INTELLIGENT DISTRIBUTION VEHICLE AND ASSEMBLY PROCESS FOR IT

Abstract

The present invention relates to an intelligent distribution vehicle (110) comprising: a first support part (202) for supporting a sensor part (201) for detecting an object, a second support part (203) for supporting the sensor part (201) at the upper portion of the first support part (202), and a position regulating part (204) for regulating the second support part (203) such that initial position information of the sensor part (201) is maintained while the sensor part (201) is supported on the second support part (203), and aligning, upon replacement of the sensor part (201), an initial position of a replacement sensor part (201) based on the initial position information of the sensor part (201).

Description

Technical area

[0001] The present disclosure relates to an intelligent distribution vehicle and a control method thereof which can shorten the adjustment time of a replacement sensor part when replacing a sensor part. Background technology

[0002] In general logistics warehouses and factories, as well as in smart factories where products with different specifications are manufactured using numerous components, smart distribution vehicles are introduced for the flexible and efficient delivery and transportation of components, etc.

[0003] Intelligent distribution vehicles are a concept that collectively refers to autonomous mobile robots (AMRs), automated guided vehicles, and unmanned stacker devices or forklifts, and these intelligent distribution vehicles can move and perform tasks under the control of a control system.

[0004] Currently, a smart distribution vehicle can move by determining its position based on map information from the smart factory, which is generated and collected by a LiDAR sensor or a camera sensor for obstacle detection. Furthermore, for the smooth movement of smart distribution vehicles, it is important to adjust the correct angle and height of a sensor to generate accurate map information.

[0005] However, if a sensor fails and is replaced with another sensor, the replacement sensor must be initially adjusted to the exact position the replaced sensor was set to before the replacement. Otherwise, smooth movement may be difficult due to inconsistencies in the map information. Furthermore, depending on the complexity of the map, adjusting the sensor's initial position after replacement can be time-consuming, which is problematic.

[0006] The above description of the related art of the present disclosure is merely intended to assist in understanding the background of the present disclosure and is not to be construed as being included in the related art as known to those skilled in the art. RevelationTechnical Problem

[0007] The present disclosure is intended to solve the above-mentioned problems encountered in the related art. An object of the present disclosure is to provide an intelligent distribution vehicle that can shorten the time required for the initial setup of a replacement sensor part based on initial position information when replacing a sensor part, and an assembly method of the intelligent distribution vehicle.

[0008] The objects of the present disclosure are not limited to those mentioned above, and other objects not mentioned will be clearly understood by those skilled in the art from the following description. Technical solution

[0009] To achieve the above-mentioned objects, an intelligent distribution vehicle is provided, comprising: a first support part configured to support a sensor part for detecting an object, a second support part configured to support the sensor part on an upper surface of the first support part, and a position regulating part configured to regulate the second support part so as to maintain initial position information of the sensor part while the sensor part is supported on the second support part, and to align an initial position of a replacement sensor part based on the initial position information of the sensor part when replacing the sensor part.

[0010] For example, the sensor part may include a 2D LiDAR sensor, a 3D LiDAR sensor, and a 3D camera sensor.

[0011] For example, the sensor part can be supported at the back and bottom by the second support part.

[0012] For example, the second support member may be provided such that it is detachable from the position regulating member.

[0013] For example, the second support part can be replaced when the sensor part is replaced.

[0014] For example, the second support member may be provided such that it is detachable from the position regulating member.

[0015] For example, the position regulating member may be provided in a plurality and connect the first support member and the second support member in a vertical direction.

[0016] For example, the initial position information of the sensor part may include at least one of information about an inclination formed by the second support part and the sensor part, and information about a width, a height, and an angle formed by the first support part and the sensor part.

[0017] For example, the position regulation part may ensure that the initial position information of the sensor part is maintained based on spatial map information acquired by the sensor part.

[0018] Furthermore, according to an embodiment of the present disclosure, an assembly method for an intelligent distribution vehicle is provided, the method comprising: determining a malfunction of a sensor part based on initial position information of the sensor part in the intelligent distribution vehicle having the sensor part for detecting an object, a first support part for supporting the sensor part, a second support part for supporting the sensor part at an upper surface of the first support part, and a position regulating part for regulating the second support part; replacing the sensor part and the second support part when the sensor part malfunctions; and aligning an initial position of a replacement sensor part based on the initial position information of the sensor part when replacing the sensor part.

[0019] For example, the sensor part may include a 2D LiDAR sensor, a 3D LiDAR sensor, and a 3D camera sensor.

[0020] For example, the second support member may be provided such that it is detachable from the position regulating member.

[0021] For example, the position regulating member may be provided in a plurality and connect the first support member and the second support member in a vertical direction.

[0022] For example, the initial position information of the sensor part may include at least one of information about an inclination formed by the second support part and the sensor part, and information about a width, a height, and an angle formed by the first support part and the sensor part.

[0023] For example, the position regulation part may ensure that the initial position information of the sensor part is maintained based on spatial map information acquired by the sensor part. Beneficial effects

[0024] According to various embodiments of the present disclosure, as described above, it is possible to shorten the time required for the initial setup of a replacement sensor part based on initial position information when replacing a sensor part. Furthermore, due to the shortened time, a smart distribution vehicle can be started immediately, thereby improving operating times.

[0025] The effects of the present disclosure are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description. Description of the drawings Fig. 1 is a block diagram showing an example of a configuration of a smart factory that can be applied to embodiments of the present disclosure. Fig. 2 is a block diagram showing an example of a control system configuration that can be applied to embodiments of the present disclosure. Fig. 3 is a block diagram showing an example of a configuration of an intelligent distribution vehicle that can be applied to embodiments of the present disclosure. Fig. 4 is a block diagram showing an example of the appearance of an intelligent distribution vehicle that can be applied to embodiments of the present disclosure. Fig. 5 is a flowchart showing an example of a driving operation of an intelligent distribution vehicle that may be applied to embodiments of the present disclosure. Fig. 6 is a block diagram showing an example of a detection part constituting an intelligent dispatch vehicle according to an embodiment of the present disclosure. Fig. 7 is a configuration diagram showing an example of a configuration of an intelligent distribution vehicle according to an embodiment of the present disclosure. Fig. 8 is a flowchart showing an example of a method for assembling an intelligent distribution vehicle according to an embodiment of the present disclosure. Statements on the invention

[0026] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings, but identical or similar components will be denoted by the same reference numerals regardless of the numbers in the drawings, and redundant descriptions thereof will be omitted. The terms "module" and "unit" used for components in the following description are indicated or used interchangeably only for the convenience of writing the description and have no different meaning or role in themselves. If it is decided in the following description that the detailed description of known technologies related to the present disclosure makes the subject matter of the embodiment described here unclear, the detailed description will be omitted.In addition, the accompanying drawings are only for the purpose of facilitating the understanding of the embodiment disclosed in the specification, and the technical nature disclosed in the specification is not limited by the accompanying drawings, and all modifications, equivalents, and substitutions should be understood as being included within the spirit and scope of the present disclosure.

[0027] Terms with ordinal numbers, such as "first," "second," etc., may be used to describe numerous components, but the components should not be construed as being limited to these terms. The terms are used only to distinguish one component from another.

[0028] It should be understood that when an element is described as being "connected to" or "coupled to" another element, it may be directly connected or directly coupled to another element, or it may be connected or coupled to another element with the further element present therebetween. On the other hand, it should be understood that when an element is described as being "directly connected to" or "directly coupled to" another element, it may be connected or coupled to another element without the further element present therebetween.

[0029] The singular forms include plural forms unless the context clearly indicates otherwise.

[0030] It is further understood that the terms "comprise (include)" or "have" as used in this specification indicate the presence of certain features, steps, operations, components, parts, or a combination thereof, but do not preclude the presence or addition of one or more other features, numbers, steps, operations, components, parts, or a combination thereof.

[0031] Furthermore, the terms "unit" or "control unit," included in electric motor control unit (MCU), hybrid control unit (HCU), etc., are merely generic terms used to refer to control devices that control specific vehicle functions and do not imply general functional units. Each control device may include, for example, a modem / transceiver that communicates with another control device or sensor to control corresponding functions, a memory that stores an operating system or logical instructions and input / output information, and one or more processors that perform detection, calculation, decision, etc., to control the corresponding functions. Depending on the implementation, a processor may be responsible for the operations of multiple control devices.

[0032] First, the configuration of a smart factory in which a smart distribution vehicle according to an embodiment is deployed and operated will be described with reference to Fig. 1 described.

[0033] Fig. 1 is a block diagram showing an example of a configuration of a smart factory that can be applied to embodiments of the present disclosure.

[0034] With reference to Fig. 1, a smart factory 100 may include a smart distribution vehicle 110, a production device 120, a monitoring device 130, and a control system 140.

[0035] Depending on the production process and target production rate, the smart factory 100 may be equipped with a plurality of smart distribution vehicles 110, a plurality of production devices 120, and a plurality of monitoring devices 130. The individual components are explained below.

[0036] First, the intelligent distribution vehicle 110 may include an autonomous mobile robot (hereinafter referred to simply as "AMR"), an automated guided vehicle (hereinafter referred to simply as "AGV"), and an unmanned stacker or forklift. Depending on the operating strategy of the intelligent distribution vehicle 110 in the smart factory 100, only one type of AGV or AMR may be operated, or the AGV and AMR may be operated jointly in a single smart factory 100.

[0037] The AGV generally performs the required operations (movement, change of direction, stop, etc.) within the smart factory 100 by detecting and following guidance tools placed on the floor to guide the AGV. In this case, the guidance tools may be, but are not limited to, optically detectable markers (dots, 2D codes, etc.), near-contact tags (e.g., NFC tags, RFID tags, etc.), magnetic stripes, wires, etc. The guidance tools may be continuously arranged on the floor or discontinuously spaced apart. Since the AGV essentially performs its tasks by detecting and following the guidance tools, the guidance tools must be installed prior to operation.If the AGV needs to move along a new path or change an existing path, it is necessary to physically construct or modify the guidance instruments. Furthermore, since the AGV will not deviate from a path established using the guidance instruments, if an obstacle is detected on or around the path, the AGV will normally stop until the detected obstacle disappears or receive separate commands. When operating the AGV, the control system 140 must control the AGV based on the guidance instruments. Thus, the control system 140 can send commands, such as "drive until a third marker is detected" or "change the heading direction by 90 degrees when the third marker is detected," to the AGV from the current position, in units of individual commands or as tasks comprising multiple commands (e.g., retrieval, supply, loading, patrol, etc.).

[0038] The AMR can determine the current position (i.e., a tracking) by sensing the environment and differs from the AGV primarily in that the AMR is capable of planning its path using tracking and maps. Thus, when a map with compatible coordinates is exchanged between the AMR and the control system 140, the control system 140 is capable of controlling the AMR by instructing the AMR to take a coordinate-based path. Furthermore, if an obstacle is detected during travel, the AMR can plan an alternate path to avoid the obstacle and then return to the original path. The function of the control system 140 to plan the AMR's path to one or more transit coordinates may be referred to as global path planning, and the function of the AMR to plan a path or an alternate path between transit coordinates according to the global path planning may be referred to as local path planning.

[0039] A more detailed configuration of the intelligent distribution vehicle 110 is described below with reference to the Fig. 3 and Fig. 4, and a driving control operation of the AMR will be described later with reference to Fig. 5 described.

[0040] Next, the production device 120 may refer to a device (e.g., a robot arm, a conveyor belt, etc.) that performs the production process of a product in the smart factory 100. More broadly, the production device 120 may refer to a device used to assist in performing tasks, such as the entry and exit of the smart distribution vehicle 110, when the production process is performed by humans.The device used to support task performance may be, but is not limited to, a device that detects the status of a particular position at which a pallet carried by the intelligent distribution vehicle 110 can be deposited or picked up within an area in which a particular production process is performed, a device that determines the process progress, or a means for blocking access to an area, etc.

[0041] The production device 120 is controlled, for example, via a programmable logic controller (PLC) and can communicate with the control system 140 regarding the process progress.

[0042] The monitoring device 130 may perform the function of obtaining information to determine the situation within the smart factory 100 and transmitting the obtained information to the control system 140. The monitoring device 130 may include, for example, but is not necessarily limited to, a camera, a proximity sensor, etc.

[0043] The control system 140 can communicate with the above-described components 110, 120, and 130 to obtain information necessary for the operation of the smart factory 100, or can control each component. For example, the control system 140 can perform dispatching of the smart distribution vehicle 110, path determination, task assignment, process management for each product, material management, etc.

[0044] In implementation, the control system 140 may include an AMR / AGV control system (ACS), which controls the surrounding process equipment based on the position of the AGV / AMR and performs task-based control of the AGV / AMR, and a mobile robot integrated monitoring system (MoRIMS), which integrates and controls two or more AMR / AGV control systems. The MoRIMS may perform control of the status and path of all intelligent distribution robots 110, distribution flow settings, and traffic in the smart factory 100 using individual ACSs. ​​For example, if the ACS is provided as intelligent distribution robot units of the same manufacturer or model, the MoRIMS may provide integrated control for collision avoidance, such asperform an analysis of bottleneck levels in intersection areas / overlapping areas, an acceleration / deceleration control and a regeneration of alternative paths through a heterogeneous traffic distribution control based on information obtained by the ACS.

[0045] In addition, the MoRIMS can also have a manufacturing execution system (MES) as the higher-level control instance, and the MES can be linked to advanced planning and scheduling (APS).

[0046] In addition to the configurations 110, 120, 130 and 140 of the smart factory 100 described above, facilities for mutual communication between individual components such as beacons, signal repeaters, access points (APs), etc., chargers for charging the smart distribution vehicle 110, loading rooms for storing or charging components, rooms in which finished products or intermediate products are stored, traffic lights, circuit breakers, waiting rooms for stationary smart distribution vehicles 110, etc., can be arranged in a suitable manner within the smart factory 100.

[0047] Hereinafter, the configuration of the control system 140, which can be applied to the embodiments of the present disclosure, will be described with reference to Fig. 2 described.

[0048] Fig. 2 is a block diagram showing an example of a control system configuration that can be applied to embodiments of the present disclosure. Each Fig. 2 mainly represents components related to the embodiments of the present disclosure, and more or fewer components may be included in the actual implementation of the control system 140.

[0049] With reference to Fig. 2, the control system 140 may include a firmware management part 141, a traffic control part 142, a process management part 143, a production / logistics management part 144, an inventory management part 145, a communication part 146, a vehicle monitoring part 147, and a map management part 148.

[0050] The firmware management part 141 can obtain the latest firmware of the intelligent distribution vehicle 110 via the communication part 146, transmit the firmware to the intelligent distribution vehicle 110, and perform a firmware update to keep the firmware of the intelligent distribution vehicle 110 up to date.

[0051] The traffic control part 142 can control traffic lights and barriers based on a path of the intelligent dispatch vehicle 110 and recalculate the path of the intelligent dispatch vehicle 110 according to the traffic.

[0052] The process management part 143 can define processes for each product and manage tasks such as a process progress and a progress position.

[0053] The production / logistics management 144 can dispatch the intelligent distribution vehicle 110 based on the task.

[0054] The inventory management part 145 manages the position and quantity of each material, and this information can be used for more efficient process flow, e.g., driving the intelligent distribution vehicle 110 to the destination before the time at which the actual assembly / consumption of a material is detected, for pallet pickup or restoration, etc.

[0055] The communication part 146 can communicate with internal components of the smart factory 100, such as the smart distribution vehicle 110, the production device 120, and the monitoring device 130, as well as with external entities, such as a firmware update server, etc.

[0056] The vehicle monitoring part 147 can monitor the position, path, battery status, communication status, powertrain status, etc. of the individual intelligent dispatch vehicle 110. In this case, the path is a concept that includes a waypoint-based global path and a local real-time path. Furthermore, the battery status can include voltage, current, temperature, peak voltage and current values, state of charge (SOC), state of health (SOH), etc. The communication status can include information about the currently active communication protocol (Wi-Fi, etc.), the connected AP, the distance to the AP, the channel in use, etc. The powertrain status can include the powertrain load, temperature, speed, etc.

[0057] In addition, the vehicle monitoring part 147 can check the task currently assigned to the individual intelligent dispatch vehicle 110, the operation mode, the firmware version, etc.

[0058] The map management part 148 can acquire map data in the form of a grid map, which is acquired while the AMR of the intelligent distribution vehicles 110 is traveling within the smart factory 100, and provide a tool that allows a factory manager to edit the acquired map data. By editing the map data, zones in which the intelligent distribution vehicle 110 performs one or more preset operations upon entry, virtual lanes, intersections, and no-entry zones can be specified, but this is only an example and is not necessarily limited to these. Furthermore, the map management part 148 can distribute the map to the remaining intelligent distribution vehicles 110, excluding the intelligent distribution vehicle 110 that acquired the original grid map through actual driving, via the communication part 146.

[0059] Next, the intelligent distribution vehicle is designed with reference to the Fig. 3 and Fig. 4 described.

[0060] Fig. 3 is a block diagram showing an example of the configuration of an intelligent distribution vehicle that can be applied to embodiments of the present disclosure.

[0061] Referring to Fig. 3, the intelligent distribution vehicle 110 may include a drive part 111, a detection part 112, a loading part 113, a communication part 114, and a control device 115. Each component is described below.

[0062] The drive part 111 may include a torque source, wheels, and a suspension system involved in moving, steering, and stopping the intelligent distribution vehicle 110. The torque source may be an electric motor powered by a built-in battery (not shown). The wheels may include one or more drive wheels that receive driving power from the torque source and a non-drive wheel that rotates due to the movement of a vehicle body without receiving driving power. Depending on the configuration, if a plurality of drive wheels are provided, the torque source is provided for each drive wheel so that the rotation of each drive wheel can be controlled independently. In this case, by changing the rotation directions of the various drive wheels, steering by turning the vehicle body can be achieved without a separate steering device.At least some of the non-drive wheels may be formed from roller-like wheels, but this is only an example and is not necessarily limited thereto.

[0063] The sensing part 112 is for detecting the surrounding environment or the self-operation status of the intelligent dispatch vehicle 100. The sensing part 112 may include at least one of 2D and 3D laser scanners (e.g., LiDAR), a 3D vision (stereo) camera, a multi-axis gyro sensor, an acceleration sensor, a wheel encoder, and a proximity sensor.

[0064] The encoder can output information for determining how much a wheel has rotated using light emitted by a light-emitting device (e.g., a photodiode). For example, the encoder can count the number of slits arranged along the circumference of a wheel or a disk rotating with the wheel during a unit of time. The controller 115 is capable of performing odometry, which determines displacement, by analyzing the amount of position change versus time using the data obtained by the encoder and the gyro sensor. However, the displacement determined based on the encoder data may differ from the actual displacement due to wheel slippage or wear (change in wheel radius).Therefore, when performing odometry, the controller 115 can correct the information collected by the wheel and gyro sensors for noise and errors using a predetermined algorithm (e.g., an extended Kalman filter (EKF)) and output results that are close to the actual values. Such odometry can be particularly useful when localization with a 2D laser scanner, which will be described later, is not possible.

[0065] The 2D laser scanner can scan the surrounding environment by emitting a laser through a rotating reflector into the surrounding area and detecting a reflected signal. The intensity of the signal in question and the time difference between emission and reception can be analyzed to output a detection result in the form of a point cloud.

[0066] The 3D vision camera can calculate the distance to an object based on the parallax between two cameras separated by a certain distance, i.e., the pixel pitch between the images captured by each camera. A texture projector, which projects infrared light with a predetermined pattern, can be provided to detect a flat object of the same color (e.g., a white wall).

[0067] Generally, the 2D laser scanner is used for mapping, navigation, object detection, etc., and the 3D camera can be used especially for obstacle avoidance during navigation, but this is just an example and is not necessarily limited to it.

[0068] The loading part 113 is a means for loading goods to be transported and can be an upper plate itself on top of the vehicle body, a table placed on the upper plate, a lift, a turntable rotating around a vertical axis, a forklift, a conveyor belt, or a combination thereof. In the case of a forklift, telescopic and tilting functions can be provided similar to a stacker device.

[0069] The communication part 114 can communicate with other components in the smart factory 100, such as the production device 120 and the control system 140. The communication part 114 can also support communication between smart distribution vehicles 110 and communicate with a charger when a charging process is performed.

[0070] The control device 115 is the unit that performs the overall control of each of the above-described components 111, 112, 113, and 114. The control device 115 can perform the current task, the current position, and the destination determination, as well as the path planning and control of the loading part based on information it receives from the control system 140 via the communication part 114.

[0071] Fig. 4 is a block diagram showing an example of the appearance of an intelligent distribution vehicle that can be applied to embodiments of the present disclosure

[0072] With reference to Fig. 4, an example of an AMR as an intelligent distribution vehicle 110 is shown. The vehicle body may have a track-like, flat shape with a long axis extending along a first axial direction. A drive wheel 111-1 is arranged in the center of the vehicle body in the first axial direction and may be arranged on one side in a second axial direction, while another drive wheel (not shown) may be arranged on the other side to oppose the one drive wheel 111-1 in the second axial direction. Such an arrangement of drive wheels may be referred to as a "differential drive (DD)". Although in Fig. 4, two or more non-drive wheels may be arranged at the lower part of the vehicle body. In this case, when the two drive wheels rotate in the same direction and at the same speed, forward or backward movement along the first axial direction is possible, and when they rotate in opposite directions at the same speed, the drive wheels can rotate based on the rotation axis extending along a third axial direction and passing through a plane center C of the vehicle body. Furthermore, the detection part 112 may be arranged on the front surface of the vehicle body, and the loading part 113 may be arranged on the upper surface of the vehicle body. The loading part 113 may be configured to be raised and lowered along the third axial direction, and a rack or tray, etc., may be attached to its upper surface via a guide 113-1.

[0073] The AMR form of Fig. However, Figure 4 is an example, and the AGV may have a similar shape, or the AMR may have a different shape.

[0074] Next, the driving operation of the intelligent distribution vehicle 110 will be described with reference to Fig. 5 described.

[0075] Fig. 5 is a flowchart showing an example of a driving operation of an intelligent distribution vehicle that can be applied to embodiments of the present disclosure. In Fig. 5, it is assumed for the sake of simplicity that the intelligent distribution vehicle 110 is an AMR which is capable of performing positioning and local path planning.

[0076] With reference to Fig. 5, the AMR can first obtain a ground truth grid map through LiDAR, etc. (S501) while driving within the smart factory 100.

[0077] When the AMR transmits the acquired grid map to the control system 140, operations for editing and adjusting the grid map may be performed in the map management part 148 of the control system 140 (S502). In this case, the editing operation may include a process of defining the above-described various zones in the above-described grid map, a process of assigning costs to each grid, and so on. At this time, the cost allocation may be performed such that the closer an obstacle or a no-entry zone is, the higher the cost, so that the AMR does not avoid the obstacle or enter a zone the AMR should not enter. This is because, when planning a local path, the AMR selects the set of cells with the lowest cost between the waypoints as the path.

[0078] In addition, the map matching process may refer to a process of coordinate matching between a CAD map used in the design of the smart factory 100, the ground truth grid map (LiDAR map), and the topology map that has undergone the editing process.

[0079] Thereafter, the control system 140 can share the topology map with all AMRs in the factory via the communication part 146 (S503).

[0080] The following steps may be operations that are applied to individual AMRs.

[0081] The AMR can determine the current position (localization) (S504) on the map based on the sensor data from the sensor part 112 and the acquired map. For example, the AMR can determine the current position by comparing the surrounding terrain and the map obtained by LiDAR based on feature points.

[0082] The control system 140 can select a specific AMR and assign it a task, and one or more waypoints can be assigned to the task, typically determined by global path planning. The waypoint can be defined as a coordinate on a map and provided with information about the direction (i.e., the heading) the AMR should take at the coordinate. According to this task assignment, a destination can be set in the AMR (Yes in S505), and the AMR can perform local path planning between waypoints based on the topology map costs (S506).

[0083] Once the path is determined, the AMR begins driving (S507), and if an obstacle is detected by the sensing part 112 during driving (Yes in S508), the AMR can perform an evasive maneuver (S509) by performing a local path search to avoid the detected obstacle. In some cases, and depending on an evasive maneuver or the failure of the evasive maneuver, the control system 140 can update the task of the corresponding AMR.

[0084] In addition, the AMR can correct position errors (S510) during movement using the odometry technique described above while driving until the destination is reached.

[0085] After reaching the destination (S511), the AMR can perform task-based maneuvers (S512). For example, the AMR can determine whether the conditions for entering a specific process area are met, pick up an empty pallet from the destination, or deposit the load loaded on the loading section 113.

[0086] In one embodiment of the present disclosure, an intelligent dispatch vehicle 110 is proposed which can shorten the time required for initial position adjustment by simply replacing a sensor part based on information about an initial position regulated by mechanical adjustments when the sensor part malfunctions.

[0087] In the following, the intelligent distribution vehicle according to an embodiment is described with reference to the Fig. 6 and Fig. 7 described.

[0088] Fig. 6 is a block diagram showing an example of a detection part constituting an intelligent distribution vehicle according to an embodiment of the present disclosure. Fig. 7 is a configuration diagram showing an example of a configuration of an intelligent distribution vehicle according to an embodiment of the present disclosure.

[0089] With reference to Fig. 6, the detection part 112 may include a sensor part 201, a first support part or first holding part 202, a second support part or second holding part 203, and a position regulation part 204. First, the first support part 202 may support or hold the sensor part 201 for detecting an object. The sensor part 201 is not limited to examples of the detection part 112 described above, such as 2D and 3D laser scanners (e.g., LiDAR), a 3D vision (stereo) camera, a multi-axis gyro sensor, an acceleration sensor, a wheel encoder, and a proximity sensor, and may also include devices that require the securing of initial setting information. As shown in Fig. As shown in Figure 7, the first support part 202 is the AMR main body and can support the rear and lower surfaces of the second support part 203 and the position adjustment part 204, which will be described later. The lower surface of the first support part 202 is formed in a flat structure to facilitate the measurement of height and angle information with the sensor part 201, while the rear surface of the first support part 202 can be formed in a structure orthogonal to the sensor part 201 to facilitate the measurement of width information.

[0090] In addition, the second support part 203 can support or hold the sensor part 201 on the top side of the first support part 202. Referring to Fig. 7, the rear and lower surfaces of the sensor part 201 can be supported by the second support part 203, similar to the first support part 202. The second support part 203 can be adjusted between the first support part 202 and the sensor part 201 by the position adjustment part 204, which will be described later. The second support part 203 is a holder that can fix the sensor part 201 in a precise position, and by simply replacing the second support part 203 with the first support part 202, immediate operation is possible based on the initial position information of the sensor part 201 without setting separate parameters.

[0091] Specifically, when replacing the sensor part 201, the initial position alignment of the replacement sensor part 201 may be performed by the position adjustment part 204. In this case, the position adjustment part 204 may adjust the second support part 203 to maintain the initial position information of the sensor part 201 while supporting the sensor part 201 on the second support part 203. At this time, the position adjustment part 204 may maintain the initial position information based on the spatial map information detected by the sensor part 201 and adjust the initial position of the sensor part 201 by preventing the initial position information from changing based on the previously acquired spatial map information when the sensor part 201 is replaced.

[0092] The method of initial position adjustment of the position adjustment part 204 may be based on the initial position information of the sensor part 201 before replacement. In this case, the initial position information of the sensor part 201 may include at least one of tilt information, height information, and angle information. The tilt information may be obtained based on the tilt formed by the sensor part 201 and the second support part 203, and the width, height, and angle information may be obtained based on the width, height, and angle formed by the sensor part 201 and the first support part 202.

[0093] Thus, the position regulating part 204 regulates the position of the second support part 203 so that the initial position of the sensor part 201 is maintained, and by regulating the position of the second support part 203, the sensor part 201 is also regulated to its initial position. In a state in which the second support part 203 is fixed to the sensor part 201, when the sensor part 201 is replaced, the second support part 203 is also replaced, making it possible to quickly align the initial position of the replacement sensor part 201 with the first support part 202. For this purpose, the second support part 203 can be provided so that it is detachable from the position regulating part 204.

[0094] Furthermore, the position regulating part 204 can connect the first support part 202 and the second support part 203 in the vertical direction. The position regulating part 204, which connects the first support part 202 and the second support part 203 in the vertical direction, not only makes it easy to restore the connection when the sensor part 201 and the second support part are replaced, but also makes it easy to obtain initial position information. Furthermore, when a plurality of position regulating parts 204 are provided, the fixing force when connecting the first support part 202 and the second support part 203 can be increased.

[0095] Based on the above-described configuration of the intelligent distribution vehicle, the assembly method of the intelligent distribution vehicle according to an embodiment will be described with reference to Fig. 8 described.

[0096] Fig. 8 is a flowchart showing an example of a method for assembling an intelligent distribution vehicle according to an embodiment of the present disclosure.

[0097] With reference to Fig. 8, the second support part 203, which is required for replacement in the event of a malfunction of the sensor part 201, can first be obtained and stored (S801). Subsequently, a malfunction of the sensor part 201 can be determined (S802). If the sensor part 201 is defective (Yes in S802) while the second support part 203 is fixed to the sensor part 201, the second support part 203 is also replaced along with the replacement of the sensor part 201 (S803). Finally, by replacing the sensor part 201 and the second support part 203, the AMR can be restarted immediately by quickly aligning the initial position of the replacement sensor part 201 using the position adjustment part 204 (S804).

[0098] In summary, according to various embodiments of the present disclosure, as described above, it is possible to shorten the time required for the initial setup of a replacement sensor part based on initial position information when replacing a sensor part. Furthermore, due to the shortened time, a smart distribution vehicle can be started immediately, improving operating times.

[0099] However, the present disclosure as described above may be implemented as computer-readable code on a program-storing medium. The computer-readable medium includes all types of recording devices that store data readable by a computer system. Examples of the computer-readable medium may include a hard disk drive (HDD), a solid-state drive (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical storage device, and the like. Therefore, the above detailed description should not be construed as limiting in any way and should be considered as exemplary.The scope of the present disclosure should be determined by a reasonable interpretation of the appended claims, and all variations and modifications within the range of equivalence of the present disclosure are intended to be included within the scope of the present disclosure. Description of reference symbols 100 Smart Factory 110 Intelligent distribution vehicle 120 production device 130 Monitoring device 140 Control system

Claims

[1] An intelligent distribution vehicle (110) comprising: a first support part (202) which is adapted to support a sensor part (201) for detecting an object, a second support part (203) which is adapted to support the sensor part (201) on an upper side of the first support part (202), and a position regulating part (204) configured to regulate the second support part (203) so as to maintain initial position information of the sensor part (201) while the sensor part (201) is supported on the second support part (203), and, upon replacement of the sensor part (201), to align an initial position of a replacement sensor part (201) based on the initial position information of the sensor part (201). [2] The vehicle (110) of claim 1, wherein the sensor part (201) comprises a 2D LiDAR sensor, a 3D LiDAR sensor, and a 3D camera sensor. [3] The vehicle (110) according to claim 1, wherein the sensor part (201) is supported at a rear side and at a bottom side by the second support part (203). [4] The vehicle (110) according to claim 1, wherein the second support member (203) is provided so as to be detachable from the position regulating member (204). [5] The vehicle (110) according to claim 4, wherein the second support part (203) is replaced when the sensor part (201) is replaced. [6] The vehicle (110) according to claim 1, wherein the position regulating part (204) is provided in a plurality and connects the first support part (202) and the second support part (203) in a vertical direction. [7] The vehicle (110) according to claim 1, wherein the initial position information of the sensor part (201) includes at least one of information about an inclination formed by the second support part (203) and the sensor part (201), and information about a width, a height, and an angle formed by the first support part (201) and the sensor part (201). [8] The vehicle (110) according to claim 1, wherein the position regulating part (204) is arranged to maintain the initial position information of the sensor part (201) based on spatial map information acquired by the sensor part (201). [9] An assembly method for an intelligent distribution vehicle (110), the method comprising: Determining a malfunction of a sensor part (201) based on initial position information of the sensor part (201) in the intelligent distribution vehicle (110), which has the sensor part (201) for detecting an object, a first support part (202) for supporting the sensor part (201), a second support part (203) for supporting the sensor part (201) on an upper side of the first support part (202), and a position regulating part (204) for regulating the second support part (203), Replacing the sensor part (201) and the second support part (203) if the sensor part (201) malfunctions, and Aligning an initial position of a replacement sensor part (201) based on the initial position information of the sensor part (201) when replacing the sensor part (201). [10] The method of claim 9, wherein the sensor part (201) comprises a 2D LiDAR sensor, a 3D LiDAR sensor and a 3D camera sensor. [11] The method according to claim 9, wherein the second support member (203) is provided so as to be detachable from the position regulating member (204). [12] The method according to claim 9, wherein the position regulating member (204) is provided in a plurality and connects the first support member (202) and the second support member (203) in a vertical direction. [13] The method according to claim 9, wherein the initial position information of the sensor part (201) includes at least one of information about an inclination formed by the second support part (203) and the sensor part (201), and information about a width, a height, and an angle formed by the first support part (201) and the sensor part (203). [14] The method according to claim 9, wherein the position regulation part (204) is arranged to maintain the initial position information of the sensor part (201) based on spatial map information acquired by the sensor part (201). [15] A computer-readable recording medium on which a program for executing the assembly method of an intelligent distribution vehicle (110) according to any one of claims 9 to 14 is recorded.

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