 5, wherein When detecting that the static electricity accumulation exceeds a threshold Q max or the obstacle distance is less than a safe distance, triggering an emergency stop or adjusting the path.

7. The box emulsion unloading and stacking method according to claim 1, wherein The multi-target dynamic path planning and cooperative control algorithm is adopted in S7 to plan a path, input parameters of the multi-target dynamic path planning and cooperative control algorithm are environment parameters, state parameters of the receiving and transporting vehicle and task constraints; the environment parameters include terrain elevation h, obstacle coordinates O x and O y , warehouse entrance coordinates W x and W y , and dynamic obstacle velocity vector v x ,v y ; the state parameters of the receiving and transporting vehicle include current position X current ,Y current of the receiving and transporting vehicle, tire rotating speed ω tire , and pallet rack height H pallet ; the task constraints are topological structures of a preset map, including path nodes N i and safety distance threshold d safe ; the dynamic path planning module is based on an improved D*Lite algorithm, an adaptive cost function thereof is f2(n)=g2(n)+ε·h2(n)+γ·DynamicRisk(n), wherein g2(n) is actual path length considering tire wear coefficient μ tire , h2(n) is a heuristic function, DynamicRisk(n) is dynamic risk assessment, ε is a weight coefficient of the heuristic function h(n), and γ is a weight coefficient of the dynamic risk cost DynamicRisk(n); the path is updated at intervals of a preset time.

8. The box emulsion unloading and stacking method according to claim 7, wherein Also included is multi-objective optimization based on the NSGA-II framework, with optimization objectives being minimum transportation time, minimum energy consumption, and maximum safety factor; the minimum transportation time is calculated in the manner of wherein L i is the length of the segmented path, v i is the driving speed of the segmented path; the minimum energy consumption is calculated in the manner of ω i is the energy consumption weight coefficient of the segmented path; the maximum safety factor is calculated in the manner of d obstacle is the minimum distance between the boxed emulsion explosive and the obstacle; the constraint condition of the objective function is that the rotation angle θ pallet of the tray frame is ≤45° / s, the maximum rotation speed ω tire of the tire is ≤2 rad / s; the output parameters are the tire rotation angle θ steer ∈[-30°, 30°] and the rotation speed ω tire ∈[0.5, 2] rad / s, the tray frame action instruction includes the lifting height H pallet ∈[0.5, 2.0] m and the rotation angle θ pallet ∈[0°, 360°].

9. A box emulsion unloading and stacking handling system characterized by, The method comprises the following steps:

10. The box emulsion unloading and stacking handling system of claim 9, wherein, S1, the carrying and stacking robot scans the box emulsion explosive in the vehicle compartment of the transport vehicle, and obtains the placement position information of the box emulsion explosive; S2, the carrying and stacking robot adjusts the speed and direction in real time according to the placement position information of the box emulsion explosive, and moves to the optimal unloading position; S3, the carrying and stacking robot obtains the placement position information of the box emulsion explosive again by using the second image acquisition unit on the mechanical arm, including the two-dimensional plane coordinates, depth information and attitude angle information of the box emulsion explosive; S4, according to the placement position information of the box emulsion explosive obtained in S3 and the preset stacking rules and sequence, the mechanical arm action instruction is generated, and the box emulsion explosive is grabbed by using the mechanical arm; S5, the mechanical arm transfers the box emulsion explosive to the receiving transport vehicle, and keeps the box emulsion explosive in a horizontal state, and repeats S3-S5 until the transfer of the box emulsion explosive is completed; S6, the receiving transport vehicle collects environmental parameters, including terrain, obstacles and warehouse entrance position information; S7, the environmental parameters are analyzed and processed in real time, the optimal transport path from the current position to the specified position of the warehouse is planned combined with the map and the task requirements; S8, the receiving transport vehicle moves to the specified position of the warehouse and performs unloading operation. In S8, the tray rack lifting mechanism on the receiving transport vehicle performs lifting operation according to the operation demand, and if it cooperates with the unloading forklift, the height of the tray rack is adjusted according to the height of the forklift tines; if it cooperates with the carrying and stacking robot, the height of the tray rack is adjusted in real time according to the operation height of the mechanical arm. The method also includes mechanical arm posture optimization based on inverse kinematics and energy minimization. The inverse kinematics solves the pitch angle φ1 of the large arm and the pitch angle φ2 of the small arm according to the two-dimensional plane coordinates x and y, the height information z and the attitude angle θ. The calculation method of the pitch angle of the large arm and the small arm is as follows: φ2=θ-φ1 The method comprises the following steps: S1, the carrying and stacking robot scans the box emulsion explosive in the vehicle compartment of the transport vehicle, and obtains the placement position information of the box emulsion explosive; S2, the carrying and stacking robot adjusts the speed and direction in real time according to the placement position information of the box emulsion explosive, and moves to the optimal unloading position; S3, the carrying and stacking robot obtains the placement position information of the box emulsion explosive again by using the second image acquisition unit on the mechanical arm, including the two-dimensional plane coordinates, depth information and attitude angle information of the box emulsion explosive; S4, according to the placement position information of the box emulsion explosive obtained in S3 and the preset stacking rules and sequence, the mechanical arm action instruction is generated, and the box emulsion explosive is grabbed by using the mechanical arm; S5, the mechanical arm transfers the box emulsion explosive to the receiving transport vehicle, and keeps the box emulsion explosive in a horizontal state, and repeats S3-S5 until the transfer of the box emulsion explosive is completed; S6, the receiving transport vehicle collects environmental parameters, including terrain, obstacles and warehouse entrance position information; S7, the environmental parameters are analyzed and processed in real time, the optimal transport path from the current position to the specified position of the warehouse is planned combined with the map and the task requirements; S8, the receiving transport vehicle moves to the specified position of the warehouse and performs unloading operation. In S8, the tray rack lifting mechanism on the receiving transport vehicle performs lifting operation according to the operation demand, and if it cooperates with the unloading forklift, the height of the tray rack is adjusted according to the height of the forklift tines; if it cooperates with the carrying and stacking robot, the height of the tray rack is adjusted in real time according to the operation height of the mechanical arm. The method also includes mechanical arm posture optimization based on inverse kinematics and energy minimization. The inverse kinematics solves the pitch angle φ1 of the large arm and the pitch angle φ2 of the small arm according to the two-dimensional plane coordinates x and y, the height information z and the attitude angle θ. The calculation method of the pitch angle of the large arm and the small arm is as follows: φ2=θ-φ1

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