Boxed emulsion explosive unloading, stacking and carrying method and system

Abstract

The invention relates to a box-packed emulsion explosive unloading, stacking and carrying method and system. The carrying method comprises the steps that a carrying and stacking robot scans box-packed emulsion explosives in a carriage of a transport vehicle, and the placing position information of the box-packed emulsion explosives is obtained; the carrying and stacking robot moves to the optimal unloading position according to the placement position information of the boxed emulsion explosives; the carrying stacking robot obtains the placing position information of the box-packed emulsion explosive again; according to the placement position information of the box-packed emulsion explosives, the box-packed emulsion explosives are grabbed through a mechanical arm; the mechanical arm is used for transferring the boxed emulsion explosive to the material receiving transport vehicle; the material receiving transport vehicle collects environmental parameters; environment parameters are analyzed and processed in real time, and an optimal transportation path from the current position to the designated position of the warehouse is planned; and the material receiving transport vehicle is moved to a warehouse for unloading operation. By means of the machine vision technology and the automatic control system, automatic operation of the whole process from unloading to stacking and carrying of the boxed emulsion explosives is achieved, manual intervention is reduced, and operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unloading, palletizing and handling of boxed emulsion explosives in a civil explosive storage depot, and specifically relates to a method and system for unloading, palletizing and handling boxed emulsion explosives. Background Art

[0002] In the fields of explosive production and logistics transportation, the unloading, palletizing and handling of boxed emulsion explosives are of crucial importance. The traditional operation methods mainly rely on manual operations and have many problems. When manually unloading, workers need to manually carry down the boxed explosives from the transport vehicle one by one, which is labor-intensive and inefficient. During the palletizing process, stacking depends on manual experience, and it is not easy to ensure the neatness and accuracy of the stacking. It may also cause the explosive boxes to be unstable during storage, posing potential safety hazards. In addition, during the process of manually handling the explosive boxes, due to the special nature of explosives, even a slight carelessness may trigger serious safety accidents, posing a huge threat to the lives of personnel and the property of enterprises. Summary of the Invention

[0003] In order to solve the deficiencies existing in the above-mentioned prior art, the present invention provides a method for unloading, palletizing and handling boxed emulsion explosives, including:

[0004] S1. The handling and palletizing robot scans the boxed emulsion explosives in the carriage of the transport vehicle to obtain the position information of the boxed emulsion explosives.

[0005] S2. The handling and palletizing robot adjusts its speed and direction in real time according to the position information of the boxed emulsion explosives and moves to the optimal unloading position.

[0006] S3. The handling and palletizing robot uses the second image acquisition unit on the robotic arm to obtain the position information of the boxed emulsion explosives again, including the two-dimensional plane coordinates, depth information and attitude angle information of the boxed emulsion explosives.

[0007] S4. According to the position information of the boxed emulsion explosives obtained in S3 and the preset palletizing rules and order, generate robotic arm action instructions and use the robotic arm to grab the boxed emulsion explosives.

[0008] S5. The robotic arm transfers the boxed emulsion explosives to the receiving transport vehicle and keeps the boxed emulsion explosives in a horizontal state. Repeat S3 - S5 until the transfer of the boxed emulsion explosives is completed.

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

[0010] S7. Analyze and process the environmental parameters in real time, and combine with the map and the requirements of the operation task to plan the optimal transportation path from the current position to the designated position in the warehouse.

[0011] S8. The receiving transport vehicle moves to the designated position in the warehouse for unloading operations.

[0012] Furthermore, S8 also includes that the pallet rack lifting mechanism on the receiving transport vehicle performs lifting operations according to the operation requirements. If it cooperates with the unloading forklift, the height of the pallet rack is adjusted according to the height of the forklift's forks; if it cooperates with the handling and palletizing robot, the height of the pallet rack is adjusted in real time according to the working height of the robotic arm.

[0013] Furthermore, in S2, the speed and direction are adjusted in real time through the dynamic path planning and attitude optimization algorithm. The input parameters of the dynamic path planning and attitude optimization algorithm include the position information data of the boxed emulsion explosive, the input environmental parameters, and the motion constraints of the robotic arm; the position information data of the boxed emulsion explosive includes the two-dimensional plane coordinates x and y, the height information z, the attitude angle θ, the coordinates of the transport vehicle's carriage boundary, and the position information of the obstacles; the environmental parameters include the ground friction coefficient μ, the site slope α, and the dynamic information of the obstacles; the motion constraints of the robotic arm include the length L1 of the large arm, the length L2 of the small arm, the maximum rotational speed ωmax of the joint motor, and the maximum clamping force Fmax of the robotic arm; 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 the heuristic function, SafetyCost(n) is the safety factor, which is dynamically adjusted according to the minimum distance between the boxed emulsion explosive and the obstacles, and λ is the 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 planning is dynamically adjusted, and the path is recalculated according to the cost function at preset time intervals.

[0014] Furthermore, it also includes the robotic arm attitude optimization. Based on inverse kinematics and energy minimization, the inverse kinematics solution calculates 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 methods of the pitch angles of the large arm and the small arm are as follows:

[0015]

[0016] φ2 = θ - φ1

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

[0018] Furthermore, the clamping force Fgrip of the robotic arm is adaptive and is dynamically adjusted according to the weight m of the boxed emulsion explosive and the friction coefficient μbox. The specific calculation process is: F grip = min(1.5·m·g·μbox , F max )。

[0019] Furthermore, when it is detected that the electrostatic accumulation exceeds the threshold Q max or the distance to the obstacle is less than the safe distance, an emergency stop or path adjustment is triggered.

[0020] Furthermore, in S7, a multi-objective dynamic path planning and cooperative control algorithm is used to plan the path. The input parameters of the multi-objective dynamic path planning and cooperative control algorithm are environmental parameters, the state parameters of the receiving transport vehicle, and task constraints; the environmental parameters include the terrain elevation h, the obstacle coordinates O x and O y , the warehouse entrance coordinates W x and W y as well as the dynamic obstacle velocity vector v x , v y ; the state parameters of the receiving transport vehicle include the current position X current , Y current of the receiving transport vehicle, the tire rotation speed ω tire , the height H pallet of the pallet rack; the task constraint is the topological structure of the preset map, including the path node N i , the safe distance threshold d safe ; the dynamic path planning module is based on the improved D*Lite algorithm, and its adaptive cost function is: f2(n) = g2(n) + ε·h2(n) + γ·DynamicRisk(n), where g2(n) is the actual path length considering the tire wear coefficient μ tire , h2(n) is the heuristic function, DynamicRisk(n) is the dynamic risk assessment, ε is the weight coefficient of the heuristic function h(n) for balancing the efficiency and optimality of path search, and γ is the weight coefficient of the dynamic risk cost DynamicRisk(n) for quantifying the impact of environmental dynamic risks on path selection; the path is updated at preset time intervals.

[0021] Furthermore, it also includes multi-objective optimization based on the NSGA-II framework, and the optimization objectives are the minimum transportation time, the minimum energy consumption, and the maximum safety factor; the operation method for the minimum transportation time is where L i is the segmented path length, and vi is the driving speed of the segmented path; the operation method for the minimum energy consumption is ω i is the energy consumption weight coefficient of the segmented path; the operation method for the maximum safety factor is d obstacle is the minimum distance between the boxed emulsion explosive and the obstacle; the constraint condition of the objective function is: the rotation angle θ pallet≤45° / s, maximum tire rotation speed ω tire ≤2 rad / s; the output parameters are the tire steering angle θ steer ∈[-30°, 30°] and the rotation speed ω tire ∈[0.5, 2] rad / s, the pallet rack action instructions include the lifting height H pallet ∈[0.5, 2.0] m and the rotation angle θ pallet ∈[0°, 360°].

[0022] The present invention also provides a boxed emulsion explosive unloading, stacking and handling system, which uses the method described above and includes a handling and stacking robot and a receiving transport vehicle. The handling and stacking robot includes a first mobile base and a robotic arm. A first control unit and a first image acquisition unit are provided on the first mobile base; the robotic arm includes a rotating base, a large arm, a small arm and a grasping claw. The rotating base is fixed on the first mobile base, and a second image acquisition unit is provided on the grasping claw; the receiving transport vehicle includes a second mobile base and a pallet rack. A second control unit and a third image acquisition unit are provided on the second mobile base, and the pallet rack is used to place the pallet.

[0023] The receiving transport vehicle further includes a rotating mechanism provided on the mobile base. There are two groups of pallet racks symmetrically arranged on the rotating mechanism. It also includes a pallet rack lifting mechanism. One end of the pallet rack lifting mechanism is connected to the pallet rack, and the other end is connected to the rotating mechanism for lifting the pallet rack.

[0024] Through machine vision technology and an automatic control system, the present invention realizes the automated operation of the whole process from unloading to stacking and handling of boxed emulsion explosives, greatly reducing manual intervention and effectively improving the operation efficiency. With the help of precise vision positioning components and precise motion control of the robotic arm, it ensures the accurate position and angle of the boxed explosives during the stacking process, and the stack is neat and uniform, which is beneficial to improving the utilization rate of storage space and the convenience of subsequent management.

[0025] The present invention reduces the link of direct human contact with explosives, reduces the risk of safety accidents caused by human negligence or improper operation, and provides a more reliable safety guarantee for the explosive handling operation. The multi-directional movement ability of the handling and stacking robot and the coordinated action of various functional mechanisms of the receiving transport vehicle enable the system to flexibly adapt to different operation scenarios and diverse actual needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0027] Figure 1 It is a schematic diagram of the handling and palletizing robot in the present invention;

[0028] Figure 2 It is a schematic diagram of the receiving transport vehicle in the present invention;

[0029] In the figure: 1. Handling and palletizing robot, 11. First moving base, 12. Manipulator arm, 101. Gripping claw, 102. Gripping claw clamping motor, 103. Gripping claw rotating motor, 104. Gripping claw pitching motor, 105. Forearm, 106. Forearm pitching motor, 107. Upper arm, 108. Upper arm pitching motor, 109. Rotary base, 110. Connecting device, 111. First image acquisition unit, 112. First control unit, 114. McCallum steering wheel, 2. Receiving transport vehicle, 201. Boxed emulsion explosive stacking mechanism, 203. Third image acquisition unit, 204. Tire, 205. Second control unit, 206. Rotating mechanism, 207. Pallet, 208. Pallet rack lifting mechanism, 209. Middle rigid support frame, 210. Pallet rack. Detailed implementation manners

[0030] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with 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. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] The boxed emulsion explosive unloading, palletizing and handling system of this embodiment includes a handling and palletizing robot 1 and a receiving transport vehicle 2. The handling and palletizing robot 1 includes a robotic arm 12 and a first moving base 11 for movement. The bottom of the first moving base 11 is equipped with four McCallum steering wheels 114, which can move flexibly in multiple directions in a complex site environment, enabling it to adapt to various unloading and palletizing operation scenarios and achieve precise positioning and movement in a plane. The first control unit 112 of the handling and palletizing robot 1 can receive signals from various sensors, as well as the first image acquisition unit 111 and the second image acquisition unit, and accurately regulate key parameters such as the steering angle and rotation speed of the McCallum steering wheels 114 according to preset algorithms and programs. The first image acquisition unit 111 has a high-precision image acquisition and processing function, and its lens can fully cover the working area. For the boxed emulsion explosives loaded in the carriage of the factory transport vehicle, it can quickly and accurately identify and obtain key information such as the position, attitude, and quantity of the explosive boxes, and is connected to the first control unit 112 of the first moving base 11 through a high-speed data transmission line to ensure that the collected information can be transmitted to the first control unit 112 in real time and accurately, providing indispensable data support for subsequent unloading and palletizing operations.

[0032] The robotic arm 12 for grasping and palletizing 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 can not only effectively ensure the stability of the robotic arm 12 during operation, but also has the ability to withstand various forces generated by the robotic arm 12 when grasping and transporting boxed emulsion explosives. The rotating base 109 is installed on the connecting device 110. This mechanism uses high-precision slewing bearings and drive motors to ensure that the robotic arm 12 can achieve continuous and smooth 360° rotation on the horizontal plane, so as to realize flexible grasping and placing operations of boxed emulsion explosives within a large range. One end of the large arm 107 is connected to the rotating base 109, and the other end is connected to the small arm 105. The large arm pitching motor 108 can convert the rotational motion of the motor into the pitching motion of the large arm 107 in the vertical plane, so as to adjust the angle of the large arm 107 to meet the grasping requirements of explosive boxes at different height positions. The same connection and transmission method is adopted between the small arm 105 and the large arm 107. The small arm pitching motor 106 drives the small arm 105 to pitch relative to the large arm 107 to further precisely adjust the grasping position. The grasping claw 101, as the component directly contacting the boxed emulsion explosives, its grasping claw rotating motor 103 can make the grasping claw 101 rotate 360° in the horizontal direction to adjust the grasping direction; the grasping claw pitching motor 104 controls the pitching of the grasping claw 101 in the vertical direction; the grasping claw clamping motor 102 can provide sufficient clamping force for the grasping claw 101 to ensure that the explosive box will not slip during transportation, and the clamping force can be precisely adjusted according to factors such as the weight and material of the explosive box. The second image acquisition unit installed at the grasping claw 101 can more accurately obtain the position information of the explosive box during the grasping operation, and closely cooperate with the first control unit 112 to realize efficient and accurate unloading and palletizing operations of boxed emulsion explosives.

[0033] The tires 204 of the boxed emulsion explosive receiving transport vehicle 2 are installed under the second mobile base to provide support and mobility for the receiving transport vehicle 2. The tires 204 have sufficient load-bearing capacity, wear resistance and grip to adapt to different road conditions and transportation environments. The second mobile base, as the basic framework of the receiving transport vehicle 2, has sufficient strength and rigidity to support components such as the pallet rack 210, the pallet rack lifting mechanism 208, and the rotating mechanism 206 above. The pallet rack 210 is used to place the pallet 207, and the pallet 207 is used to place boxed emulsion explosives.

[0034] Furthermore, the pallet rack lifting mechanism 208 is installed on the rotating mechanism 206 and adopts an electric drive mode, which can achieve precise lifting movement of the pallet rack 210 in the vertical direction to adapt to different shelf height operation scenarios and ensure height adaptability when cooperating with the unloading forklift or the robotic arm 12. The rotating mechanism 206 is located on the second moving base. With the help of a high-strength slewing bearing and a driving device, the pallet rack 210 can rotate 360° on the horizontal plane. This design greatly facilitates palletizing operations in different directions and effectively improves operation efficiency and flexibility. After the palletizing operation is completed in the pallet 207 above one side of the pallet rack 210, the rotating mechanism 206 can rotate it to the other side, and the other side can continue the palletizing operation without the need for the receiving transport vehicle 2 to turn around or reposition, making full use of the space on both sides of the vehicle and increasing the single transport loading capacity. The third image acquisition unit 203 is installed on both sides of the second moving base and is used to collect information on the vehicle's surrounding environment, including terrain, obstacles, positions of other equipment, etc., providing environmental perception data for vehicle movement and operation. The second control unit 205 is installed on the lower rack of the second moving base, responsible for receiving the information from the third image acquisition unit 203, and deeply analyzing and processing it according to preset algorithms and rules, and then precisely controlling the movement of the vehicle, the lifting and rotation of the pallet rack 210, etc. It can further include a boxed emulsion explosive stacking alignment mechanism 201 installed on both sides of the pallet rack 210. After the robotic arm 12 completes the palletizing operation, this mechanism can quickly start and perform a clamping action. The clamping action is to push the clamping arms towards both sides of the stack by a high-precision linear drive device. The contact part of this mechanism with the boxed emulsion explosive uses a soft material with a certain friction force, which can not only ensure sufficient clamping force on the stack to make the explosive boxes in each layer of the stack closely arranged and control the stack alignment within the specified error range, but also avoid scratching or damaging the surface of the explosive boxes. The middle rigid support frame 209 is located above the rotating mechanism 206 and is tightly connected to the pallet rack 210, providing additional support for the pallet rack 210 and enhancing its stability when carrying explosive boxes, preventing the pallet rack 210 from deforming or shaking during rotation, lifting or transportation.

[0035] The method for unloading, palletizing and transporting boxed emulsion explosives in this embodiment includes the following steps:

[0036] S1: The handling and palletizing robot 1 is started. The four McCallum steering wheels 114 at the bottom of the first moving 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 boxed emulsion explosives in the carriage of the factory transport vehicle with high resolution and high frame rate, obtains the placement position information such as the two-dimensional plane coordinates, depth information, and attitude angles of the explosive boxes, and transmits it to the first control unit 112 in real time through wireless communication.

[0037] S2: The first control unit 112 accurately calculates parameters such as the steering angle and rotational speed of the McCollum steering wheel 114 based on a preset algorithm and program, in combination with the received position information, and controls the first mobile base 11 to move towards the unloading position. During the movement, the speed and direction are adjusted in real time according to the updated information of the first image acquisition unit 111 to ensure accurate docking at the optimal unloading position.

[0038] Specifically, the preset algorithm of the automatic control system is the dynamic path planning and attitude optimization algorithm (DPPOA) to calculate the path. The input parameters of the dynamic path planning and attitude optimization algorithm (DPPOA) include the data collected by the first image acquisition unit 111, the environmental parameters collected by each sensor and input in advance, and the motion constraint conditions of the robotic arm 12 of the handling and palletizing robot 1. The data collected by the first image acquisition unit 111 includes the two-dimensional plane coordinates x, y, height information z, and attitude angle θ of the emulsion explosive box, as well as the coordinates of the transport vehicle carriage boundary and the position of obstacles, such as the unloaded area. The environmental parameters include the ground friction coefficient μ, the site slope α, and the dynamic information of on-site obstacles collected by the first image acquisition unit 111, such as personnel or other equipment. The motion constraint conditions of the robotic arm 12 include the lengths L1, L2 of the boom 107 and the forearm 105, and the maximum rotational speed ω of the joint motor max , and the maximum clamping force F of the gripper 101 max .

[0039] The specific operation model is as follows. The path planning module uses an improved A* algorithm. 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 (considering the steering energy consumption of the McCollum wheel), h1(n) is the heuristic function (Euclidean distance to the target position), and SafetyCost(n) is the safety factor, 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. Every 200 ms, the first control unit 112 receives new data from the first image acquisition unit 111 and recalculates the path according to the cost function.

[0040] The attitude optimization module of the robotic arm 12 is based on inverse kinematics and energy minimization. The inverse kinematics solution calculates the pitching angles (φ1, φ2) of the boom 107 and the forearm 105 according to the target position (x, y, z) and the attitude angle θ. The calculation methods of the pitching angles of the boom 107 and the forearm 105 are as follows:

[0041]

[0042] And the solution that minimizes the total energy consumption of the joint motor is adopted, that is: where ki is the efficiency coefficient of motor i.

[0043] The robotic arm 12 can achieve adaptive clamping force. This function dynamically adjusts the clamping force according to the weight m and material (friction coefficient μ) of the explosive box. The specific calculation process is as follows: F box = min(1.5·m·g·μ grip , F box , F max ).

[0044] The output parameters after the above-mentioned model algorithm are the control instructions for the first mobile chassis, the action instructions for the robotic arm 12, and the safety warning signal. The control instructions for the first mobile chassis include the steering angles (β1, β2, β3, β4) and rotational speeds (v1, v2, v3, v4) of the McColum wheels. The function of the control instructions for the first mobile chassis is to ensure that the vehicle moves smoothly along the optimal path and avoids obstacles. The action instructions for the robotic arm 12 are the pitching angles (φ1, φ2) of the boom 107 and the forearm 105, and the magnitude of the clamping force. The function of the output parameters is to accurately grasp the explosive box and stack it at the specified position to avoid slipping or damage. The safety warning signal triggers an emergency stop or adjusts the path when it detects that the static electricity accumulation exceeds the threshold (Q max ) or the distance to the obstacle is less than the safe distance to ensure safety.

[0045] The innovation of the algorithm lies in introducing a safety cost function that is updated in real time in path planning, giving priority to choosing paths far from people and obstacles; the movement of the robotic arm 12 not only considers position accuracy but also reduces motor loss through energy minimization; it can dynamically adjust the clamping force according to the characteristics of the explosive box, taking into account both safety and stability.

[0046] S3: After the first mobile base 11 reaches the specified unloading position, the robotic arm 12 starts to operate; the second image acquisition unit at the grasping claw 101 accurately locates 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 for the robotic arm 12 according to the position and attitude of the explosive box, the preset stacking rules and sequence. The boom pitching motor 108 starts to adjust the angle of the boom 107 so that the grasping claw 101 reaches the height position of the explosive box. The forearm pitching motor 106 drives the pitching action of the forearm 105 to further accurately adjust the grasping position. The grasping claw rotation motor 103 adjusts the grasping direction, and the grasping claw clamping motor 102 provides the clamping force to grasp the explosive box.

[0048] S5: After the grasping is completed, the rotating base 109 drives the robotic arm 12 to rotate on the horizontal plane, moves the explosive box above the designated stacking position of the pallet 207 on the receiving transport vehicle 2. The boom 107 and the forearm 105 adjust their postures again. The pitching motor 104 of the grasping claw controls the pitching of the grasping claw 101 in the vertical direction, and accurately places the explosive box on the pallet 207. Repeat the grasping and stacking actions to complete the palletizing operation of one pallet 207.

[0049] S6: The third image acquisition unit 203 of the receiving transport vehicle 2 is installed on both sides of the second moving base, continuously collects the surrounding environment parameters, including information such as terrain, obstacles, warehouse entrance position, and other equipment positions, and feeds them back to the second control unit 205 in real time.

[0050] S7: The second control unit 205 is built-in with algorithms and logic judgment modules, analyzes and processes the environmental information, combines the preset map and the requirements of the operation task, plans the optimal transportation path from the current position to the warehouse, controls the rotation direction and speed of the tires 204, so that the receiving transport vehicle 2 drives along the planned path towards the warehouse, and adjusts the path in a timely manner according to the monitoring information of the third image acquisition unit 203 during the transportation process.

[0051] Specifically, the built-in algorithm of the second control unit 205 is a multi-objective dynamic path planning and cooperative control algorithm (MD-PCCA). 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 specifically 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 dynamic obstacle speed vector v x ,v y , such as the speed vector of personnel or other mobile devices. The vehicle state parameters are the current position (X current ,Y current ) of the receiving transport vehicle 2, the rotation speed (ω tire ) of the tires 204, and the height (H pallet ) of the pallet rack 210. The task constraint is the topological structure of the preset map (such as the path node N i , the 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), where g2(n) represents the actual path length (considering the tire 204 wear coefficient μtire ), h2(n) represents the heuristic function (Manhattan distance combined with terrain slope correction), and DynamicRisk(n) represents the dynamic risk assessment (predicting the collision probability based on the obstacle speed). And this model can achieve real-time replanning, updating the path every 100 ms to respond to sudden obstacles.

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

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

[0055] Through the above algorithm, vehicle control instructions, pallet rack 210 action instructions, and safety warning signal output parameters can be obtained. The role of the vehicle control instructions is to ensure that the transport vehicle moves smoothly along the optimal path and avoids dynamic obstacles. The specific output parameters are the steering angle θ steer ∈ [-30°, 30°] and the rotational speed ω tire ∈ [0.5, 2] rad / s. The pallet rack 210 action instructions ensure adaptation to different operation 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 replanning the path or stopping the operation when detecting signals such as static electricity.

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

[0057] S8: After the receiving transport vehicle 2 arrives at the warehouse or the designated stacking area, the pallet rack lifting mechanism 208 performs lifting operations according to actual operation requirements. When cooperating with an unloading forklift, the height of the pallet rack 210 is adjusted according to the height of the forklift's fork teeth; when cooperating with the handling and palletizing robot 1, it is adjusted in real time according to the operating height of the robotic arm 12.

[0058] S9: During the palletizing operation, when the palletizing operation on one side of the pallet rack 210 is completed, the rotating mechanism 206 rotates the pallet rack 210 to the other side through the slewing bearing and the driving device, and the palletizing operation continues on the other side, without the need for the receiving transport vehicle 2 to turn around or reposition.

[0059] S10: After the robotic arm 12 completes the palletizing operation on one pallet rack 210, the boxed emulsion explosive stack alignment mechanism 201 is quickly activated. The clamping arms are pushed towards both sides of the stack through a high-precision linear driving device, and a clamping force is applied to the stack using a material with a soft and friction-bearing contact part, so that the explosive boxes are closely arranged, and the alignment is controlled within the specified error range, while avoiding scratching the surface of the explosive boxes. The rigid support frame 209 in the middle provides additional support for the pallet rack 210, enhancing its stability and preventing deformation or shaking.

[0060] S11: The handling and palletizing robot 1 and the receiving transport vehicle 2 communicate and cooperate through the first control unit 112 and the second control unit 205. After the handling and palletizing robot 1 completes the palletizing operation on one pallet rack 210, it notifies the receiving transport vehicle 2 to operate. The receiving transport vehicle 2 feeds back status information to the handling and palletizing robot 1 during transportation or operation. The operator can also remotely monitor and intervene to ensure the safe and efficient operation of the system, realizing the full automation of the whole process of unloading, palletizing, and handling of boxed emulsion explosives.

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

Claims

1. A method for unloading, stacking and transporting boxed emulsion explosives, characterized in that, Including: S1. The handling and palletizing robot scans the boxed emulsion explosives in the carriage of the transport vehicle to obtain the placement position information of the boxed emulsion explosives; S2. The handling and palletizing robot adjusts its speed and direction in real time according to the placement position information of the boxed emulsion explosives and moves to the optimal vehicle unloading position; S3. The handling and palletizing robot uses the second image acquisition unit on the robotic arm to obtain the placement position information of the boxed emulsion explosives again, including the two-dimensional plane coordinates, depth information and attitude angle information of the boxed emulsion explosives; S4. According to the placement position information of the boxed emulsion explosives obtained in S3, as well as the preset palletizing rules and sequence, generate a robotic arm movement instruction and use the robotic arm to grab the boxed emulsion explosives; S5. The robotic arm transfers the boxed emulsion explosives to the receiving transport vehicle and keeps the boxed emulsion explosives in a horizontal state. Repeat S3 - S5 until the transfer of the boxed emulsion explosives is completed; S6. The receiving transport vehicle collects environmental parameters, including terrain, obstacles and warehouse entrance position information; S7. Analyze and process the environmental parameters in real time, and combine with the map and operation task requirements to plan the optimal transport path from the current position to the designated position in the warehouse; S8. The receiving transport vehicle moves to the designated position in the warehouse for unloading operations.

2. The method for unloading, stacking and transporting boxed emulsion explosive according to claim 1, wherein S8 also includes that the pallet rack lifting mechanism on the receiving transport vehicle performs lifting operations according to the operation requirements. If it cooperates with the unloading forklift, the height of the pallet rack is adjusted according to the height of the forklift forks; if it cooperates with the handling and palletizing robot, the height of the pallet rack is adjusted in real time according to the operation height of the robotic arm.

3. The method for unloading, stacking and transporting boxed emulsion explosives according to claim 1, characterized in that In S2, the speed and direction are adjusted in real time through the dynamic path planning and attitude optimization algorithm. The input parameters of the dynamic path planning and attitude optimization algorithm include the position information data of the boxed emulsion explosive, the input environmental parameters, and the motion constraint conditions of the robotic arm. The position information data of the boxed emulsion explosive includes the two-dimensional plane coordinates x and y, the height information z, the attitude angle θ, the boundary coordinate information of the transport vehicle carriage, and the obstacle position information. The environmental parameters include the ground friction coefficient μ, the site slope α, and the dynamic information of the obstacles. The motion constraint conditions of the robotic arm include the length L1 of the upper arm, the length L2 of the forearm, the maximum rotational speed ω of the joint motor max and the maximum clamping force F of the robotic arm max ; An improved A* algorithm is adopted. 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 the 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 the dynamic weight coefficient; The path planning is dynamically adjusted, and the path is recalculated according to the cost function at preset time intervals.

4. The method for unloading, stacking and transporting boxed emulsion explosives according to claim 3, characterized in that, It also includes robotic arm attitude optimization. Based on inverse kinematics and energy minimization, inverse kinematics solution calculates the pitch angle φ1 of the upper arm and the pitch angle φ2 of the lower arm according to the two-dimensional plane coordinates x and y, height information z and attitude angle θ. The calculation methods of the pitch angles of the upper arm and the lower arm are as follows: φ2 = θ - φ1 Adopt the solution that minimizes the total energy consumption of the joint motors, that is: where k i is the efficiency coefficient of motor i.

5. The method for unloading, stacking and transporting boxed emulsion explosives according to claim 4, characterized in that, Clamping force F of the robotic arm grip Adaptive, based on the weight m of the boxed emulsion explosive and the friction coefficient μ box Dynamically adjust the clamping force. The specific calculation process is: F grip = min(1.5·m·g·μ box , F max ).

6. The unpacking, stacking and handling method of boxed emulsion explosive according to claim 5, characterized in that, When it is detected that the static electricity accumulation exceeds the threshold Q max or the distance to the obstacle is less than the safe distance, an emergency stop or path adjustment is triggered.

7. The method for unloading, stacking and transporting boxed emulsion explosives according to claim 1, characterized in that, In S7, a multi-objective dynamic path planning and cooperative control algorithm is used to plan the path. The input parameters of the multi-objective dynamic path planning and cooperative control algorithm are environmental parameters, the state parameters of the material receiving transport vehicle, and task constraints. The environmental parameters include the terrain elevation h, the obstacle coordinates O x and O y , the warehouse entrance coordinates W x and W y and the dynamic obstacle velocity vector v x , v y ; the state parameters of the material receiving transport vehicle include the current position X current , Y current of the material receiving transport vehicle, the tire rotation speed ω tire , the height H pallet of the pallet rack; the task constraint is the topological structure of the preset map, including the path node N i , the safety distance threshold d safe ; the dynamic path planning module is based on the improved D*Lite algorithm, and its adaptive cost function is: f2(n) = g2(n) + ε·h2(n) + γ·DynamicRisk(n), where g2(n) is the actual path length considering the tire wear coefficient μ tire , h2(n) is the heuristic function, DynamicRisk(n) is the dynamic risk assessment, ε is the weight coefficient of the heuristic function h(n), and γ is the weight coefficient of the dynamic risk cost DynamicRisk(n); the path is updated at preset time intervals.

8. The method for unloading, stacking and transporting boxed emulsion explosives according to claim 7, characterized in that, It also includes multi-objective optimization based on the NSGA-II framework, with the optimization objectives being the minimum transportation time, the minimum energy consumption, and the maximum safety factor; the operation method for the minimum transportation time is wherein, L i is the segmented path length, and v i is the driving speed of the segmented path; the operation method for the minimum energy consumption is ω i is the energy consumption weight coefficient of the segmented path; the operation method for the maximum safety factor is d obstacle is the minimum distance between the boxed emulsion explosive and the obstacle; the constraint conditions of the objective function are: the rotation angle θ of the pallet rack pallet ≤ 45° / s, and the maximum rotational speed ω of the tire tire ≤ 2 rad / s; the output parameters are the tire steering angle θ steer ∈ [-30°, 30°] and the rotational speed ω tire ∈ [0.5, 2] rad / s, and the pallet rack action instructions include the lifting height H pallet ∈ [0.5, 2.0] m and the rotation angle θ pallet ∈ [0°, 360°].

9. A boxed emulsion explosive unloading, stacking and handling system, characterized in that, Using the method according to claim 1, including a handling and palletizing robot and a receiving transport vehicle; the handling and palletizing robot includes a first moving base and a robotic arm. A first control unit and a first image acquisition unit are provided on the first moving base; the robotic arm includes a rotating base, an upper arm, a lower arm and a gripper. The rotating base is fixed on the first moving base, and a second image acquisition unit is provided on the gripper; the receiving transport vehicle includes a second moving base and a pallet rack. A second control unit and a third image acquisition unit are provided on the second moving base, and the pallet rack is used to place the pallet.

10. The palletizing and handling system for unloading boxed emulsion explosive according to claim 9, characterized in that, The receiving transport vehicle also includes a rotating mechanism provided on the moving base. There are two groups of pallet racks symmetrically arranged on the rotating mechanism. It also includes a pallet rack lifting mechanism. One end of the pallet rack lifting mechanism is connected to the pallet rack and the other end is connected to the rotating mechanism for lifting the pallet rack.

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