A luggage delivery robot, luggage delivery, extraction method, system and medium

Abstract

Embodiments of the present application provide a luggage delivery robot, a luggage delivery and extraction method, a system and a medium, relating to the technical field of computer, the luggage delivery robot comprises an image acquisition device, a processor, a moving component and a luggage storage component; the processor is configured to determine a target position at which a target passenger reserves to extract luggage through a used client, obtain a planned route to the target position, and drive the moving component to move based on the planned route; the image acquisition device is configured to acquire a scene image and send the scene image to the processor; the processor is further configured to send an extraction reminder to the client used by the target passenger after recognizing the target passenger, and send a luggage release instruction to the luggage storage component after recognizing an extraction behavior of the target passenger; and the luggage storage component is configured to release the carried luggage in response to the luggage release instruction. The robot provided by the embodiments of the present application can improve the efficiency of luggage delivery.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and in particular to a baggage delivery robot, baggage delivery and retrieval method, system and medium. Background Technology

[0002] During the baggage claim process, passengers typically need to go to a designated baggage claim area to retrieve their luggage. For example, at an airport, airport staff will place all passengers' luggage on carousels in the baggage claim area. After passengers disembark, they need to walk to the baggage claim area themselves and then find their own luggage from the large number of bags on the carousel.

[0003] In the above scheme, since it usually takes a long time for passengers to find their luggage, when there are a large number of passengers, it may cause congestion in the baggage claim area, thus leading to a higher traffic safety risk. Summary of the Invention

[0004] The purpose of this application is to provide a baggage delivery robot, baggage delivery and retrieval method, system, and medium to improve baggage delivery efficiency, avoid traffic congestion, and reduce traffic safety risks. The specific technical solution is as follows:

[0005] In a first aspect, embodiments of this application provide a baggage delivery robot, the robot including an image acquisition device, a processor, moving parts, and a baggage storage part for placing baggage;

[0006] The processor is configured to determine the target location where the target passenger has booked baggage pickup through the client they are using, obtain a planned route to the target location, and drive the moving parts to move based on the planned route, so that the robot carries the target passenger's baggage at the baggage storage unit.

[0007] The image acquisition device is used to acquire scene images and send the scene images to the processor;

[0008] The processor is further configured to send a baggage retrieval reminder to the client used by the target passenger after recognizing the target passenger based on the scene image, and send a baggage release instruction to the baggage storage component after recognizing the target passenger's baggage retrieval behavior based on the scene image;

[0009] The baggage storage component is used to release the baggage carried in response to the baggage release instruction.

[0010] Secondly, this application also provides a baggage delivery method applied to a robot, the method comprising:

[0011] Determine the target location for the baggage pickup reservation made by the passenger through the app they are using;

[0012] Obtain the planned route to the target location;

[0013] Carrying the luggage of the target passenger, proceed along the planned route;

[0014] After identifying the target passenger, a baggage retrieval reminder is sent to the client used by the target passenger;

[0015] After recognizing the target passenger's baggage retrieval behavior, the baggage is released.

[0016] Thirdly, this application also provides a baggage retrieval method, applied to a client, the method comprising:

[0017] Obtain the target location for the passenger's scheduled baggage pickup;

[0018] Send the target location to the baggage delivery robot;

[0019] Receive baggage retrieval reminders sent by the baggage delivery robot after identifying the target passenger;

[0020] In response to the baggage claim reminder, the target passenger is reminded to claim their baggage.

[0021] Fourthly, embodiments of this application also provide a baggage retrieval system, the system comprising: a client and a baggage delivery robot; wherein,

[0022] The client is used to execute the method described in the third aspect above;

[0023] The baggage delivery robot is used to perform the method described in the second aspect above.

[0024] Fifthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described in the second or third aspect above.

[0025] Beneficial effects of the embodiments in this application:

[0026] The baggage delivery robot provided in this application includes an image acquisition device, a processor, moving parts, and a baggage storage component. The processor can obtain a planned route to the target location reserved by the passenger and drive the moving parts to move according to the planned route. This allows the robot to carry the passenger's baggage at the baggage storage component. After recognizing the target passenger based on the scene image acquired by the image acquisition device, the robot sends a baggage retrieval reminder to the passenger's client. After recognizing the passenger's baggage retrieval behavior based on the scene image, the baggage storage component can respond to the baggage release command and release the baggage. Different passengers can reserve different target locations, which avoids passengers staying in the same area. The processor of the baggage delivery robot can recognize the target passenger based on the scene image, so the passenger does not need to search for their baggage. After the processor recognizes the target passenger, it sends a baggage retrieval reminder to the passenger's client, which helps the passenger retrieve their baggage quickly. Therefore, applying the baggage delivery robot provided in this application can shorten the time for passengers to retrieve their baggage, improve baggage delivery efficiency, avoid congestion, and reduce traffic safety risks. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0028] Figure 1 This is a schematic diagram of the structure of a first type of baggage delivery robot provided in an embodiment of this application;

[0029] Figure 2 This is a schematic diagram of the structure of a second type of baggage delivery robot provided in an embodiment of this application;

[0030] Figure 3 A flowchart illustrating the first baggage delivery method provided in this application embodiment;

[0031] Figure 4 A flowchart illustrating the second baggage delivery method provided in this application embodiment;

[0032] Figure 5 A flowchart illustrating the third baggage delivery method provided in this application embodiment;

[0033] Figure 6 A flowchart illustrating the fourth baggage delivery method provided in this application embodiment;

[0034] Figure 7 A flowchart illustrating a baggage retrieval method provided in this application embodiment;

[0035] Figure 8 This is a schematic diagram of a baggage retrieval system provided in an embodiment of this application. Detailed Implementation

[0036] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0037] To reduce traffic safety risks, this application provides a baggage delivery robot, baggage delivery and retrieval method, system and medium, which will be described in detail below.

[0038] The following is a detailed introduction to the aforementioned baggage delivery robot.

[0039] See Figure 1 , Figure 1 This is a schematic diagram of the structure of a baggage delivery robot provided in an embodiment of this application. In this embodiment, the robot includes an image acquisition device 101, a processor 102, a moving part 103, and a baggage storage part 104 for placing baggage.

[0040] The processor 102 is used to determine the target location where the target passenger has booked baggage retrieval through the client they are using, obtain the planned route to the target location, and drive the motion component 103 to move based on the planned route so that the robot can carry the target passenger's baggage at the baggage storage component 104.

[0041] Image acquisition device 101 is used to acquire scene images and send the scene images to processor 102;

[0042] The processor 102 is also used to send a baggage retrieval reminder to the client used by the target passenger after the target passenger is identified based on the scene image, and to send a baggage release instruction to the baggage storage component 104 after the target passenger's baggage retrieval behavior is identified based on the scene image.

[0043] The baggage storage unit 104 is used to release the baggage carried in response to a baggage release instruction.

[0044] The functions of each component in the baggage delivery robot are explained below.

[0045] Regarding the processor 102, when determining the target location, a communication connection can be established between the processor 102 and the client used by the target passenger. This allows the processor 102 to directly obtain the target location sent by the target passenger through the client. Additionally, both the processor 102 and the client can establish communication connections with the backend management platform. The client can then send the target location it has reserved to the management platform, and the processor 102 can receive the target location forwarded by the management platform. The client can be installed on the target passenger's own user device or on a mobile device provided to the target passenger when checking in their luggage. This mobile device can include communication, voice, and location functions, such as a wristband or watch.

[0046] After determining the target location, the processor 102 can plan a route to the target location based on the robot's current location and the target location. Furthermore, if both the processor 102 and the client have established a communication connection with the management platform, they can also obtain the route planned by the management platform based on the robot's current location and the target location. In this way, the processor 102 can drive the moving part 103 to move along the planned route, thereby enabling the robot to carry the target passenger's luggage from the luggage storage part 104 to the target location.

[0047] For image acquisition device 101, the aforementioned scene image refers to the image of the scene in which the robot is located.

[0048] One or more image acquisition devices 101 can be installed in the robot. In addition, the robot may also include a rotating component on which the image acquisition device 101 can be mounted to expand the area acquired by the image acquisition device 101.

[0049] After obtaining the scene image captured by the image acquisition device 101, the processor 102 can perform object recognition on the scene image. If the target passenger is identified, it means that the target passenger is near the robot. At this time, a baggage retrieval reminder can be sent to the client used by the target passenger. After receiving the baggage retrieval reminder, the client can remind the target passenger to retrieve the baggage by ringing, vibrating, or other means. The processor 102 can also send the baggage delivery robot's number, appearance, and other information to the client. In this way, the baggage delivery robot's number, appearance, and other information can be displayed on the client's screen to help the target passenger find the baggage delivery robot.

[0050] In one embodiment of this application, when performing object recognition on a scene image, human body recognition can be performed on the scene image to identify the pedestrian area where the pedestrian is located in the scene image, and to determine whether the pedestrian corresponding to the pedestrian area is the target passenger.

[0051] Specifically, when determining whether a pedestrian in a pedestrian area is the target passenger, pedestrian features such as body and face characteristics can be extracted. These extracted features are then matched with pre-obtained features of the target passenger. If the pedestrian features match, the pedestrian corresponding to the matching features is the target passenger. This method of identifying pedestrian areas in a scene image and using pedestrian features within those areas to determine the target passenger essentially involves pedestrian re-identification of the scene image to determine whether each object in the scene image is the target passenger.

[0052] In one embodiment of this application, the above-mentioned pedestrian re-identification of scene images can be achieved using a trained pedestrian re-identification model.

[0053] In one embodiment of this application, the robot may also include a speaker, so that when the processor 102 sends a baggage claim reminder to the client used by the target passenger, the processor 102 may send a broadcast command to the speaker, so that the speaker responds to the broadcast command and broadcasts according to the preset broadcast content to remind the target passenger to claim their baggage.

[0054] The data processing equipment can also obtain passenger information of the target passenger and generate broadcast instructions containing specific broadcast content for the target passenger based on the passenger information, so that the loudspeaker can broadcast according to the specific broadcast content.

[0055] The robot may also include a display screen, so that when the processor 102 sends a baggage claim reminder to the target passenger's client, it can display a reminder message on the screen reminding the target passenger to claim their baggage.

[0056] After obtaining the scene image captured by the image acquisition device 101, the processor 102 can also perform baggage retrieval behavior recognition on the scene image. If it is recognized that there is baggage retrieval behavior and the object of the behavior is the target passenger, it can send a baggage release instruction to the baggage storage component 104.

[0057] After identifying the target passenger, the processor 102 can extract baggage behavior recognition from the scene images subsequently acquired by the image acquisition device 101. This way, the processor 102 does not need to extract baggage behavior recognition from each scene image it acquires, thus reducing the workload of the processor 102.

[0058] The baggage storage unit 104 may have a locking function, so that the stored baggage can be locked without receiving a baggage release instruction, so that other passengers may mistakenly take or steal it. After receiving a baggage release instruction, the baggage storage unit 104 may unlock the stored baggage in response to the baggage release instruction, so that the target passenger can retrieve the baggage from the baggage storage unit 104.

[0059] As can be seen from the above, the baggage delivery robot provided in this application embodiment allows different passengers to book different target locations, thus avoiding passengers from staying in the same area. Furthermore, the processor 102 of the baggage delivery robot can identify the target passenger based on scene images, eliminating the need for passengers to search for their luggage themselves. After the processor 102 identifies the target passenger, it sends a baggage retrieval reminder to the client used by the target passenger, which helps the target passenger retrieve their luggage quickly. Therefore, the baggage delivery robot provided in this application embodiment can shorten the time for passengers to retrieve their luggage, improve baggage delivery efficiency, avoid congestion, reduce traffic safety risks, and also reduce the manpower and material costs for traffic management.

[0060] In one embodiment of this application, when the client is a mobile device provided to the passenger, after the target passenger receives the luggage, the luggage delivery robot or the client can send a prompt message to the target passenger's mobile device to remind the target passenger to return the mobile device to the luggage delivery robot.

[0061] When extracting baggage behavior recognition based on scene images, the processor 102 can perform the recognition in the manner mentioned in the following embodiments.

[0062] In one embodiment of this application, the image acquisition device 101 is specifically used to acquire a first scene image and send the first scene image to the processor 102.

[0063] The processor 102 is specifically used to identify baggage retrieval behavior in the first scene image. If baggage retrieval behavior is identified, it determines whether the object in the first scene image that generates baggage retrieval behavior is the target passenger. If it is the target passenger, it sends a baggage release instruction to the baggage storage component 104.

[0064] The first scene image mentioned above can be an image captured by the image acquisition device 101 after the processor 102 identifies the target passenger, or it can be any of the images captured by the image acquisition device 101.

[0065] The processor 102 can utilize existing behavior recognition models and algorithms to perform baggage retrieval behavior recognition on the first scene image. For example, the first scene image can be input into a trained behavior recognition model, which can then determine whether baggage retrieval behavior exists. After recognizing baggage retrieval behavior, the processor can identify the object that generated the behavior and determine whether the object is the target passenger. If so, a baggage release instruction is sent to the baggage storage component 104.

[0066] The specific implementation method for determining whether the object that generates the baggage retrieval behavior is the target passenger can be found in the following embodiments, which will not be described in detail here.

[0067] In one embodiment of this application, if the processor 102 determines that the object of the baggage retrieval behavior is not the target passenger, a warning message may be issued.

[0068] As can be seen from the above, when the processor 102 identifies the act of retrieving luggage based on the first scene image using the luggage delivery robot provided in this application embodiment, it can also determine whether the object in the first scene image that generates the act of retrieving luggage is the target passenger. This can prevent other passengers from mistakenly taking, mistaking, or stealing luggage. Therefore, the luggage delivery robot provided in this application embodiment can improve the safety and reliability of luggage delivery.

[0069] There are several ways to determine whether the person who initiated the baggage claim is the target passenger. The first method will be explained below.

[0070] In one embodiment of this application, the processor 102 is specifically used to obtain image features of the object that generates the baggage retrieval behavior based on a first scene image, and if it is confirmed that the image features match the preset benchmark image features of the target passenger, then the object is determined to be the target passenger.

[0071] Specifically, the baseline image features of the target passenger can be obtained in advance. After the processor 102 obtains the first scene image and extracts the image features of the object that generates the baggage retrieval behavior from the first scene image, it can calculate the similarity between the image features and each baseline image feature. If the similarity is greater than or equal to a preset similarity threshold, the image features can be considered to match the baseline image features of the target passenger, and the object can be determined to be the target passenger. If the similarity is less than the preset similarity threshold, the image features can be considered to not match the baseline image features of the target passenger, and the object can be determined to be not the target passenger.

[0072] In one embodiment of this application, the baseline image features of the target passenger can be obtained through either of the following two implementation methods.

[0073] In the first implementation, the aforementioned baseline image features are: image features of the target passenger extracted based on the baggage check-in image. The baggage check-in image is: an image of the target passenger collected when the target passenger checks in their baggage. Therefore, a baggage check-in image of the target passenger can be collected when the target passenger checks in their baggage, and image features of the target passenger can be extracted based on the baggage check-in image as the baseline image features of the target passenger.

[0074] For example, facial recognition can be performed on the baggage check-in image to obtain the area where the target passenger's face is located in the baggage check-in image, and the features of this area can be extracted to obtain the target passenger's facial features, which can be used as the aforementioned baseline image features.

[0075] In the solution provided by this implementation, the baggage check-in image is an image of the target passenger collected when the target passenger checks in baggage. Based on the baggage check-in image, the image features of the target passenger can be accurately extracted and used as the reference image features of the target passenger. In this way, by using more accurate reference image features, the accuracy of subsequent processing can be improved.

[0076] In the second implementation, the client can obtain a passenger image of the target passenger before or when booking the target location, and send the passenger image to the processor 102. After obtaining the passenger image, the processor 102 can extract the image features of the target passenger from the passenger image as the aforementioned baseline image features. Alternatively, after obtaining the passenger image, the client can also extract the image features of the target passenger from the passenger image and send the extracted image features to the processor 102. Thus, after receiving the image features sent by the client, the processor 102 uses the obtained image features as the aforementioned baseline image features.

[0077] The passenger images mentioned above can be entered by the passenger themselves, or they can be captured by the camera on the user device used by the target passenger through the client.

[0078] As can be seen from the above, the baggage delivery robot provided in this application, by utilizing the image features of the object that performs the baggage retrieval action and the reference features of the target passenger, can accurately determine whether the object performing the baggage retrieval action is the target passenger. When the image features of the object performing the baggage retrieval action match the reference image features, the object can be identified as the target passenger, and the baggage can be released. Therefore, the robot provided in this application can improve the accuracy and reliability of baggage delivery.

[0079] The second method for determining whether the person who initiated the baggage claim is the target passenger is explained below.

[0080] In one embodiment of this application, the processor 102 is specifically used to obtain object information provided by the object, and if it is confirmed that the object information matches the passenger information recorded in the tag of the baggage being carried, then the object is determined to be the target passenger.

[0081] The luggage tags can record information such as the passenger's mode of transportation number, travel time, departure point, destination, passenger seat number, ticket number, and passenger's name and mobile phone number.

[0082] Specifically, the robot may include input devices such as a keyboard and a touchscreen, allowing the processor 102 to obtain information such as the ticket number and passenger name input by the person performing the baggage retrieval action. Additionally, when the robot retrieves baggage, the processor 102 can access the passenger information recorded on the baggage tag. By matching the object information with the passenger information recorded on the baggage tag, a match can be made, identifying the object as the target passenger.

[0083] For example, when acquiring passenger information, the processor 102 can acquire RFID (Radio Frequency Identification) information on the suitcase, and acquire the ID information, communication information, and information on the means of transportation of the passenger to which the suitcase belongs, based on the RFID information. For example, if the target passenger is traveling by airplane, the means of transportation information can be flight information; if the target passenger is traveling by high-speed rail, the means of transportation information can be train schedule information.

[0084] As can be seen from the above, when using the baggage delivery robot provided in this application embodiment, the object information input by the object can accurately represent the identity of the object. By matching the object information with the passenger information recorded in the baggage tag carried by the robot, it is possible to accurately determine whether the object is the target passenger. When the object information matches the passenger information of the target passenger, the object can be identified as the target passenger, and the baggage can be released. Therefore, using the robot provided in this application embodiment can improve the accuracy and reliability of baggage delivery.

[0085] The third method for determining whether the person who initiated the baggage claim is the target passenger is explained below.

[0086] In one embodiment of this application, see [link to embodiment]. Figure 2 The diagram provides a structural schematic of a second type of baggage delivery robot. In this embodiment, the robot also includes a barcode scanner 105, which is used to scan the identification code provided by the object, obtain the object's identity information, and send the identity information to the processor 102.

[0087] The processor 102 is specifically used to determine whether the identity information matches the passenger identity information recorded in the tag of the baggage being carried. If they match, the object is identified as the target passenger.

[0088] The aforementioned identification code can be a QR code, barcode, or other form of barcode. This identification code can be stored in the client device or printed on transportation tickets, such as train tickets, plane tickets, or ship tickets.

[0089] Specifically, after the processor 102 recognizes the baggage retrieval behavior, it can send a QR code reminder to the person who performed the behavior and notify the scanner to start working. After the scanner scans the identification code provided by the person and obtains the person's identity information, the scanner 105 sends the obtained identity information to the processor 102. The processor 102 can obtain the identity information and match it with the passenger information of the target passenger. If the two types of information match, the person is determined to be the target passenger.

[0090] As can be seen from the above, using the baggage delivery robot provided in this application embodiment, the scanner can scan the identification code provided by the object to obtain the object's identity information. The processor 102 can then match this identity information with the target passenger's passenger information to accurately determine whether the object is the target passenger. If the object is determined to be the target passenger, the baggage is released. Therefore, using the robot provided in this application embodiment can improve the accuracy and reliability of baggage delivery.

[0091] The following describes the specific implementation method of the processor 102 in recognizing the target passenger based on the scene image acquired by the image acquisition device 101.

[0092] In one embodiment of this application, the image acquisition device 101 is specifically used to acquire a second scene image and send the second scene image to the processor 102.

[0093] The processor 102 is also used to obtain the preset reference image features of the target passenger and extract the pedestrian features of the pedestrian in the second scene image. If the pedestrian features match the reference image features, the target passenger is identified.

[0094] Specifically, the image acquisition device 101 can acquire images of the second scene in the following two ways.

[0095] In the first case, the image acquisition device 101 can acquire the second scene image after the robot travels to the target position according to the planned route.

[0096] In this case, after obtaining the planned route, the processor 102 controls the moving part 103 to move according to the planned route. After the robot reaches the target position, it can notify the image acquisition device 101 to work. In this way, the image acquisition device 101 can acquire a second scene image at the target position. Then, the processor 102 can identify the target passenger based on the second scene image and release the luggage carried by the identified target passenger, so that the target passenger can pick up the luggage at the target position. This can avoid traffic congestion caused by a large number of passengers staying in the same area.

[0097] In the second case, the image acquisition device 101 can also acquire images of the second scene while the robot is moving along the planned route.

[0098] To retrieve their luggage more quickly, target passengers may travel in the opposite direction of the planned route to find the robot carrying their luggage, or wait for the robot at a point in the middle of the planned route. Therefore, in response to this situation, the image acquisition device 101 can acquire a second scene image during the robot's movement. If the processor 102 identifies the target passenger during the robot's movement, it can send a reminder message to the target passenger's corresponding mobile device on the spot, so that the target passenger can retrieve their luggage on the spot without having to travel to the target location, thus improving the efficiency of the target passenger in retrieving their luggage.

[0099] Specifically, the processor 102 obtains the aforementioned preset reference image features and matches the pedestrian features extracted from the second scene image with the reference image features. The implementation method is described in the foregoing embodiments and will not be repeated here.

[0100] As can be seen from the above, by applying the baggage delivery robot provided in this application embodiment, the processor 102 extracts pedestrian features from the second scene image captured by the image acquisition device 101, obtains the reference image features of the target passenger, and matches the pedestrian features with the reference image features. This allows for accurate identification of the target passenger among all pedestrians within the field of view of the image acquisition device 101, thereby enabling accurate baggage delivery to the identified target passenger. Therefore, applying the baggage delivery robot provided in this application embodiment can improve the accuracy of baggage delivery. Furthermore, the processor 102 can identify the target passenger through feature matching, eliminating the need for the passenger to search for the robot themselves, thus improving the convenience of baggage retrieval for the target passenger.

[0101] In addition to establishing a direct communication connection with the client, the processor 102 can also establish an indirect communication connection with the client through the management platform. Furthermore, the management platform can also manage baggage delivery tasks in a unified manner.

[0102] In one embodiment of this application, the processor 102 is specifically used to control the baggage storage component 104 to retrieve baggage from the baggage claim area, obtain passenger information recorded in the tag of the retrieved baggage, send the correspondence between the obtained passenger information and the robot to the management platform, and obtain the target location for the target passenger to reserve baggage retrieval through the client used by the target passenger, which is forwarded by the management platform according to the correspondence and the passenger information of the target passenger.

[0103] Specifically, the processor 102 can obtain the attribute information of its own robot, such as the robot's name, number, and tag. After obtaining the passenger information recorded in the tag of the retrieved luggage, the processor 102 can generate a correspondence between the passenger information and the attribute information, send this correspondence to the management platform, and enter a standby state to wait for the target location. After receiving the target location, the luggage is then delivered based on the target location.

[0104] The client used by the target passenger can also establish a communication connection with the management platform, so that the client can send the target passenger's reserved location and passenger information to the management platform.

[0105] The management platform can receive the target location and passenger information sent by the client used by the target passenger, and receive the correspondence between the passenger information and robot attribute information sent by the processor 102 of each robot. In this way, the management platform can determine the robot attribute information corresponding to the passenger information of the target passenger from multiple correspondences. Based on the determined attribute information, the robot carrying the target passenger's luggage can be identified, and the target location reserved by the target passenger can be forwarded to that robot.

[0106] As can be seen from the above, by applying the baggage delivery robot provided in this application embodiment, the processor 102 in the robot can send the correspondence between the passenger information of the target passenger to whom the retrieved baggage belongs and the robot to the management platform. The management platform can forward the target location reserved by the target passenger to the processor 102 according to the correspondence. In this way, the processor 102 can accurately obtain the target location reserved by the target passenger, thereby enabling the baggage delivery robot to deliver the baggage to the target passenger at the target location reserved by the target passenger. Therefore, applying the baggage delivery robot provided in this application embodiment can improve the convenience of passengers retrieving their baggage. In addition, after the robot retrieves the baggage and sends the above-mentioned correspondence to the management platform, if it receives the target location of the target passenger's reserved baggage, it can immediately obtain the planned route, drive the moving parts to move, and make the robot move to the target location, thereby responding to the target passenger's need to retrieve their baggage in a timely manner and improving the passenger's user experience.

[0107] In one embodiment of this application, the processor 102 can obtain the target passenger information of the target passenger before driving the motion component 103 to move based on the planned route, and control the baggage storage component 104 to retrieve the baggage from the baggage claim area that matches the passenger information recorded in the tag with the target passenger information.

[0108] Specifically, when using the client, the target passenger can view the available robots and select one, or the management platform can select one from the available robots for baggage delivery. After the target passenger or management platform selects a robot, a communication connection can be established directly or indirectly between the client and the selected robot. In this way, the processor 102 of the selected robot can obtain the target passenger information and control the baggage storage component 104 to retrieve the baggage from the baggage claim area that matches the passenger information recorded on the tag. The processor 102 can also determine the target passenger's reserved destination and obtain the planned route to the destination, thereby driving the motion component 103 to move according to the planned route, so that the robot carries the target passenger's baggage to the target passenger's reserved destination, realizing baggage delivery.

[0109] As can be seen from the above, by applying the baggage delivery robot provided in this application embodiment, the processor 102 can obtain the target passenger's information, and thus accurately control the baggage storage component 104 to retrieve the target passenger's baggage based on the target passenger information. This, in turn, drives the motion component 103 to move according to the planned route, enabling the accurate delivery of the target passenger's baggage to the target location reserved by the target passenger, thereby achieving baggage delivery. Therefore, applying the baggage delivery robot provided in this application embodiment can improve the convenience of passengers retrieving their baggage and increase baggage delivery efficiency.

[0110] In addition, the robot can obtain the target passenger information when determining the target location before retrieving the luggage, which can prevent the robot from being occupied for a long time and thus improve the utilization efficiency of the robot.

[0111] During the process of the robot delivering luggage, the processor 102 can send relevant information about the luggage delivery to the client so that the target passenger can understand the luggage delivery status.

[0112] In one embodiment of this application, the processor 102 is further configured to: obtain the travel time to the target location along the planned route, and send the travel time and / or the planned route to the client used by the target passenger.

[0113] Specifically, after obtaining the planned route, the processor 102 can estimate the travel time based on the route length. For example, it can calculate the time to reach the target location at a preset speed along the planned route. Additionally, it can consider pedestrian traffic and road conditions along the planned route, setting an extra time. Thus, after calculating the ideal travel time based on the planned route length and the preset speed, the calculated time is added to the extra time, resulting in the total travel time. After obtaining the travel time, the processor 102 sends the travel time to the client used by the target passenger, and can also send the planned route to that client.

[0114] As can be seen from the above, when using the baggage delivery robot provided in this application embodiment, the processor 102 in the robot can send the time and / or route planning to the client used by the target passenger, so that the target passenger can know the baggage delivery status of the robot, thereby improving the user experience of the target passenger.

[0115] In one embodiment of this application, when the processor 102 sends the planned route to the client, it can also send the current location of the robot to the client. The client can display the planned route and the current location of the robot, so that the target passenger can know the current location of the luggage in real time.

[0116] Additionally, if the target passenger needs to expedite baggage retrieval, the app can also provide reverse navigation based on the planned route.

[0117] During the process of delivering luggage, if the robot has reached the destination location reserved by the target passenger but the target passenger has not yet arrived, the robot can wait for the target passenger at the destination location. However, this may cause the robot to obstruct traffic at the destination location.

[0118] To address the aforementioned issues, in one embodiment of this application, the processor 102 is further configured to obtain the target time for the target passenger to retrieve their luggage, determine the departure time based on the target time and travel duration, and at the departure time, drive the motion component 103 based on the planned route so that the robot carries the target passenger's luggage along the planned route.

[0119] The target time mentioned above can be determined by the target passenger based on the travel time, or it can be determined based on their own itinerary.

[0120] Specifically, when a passenger reserves a target location for baggage pickup through their client application, they can also reserve a target time for baggage pickup. When the client obtains the target location and sends it to the processor 102, it can also obtain the target time for baggage pickup, either via voice input or manual input, and send that time to the processor 102 as well. After obtaining the target location and time, the processor can obtain the planned route and the travel time along the planned route to the target location. The processor subtracts the travel time from the target time to obtain the time after subtraction, which is used as the robot's departure time.

[0121] In addition, when there is a communication connection between the client and the management platform, the target location and target time can be sent to the management platform. In this way, the management platform can plan the robot's travel route and determine the travel time of the robot to the target location along the planned route. The travel time is subtracted from the target time to obtain the time after the subtraction, which is used as the robot's departure time. Finally, the planned new travel route and departure time are sent to the processor 102. In this way, the processor 102 can control the moving parts to move according to the obtained travel route at the obtained departure time.

[0122] After the processor 102 obtains the target time for the passenger to pick up their luggage, it determines the departure time based on the target time and the travel time mentioned above. At the departure time, it starts to drive the motion component 103 to move according to the planned route. In this way, when the target passenger arrives at the target location at the target time, the robot can arrive at the target location at the same time, thereby avoiding the situation where the robot waits for the target passenger and ensuring smooth traffic.

[0123] Corresponding to the aforementioned baggage delivery robot, this application also provides a baggage delivery method.

[0124] In one embodiment of this application, see [link to embodiment]. Figure 3 The document provides a flowchart of the first baggage delivery method, which is applied to a robot. The method includes the following steps S301-S305.

[0125] Step S301: Determine the target location for baggage retrieval by the target passenger through the client application they are using;

[0126] Step S302: Obtain the planned route to the target location;

[0127] Step S303: Carry the target passenger's luggage and proceed along the planned route;

[0128] Step S304: After identifying the target passenger, send a baggage claim reminder to the client used by the target passenger;

[0129] Step S305: After recognizing the target passenger's baggage retrieval behavior, release the baggage.

[0130] In this solution, different passengers can book different target locations, which can prevent passengers from staying in the same area. The baggage delivery robot can identify the target passenger on its own, so the passenger does not need to look for the baggage. After the baggage delivery robot identifies the target passenger, it sends a baggage retrieval reminder to the client used by the target passenger, which can help the target passenger retrieve the baggage quickly. Therefore, the baggage delivery solution provided in this application embodiment can shorten the time for passengers to retrieve their baggage, improve baggage delivery efficiency, avoid congestion, and reduce traffic safety risks.

[0131] In one embodiment of this application, see [link to embodiment]. Figure 4 The document provides a flowchart of a second baggage delivery method. In this embodiment, step S305 can be implemented through the following steps S305A-S305D.

[0132] Step S305A: Acquire the first scene image;

[0133] Step S305B: Extract baggage behavior recognition from the first scene image;

[0134] Step S305C: If baggage retrieval behavior is detected, determine whether the object in the first scene image that generates baggage retrieval behavior is the target passenger. If yes, proceed to step S305D.

[0135] Step S305D: Release the baggage being carried.

[0136] In this solution, after recognizing the act of retrieving luggage based on the first scene image, it can be determined whether the object in the first scene image that performs the act of retrieving luggage is the target passenger. This can prevent other passengers from mistakenly taking, mistaking, or stealing luggage. Therefore, applying the luggage delivery solution provided in this application embodiment can improve the safety and reliability of luggage delivery.

[0137] In one embodiment of this application, when determining whether the object that generates the baggage retrieval behavior in the first scene image is the target passenger, the image features of the object that generates the baggage retrieval behavior can be obtained based on the first scene image. If it is confirmed that the image features match the preset reference image features of the target passenger, then the object is determined to be the target passenger.

[0138] In this solution, by utilizing the image features of the object that initiates the baggage retrieval action and the baseline features of the target passenger, it is possible to accurately determine whether the object initiating the baggage retrieval action is the target passenger. When the image features of the object initiating the baggage retrieval action match the baseline image features, the object can be identified as the target passenger, and the baggage can be released. Therefore, applying the solution provided in this application embodiment can improve the accuracy and reliability of baggage delivery.

[0139] In one embodiment of this application, when determining whether the object that generates the baggage retrieval behavior in the first scene image is the target passenger, object information provided by the object can also be obtained. If it is confirmed that the object information matches the passenger information recorded in the tag of the baggage being carried, then the object is determined to be the target passenger.

[0140] As can be seen from the above, the baggage delivery method provided in this application allows the input object information to accurately represent the object's identity. By matching the object information with the passenger information recorded in the baggage tag carried by the robot, it is possible to accurately determine whether the object is the target passenger. When the object information matches the target passenger's passenger information, the object can be identified as the target passenger, and the baggage can be released. Therefore, the solution provided in this application can improve the accuracy and reliability of baggage delivery.

[0141] In one embodiment of this application, when determining whether the object that generates the baggage retrieval behavior in the first scene image is the target passenger, the identification code provided by the object can also be scanned to obtain the object's identity information. If the identity information is determined to match the passenger identity information recorded in the tag of the baggage being carried, then the object is determined to be the target passenger.

[0142] As can be seen from the above, the baggage delivery method provided in this application can scan the identification code provided by the recipient to obtain the recipient's identity information. This identity information can then be matched with the target passenger's passenger information to accurately determine whether the recipient is the target passenger. If the recipient is determined to be the target passenger, the baggage can be released. Therefore, the solution provided in this application can improve the accuracy and reliability of baggage delivery.

[0143] In one embodiment of this application, the reference image features are: image features of the target passenger extracted based on the baggage check-in image, wherein the baggage check-in image is: an image of the target passenger collected when the target passenger checks in baggage.

[0144] In this scheme, the baggage check-in image is an image of the target passenger collected when the target passenger checks in their baggage. Based on the baggage check-in image, the image features of the target passenger can be accurately extracted and used as the baseline image features of the target passenger. By using more accurate baseline image features, the accuracy of subsequent processing can be improved.

[0145] In one embodiment of this application, see [link to embodiment]. Figure 5 The present invention provides a flowchart of a third baggage delivery method. In this embodiment, the above method includes the following steps S306, and the above steps S304 can be implemented by the following steps S304A-S304C.

[0146] Step S306: Obtain the preset baseline image features of the target passenger;

[0147] When identifying a target passenger, the following steps S304A-S304C can be used.

[0148] Step S304A: Acquire the second scene image;

[0149] Step S304B: Extract pedestrian features from the second scene image;

[0150] Step S304C: If the pedestrian features match the reference image features, the target passenger is identified, and a baggage retrieval reminder is sent to the client used by the target passenger.

[0151] As can be seen from the above, by applying the baggage delivery method provided in this application embodiment, pedestrian features are extracted from the collected second scene image to obtain the reference image features of the target passenger. Matching the pedestrian features and the reference image features allows for accurate identification of the target passenger among all pedestrians within the collected field of view, thus enabling accurate baggage delivery to the identified target passenger. Therefore, applying the baggage delivery scheme provided in this application embodiment can improve the accuracy of baggage delivery. Furthermore, since the target passenger can be identified through feature matching, passengers do not need to search for the robot themselves, thereby improving the convenience of baggage retrieval for the target passenger.

[0152] In one embodiment of this application, when acquiring the second scene image, the second scene image can be acquired while traveling along a planned route.

[0153] In this solution, in order to retrieve their luggage more quickly, the target passenger may travel in the opposite direction of the planned route to find the robot carrying their luggage, or wait for the robot at a point in the middle of the planned route. Therefore, to address this situation, a second scene image can be captured during the robot's movement. If the target passenger is identified during the robot's movement, a reminder message can be sent to the client used by the target passenger on the spot, so that the target passenger can retrieve their luggage on the spot without having to travel to the target location, thus improving the efficiency of the target passenger in retrieving their luggage.

[0154] In one embodiment of this application, when acquiring the second scene image, the second scene image can also be acquired after traveling to the target location according to the planned route.

[0155] In this solution, after obtaining the planned route and proceeding to the target location according to the planned route, a second scene image of the target location can be collected. Based on the second scene image, the target passenger can be identified, and the luggage carried by the identified target passenger can be released, so that the target passenger can retrieve the luggage at the target location. This can avoid traffic congestion caused by a large number of passengers staying in the same area.

[0156] In one embodiment of this application, see [link to embodiment]. Figure 6 The present invention provides a flowchart of a fourth baggage delivery method. In this embodiment, the above method further includes the following steps S307-S309, and the above step S301 can be implemented by the following step S301A.

[0157] Step S307: Collect your luggage at the baggage claim area;

[0158] Step S308: Obtain passenger information recorded in the tag of the retrieved baggage;

[0159] Step S309: Send the correspondence between the obtained passenger information and the robot to the management platform;

[0160] After obtaining the above correspondence, step S301 can be achieved through the following step S301A.

[0161] Step S301A: Obtain the target location for baggage retrieval, which is forwarded by the management platform based on the corresponding relationship and the target passenger's passenger information, and which the target passenger has booked through the client they are using.

[0162] As can be seen from the above, by applying the baggage delivery method provided in this application embodiment, the robot can send the correspondence between the passenger information of the target passenger to which the retrieved baggage belongs and the robot to the management platform. The management platform can forward the target location reserved by the target passenger to the robot according to the correspondence. In this way, the robot can accurately obtain the target location reserved by the target passenger, and thus realize that the baggage delivery robot delivers the baggage carried by the target passenger to the target passenger at the target location reserved by the target passenger. Therefore, by applying the baggage delivery robot provided in this application embodiment, the convenience of passengers retrieving their baggage can be improved.

[0163] In one embodiment of this application, before the robot travels along the planned route, target passenger information of the target passenger can be obtained; baggage matching the passenger information recorded in the tag can be retrieved from the baggage claim area.

[0164] As can be seen from the above, the baggage delivery method provided in this application embodiment can obtain the target passenger's information, thereby accurately retrieving the target passenger's baggage from the baggage claim area based on the target passenger information. Then, based on the planned route, the baggage can be accurately transported to the target location reserved by the target passenger, thus realizing baggage delivery. Therefore, the baggage delivery robot provided in this application embodiment can improve the convenience of baggage retrieval for passengers and increase baggage delivery efficiency.

[0165] In addition, the robot can obtain the target passenger information when determining the target location, and then retrieve the luggage. Compared with the robot retrieving the luggage first and then waiting to obtain the target location and target passenger information, this can prevent the robot from being occupied for a long time, thereby improving the utilization efficiency of the robot.

[0166] In one embodiment of this application, during baggage delivery, the travel time to the target location along the planned route can be obtained, and the travel time and / or the planned route can be sent to the client used by the target passenger.

[0167] As can be seen from the above, by applying the baggage delivery method provided in the embodiments of this application, the robot can send the time and / or route planning information to the client used by the target passenger, so that the target passenger can know the status of the robot's baggage delivery, thereby improving the user experience of the target passenger.

[0168] In one embodiment of this application, during the baggage delivery process, the target time for the target passenger to pick up the baggage can also be obtained. In this way, after obtaining the travel time to the target location along the planned route, the departure time can be determined according to the target time and travel time, and the baggage of the target passenger can be carried along the planned route at the departure time.

[0169] In this solution, after obtaining the target passenger's scheduled baggage pickup time, the departure time is determined based on the target time and the aforementioned travel time. The robot then begins moving along the planned route at the departure time. This ensures that when the target passenger arrives at the target location at the target time, the robot will arrive at the target location at that exact time, thus avoiding situations where the robot waits for the target passenger and ensuring smooth traffic flow.

[0170] Corresponding to the above-mentioned baggage delivery method applied to robots, this application also provides a baggage retrieval method applied to clients.

[0171] In one embodiment of this application, see [link to embodiment]. Figure 7 The document provides a flowchart of the first baggage retrieval method. In this embodiment, the above method is applied to the client and includes the following steps S701-S704.

[0172] Step S701: Obtain the target location for the target passenger's scheduled baggage pickup.

[0173] Specifically, the aforementioned client can display a scene map, allowing the target passenger to select a location on the scene map to reserve their luggage based on their travel itinerary. The client can then obtain the target location selected by the target passenger.

[0174] In addition, the target passenger can also use their current location as the target location. In this case, the client can locate the target passenger's current location and use that location as the target location.

[0175] Step S702: Send the target location to the baggage delivery robot.

[0176] Specifically, the aforementioned client can establish a communication connection with the baggage delivery robot, allowing the client to directly send the target location to the baggage delivery robot.

[0177] In addition, both the aforementioned client and the baggage delivery robot can establish communication connections with the management platform. This allows the client to send the target location to the management platform, which then forwards it to the baggage delivery robot.

[0178] Step S703: Receive a baggage retrieval reminder sent by the baggage delivery robot after identifying the target passenger.

[0179] Specifically, once the baggage delivery robot identifies the target passenger, it means that the robot has arrived near the passenger with the baggage. At this point, the robot can send baggage retrieval information to the client app used by the target passenger, who can then receive a baggage retrieval reminder from the robot.

[0180] Step S704: In response to the baggage claim reminder, remind the target passenger to collect their baggage.

[0181] Specifically, in response to baggage claim reminders, the aforementioned client can display baggage claim reminder information and alert the target passenger to check the client via vibration, message ringtone, etc., so that the target passenger can know that the baggage delivery robot has arrived nearby and thus retrieve their baggage.

[0182] As can be seen from the above, when using the solution provided in this application embodiment for baggage retrieval, the client can send the target passenger's reserved target location to the baggage delivery robot and receive a baggage retrieval reminder from the baggage delivery robot. In response to the baggage retrieval reminder, the client reminds the target passenger to retrieve their baggage. Therefore, the baggage retrieval solution provided in this application embodiment can ensure that the target passenger retrieves their baggage, thereby guaranteeing the reliability of baggage retrieval.

[0183] Corresponding to the above-mentioned baggage delivery and baggage retrieval methods, this application also provides a baggage retrieval system.

[0184] In one embodiment of this application, see [link to embodiment]. Figure 8 The present invention provides a schematic diagram of the structure of a first baggage retrieval system. In this embodiment, the system includes a client 801 and a baggage delivery robot 802.

[0185] Client 801 is used to implement the steps described in the above-described baggage retrieval method embodiment;

[0186] The baggage delivery robot 802 is used to implement the steps described in the above-described baggage delivery method embodiment.

[0187] As can be seen from the above, by applying the solution provided in the embodiments of this application for baggage retrieval, the baggage delivery robot can deliver the baggage of the target passenger to the target location reserved by the target passenger. Different passengers can reserve different locations, which can avoid a large number of passengers gathering in the same area, thereby avoiding congestion, reducing traffic safety risks, and also improving the efficiency of baggage retrieval for the target passenger.

[0188] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the above-described baggage delivery or baggage retrieval methods.

[0189] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to perform any of the baggage delivery or baggage retrieval methods described above.

[0190] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or other media (e.g., solid state disk (SSD)).

[0191] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0192] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the descriptions of the method, system, computer-readable storage medium, and computer program product embodiments are relatively simple because they are substantially similar to the device embodiments describing the baggage delivery robot; relevant parts can be referred to in the descriptions of the baggage delivery robot embodiments.

[0193] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A baggage delivery robot, characterized in that, The robot includes an image acquisition device, a processor, moving parts, and a luggage storage component for placing luggage. The processor is configured to determine the target location where the target passenger has booked baggage pickup through the client they are using, obtain a planned route to the target location, and drive the moving parts to move based on the planned route, so that the robot carries the target passenger's baggage at the baggage storage unit. The image acquisition device is used to acquire scene images and send the scene images to the processor; The processor is further configured to perform pedestrian re-identification on the scene image to identify the target passenger; after identifying the target passenger, send a baggage retrieval reminder to the client used by the target passenger, and perform baggage retrieval behavior recognition on the scene image captured by the image acquisition device after identifying the target passenger; after identifying the target passenger's baggage retrieval behavior, send a baggage release instruction to the baggage storage component. The baggage storage component is used to release the baggage carried in response to the baggage release instruction.

2. The robot according to claim 1, characterized in that, The image acquisition device is specifically used to acquire a first scene image and send the first scene image to the processor. The processor is specifically used to identify baggage retrieval behavior in the first scene image. If baggage retrieval behavior is identified, it determines whether the object in the first scene image that generates baggage retrieval behavior is the target passenger. If it is the target passenger, it sends a baggage release instruction to the baggage storage component.

3. The robot according to claim 2, characterized in that, The processor is specifically configured to obtain image features of the object that generates the baggage retrieval behavior based on the first scene image; if the image features match the preset benchmark image features of the target passenger, then the object is determined to be the target passenger; or The processor is specifically used to obtain object information provided by the object, and if it is confirmed that the object information matches the passenger information recorded in the tag of the luggage being carried, then the object is determined to be the target passenger. or The robot also includes: a barcode scanner, used to scan the identification code provided by the object, obtain the object's identity information, and send the identity information to the processor; The processor is specifically used to determine whether the identity information matches the passenger identity information recorded in the tag of the carried luggage. If they match, the object is determined to be the target passenger.

4. The robot according to claim 3, characterized in that, The reference image features are: image features of the target passenger extracted based on the baggage check-in image, wherein the baggage check-in image is: an image of the target passenger collected when the target passenger checks in baggage.

5. The robot according to claim 1, characterized in that, The image acquisition device is specifically used to acquire a second scene image and send the second scene image to the processor; The processor is further configured to obtain preset reference image features of the target passenger and extract pedestrian features of pedestrians in the second scene image. If the pedestrian features match the reference image features, the target passenger is identified.

6. The robot according to claim 5, characterized in that, The image acquisition device is specifically used for: The robot acquires a second scene image while traveling along the planned route; or After the robot travels along the planned route to the target location, it acquires a second scene image.

7. The robot according to claim 1, characterized in that, The processor is specifically used to control the baggage storage component to retrieve baggage from the baggage claim area, obtain passenger information recorded in the tag of the retrieved baggage, send the correspondence between the obtained passenger information and the robot to the management platform, and obtain the target location for baggage retrieval that the target passenger has booked through the client they are using, forwarded by the management platform based on the correspondence and the target passenger's passenger information.

8. The robot according to claim 1, characterized in that, The processor is further configured to obtain target passenger information of the target passenger before driving the moving component to move based on the planned route, and control the baggage storage component to retrieve baggage from the baggage claim area that matches the passenger information recorded in the tag with the target passenger information.

9. The robot according to any one of claims 1-8, characterized in that, The processor is also used for: The system obtains the travel time along the planned route to the target location and sends the travel time to the client used by the target passenger. or The planned route is sent to the client.

10. The robot according to claim 9, characterized in that, The processor is further configured to obtain the target time for the target passenger to pick up their luggage, determine the departure time based on the target time and the travel time, and drive the motion component based on the planned route at the departure time, so that the robot carries the target passenger's luggage along the planned route.

11. A method for baggage delivery, characterized in that, Applied to robots, the method includes: Determine the target location for the baggage pickup reservation made by the passenger through the app they are using; Obtain the planned route to the target location; Carrying the luggage of the target passenger, proceed along the planned route; Perform pedestrian re-identification on the scene image to identify the target passenger; after identifying the target passenger, send a baggage retrieval reminder to the client used by the target passenger; The system performs baggage retrieval behavior recognition on scene images captured by the image acquisition device after identifying the target passenger; and releases the baggage after recognizing the target passenger's baggage retrieval behavior.

12. The method according to claim 11, characterized in that, The step of releasing the baggage after recognizing the target passenger's baggage retrieval behavior includes: Acquire images of the first scene; Extract luggage behavior recognition from the first scene image; If baggage retrieval behavior is detected, determine whether the object in the first scene image that performs the baggage retrieval behavior is the target passenger; If the passenger is the target passenger, their luggage will be released.

13. The method according to claim 12, characterized in that, Determining whether the object in the first scene image that performs the baggage retrieval action is the target passenger includes: Based on the first scene image, image features of the object that generates the baggage retrieval behavior are obtained. If it is confirmed that the image features match the preset benchmark image features of the target passenger, then the object is determined to be the target passenger. or If the object information provided by the object is obtained, and it is confirmed that the object information matches the passenger information recorded in the tag of the luggage being carried, then the object is determined to be the target passenger. or Scan the identification code provided by the object to obtain the object's identity information. If the identity information matches the passenger identity information recorded in the tag of the luggage being carried, then the object is identified as the target passenger.

14. The method according to claim 13, characterized in that, The reference image features are: image features of the target passenger extracted based on the baggage check-in image, wherein the baggage check-in image is: an image of the target passenger collected when the target passenger checks in baggage.

15. The method according to claim 11, characterized in that, The method further includes: Obtain the preset baseline image features of the target passenger; The target passenger is identified using the following methods: Acquire images of the second scene; Extract pedestrian features from the second scene image; If the pedestrian features match the reference image features, then the target passenger is identified.

16. The method according to claim 15, characterized in that, The acquisition of the second scene image includes: Acquire second scene images while proceeding along the planned route; or After proceeding to the target location according to the planned route, a second scene image is acquired.

17. The method according to claim 11, characterized in that, The method further includes: Collect your luggage at the baggage claim area; Obtain passenger information recorded in the tags of the retrieved luggage; Send the obtained passenger information and the correspondence between them and the robot to the management platform; Determining the target location for baggage pickup booked by the target passenger through the client application they used includes: The management platform obtains the target location for baggage retrieval, which is forwarded by the target passenger through the client they are using, based on the corresponding relationship and the passenger information of the target passenger.

18. The method according to claim 11, characterized in that, Before the luggage carrying the target passenger travels along the planned route, the following is also included: Obtain the target passenger information of the target passenger; Retrieve baggage from the baggage claim area where the passenger information recorded on the tag matches the target passenger information.

19. The method according to any one of claims 11-18, characterized in that, The method further includes: The system obtains the travel time along the planned route to the target location and sends the travel time to the client used by the target passenger. or The planned route is sent to the client.

20. The method according to claim 19, characterized in that, The method further includes: Obtain the target time for the target passenger to pick up their luggage; The baggage carrying the target passenger travels along the planned route, including: The departure time is determined based on the target time and the travel duration. At the departure time, the passenger will carry the luggage of the target passenger and proceed along the planned route.

21. A method for retrieving baggage, characterized in that, Applied to a client, the method includes: Obtain the target location for the passenger's scheduled baggage pickup; Send the target location to the baggage delivery robot; The system receives a baggage retrieval alert sent by the baggage delivery robot after it identifies the target passenger and the target passenger's baggage retrieval behavior. The baggage delivery robot identifies the target passenger by performing pedestrian re-identification on the scene image. In response to the baggage claim reminder, the target passenger is reminded to claim their baggage.

22. A baggage claim system, characterized in that, The system includes: a client application and a baggage delivery robot; wherein... The client is used to perform the method of claim 21; The baggage delivery robot is used to perform the method of any one of claims 11-20.

23. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 11-20 or 21.

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