An intelligent shooting system, method, electronic device, medium and product
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SPREADTRUM COMMUNICATION (SHANGHAI) CO LTD
- Filing Date
- 2026-02-03
- Publication Date
- 2026-06-12
Smart Images
Figure CN122195087A_ABST
Abstract
Description
Technical Field
[0001] This disclosure generally relates to the field of intelligent robot technology, and more particularly to an intelligent shooting system, method, electronic device, medium, and product. Background Technology
[0002] A camera robot can ensure that the camera equipment can accurately track the target and quickly adjust to the appropriate shooting position to obtain the desired footage.
[0003] In existing technologies, photography robots are typically equipped with photographic equipment and movable structures, enabling autonomous movement to track shooting targets. However, their ability to adjust shooting posture and height is limited. Because existing photography robots lack the ability to perceive the overall environment of the shooting location and cannot acquire site map information, they can only rely on sensors to detect the surrounding local environment. This makes it difficult to accurately determine the relative position of the shooting target to their own shooting range. When the shooting target exceeds the current shooting range, the robot must blindly move and probe to find a suitable shooting position. This not only results in delayed response and low shooting efficiency but also easily leads to unreasonable movement paths due to incomplete understanding of the site environment. Furthermore, they can only adjust the shooting angle by moving, failing to flexibly adapt to preset shooting conditions in different scenarios, thus affecting the quality of the captured images and scene adaptability. Summary of the Invention
[0004] This disclosure addresses some of the shortcomings mentioned in the background art by providing an intelligent shooting system, method, electronic device, medium, and product.
[0005] In a first aspect, embodiments of this disclosure provide an intelligent shooting system, including: a shooting robot and a control module; the shooting robot includes a photography device, a robotic arm connected to the photography device, a lifting platform connected to the robotic arm, and a movable device connected to the lifting platform;
[0006] The photographic device is used to acquire a site map of the target shooting location and transmit the site map to the control module. The control module is used to control the robotic arm to adjust the photographic device to a shooting position that meets preset shooting conditions when the shooting target is determined to be within the shooting range based on the site map; when the shooting target is determined to be outside the shooting range based on the site map, the control module generates a movement path based on the site map and controls the movable device to move and / or the lifting platform to move to the shooting range, and then executes the step of controlling the robotic arm to adjust the photographic device to a shooting position that meets preset shooting conditions.
[0007] In one embodiment of the first aspect, the photographic device includes a camera and a lidar; The camera is used to capture images of the target to obtain target images; the lidar is used in conjunction with the camera to scan the target shooting area to generate the site map.
[0008] In one embodiment of the first aspect, the control module is further configured to: Determine the path prediction model; Obtain obstacle information of the target shooting site obtained by the LiDAR scan; If, based on the site map, it is determined that the target is not within the shooting range, the obstacle information and the site map are input into the path prediction model to obtain the movement path.
[0009] In one embodiment of the first aspect, the control module is further configured to: When the target is in motion, the camera captures the movement path of the target. The motion path is analyzed to obtain the predicted path of the target at the next moment; The future movement path of the shooting robot is obtained by processing the motion path and the predicted path.
[0010] In one embodiment of the first aspect, the control module is further configured to: When the shooting robot moves according to the movement path, the motion state of the shooting robot is determined; wherein, the motion state is used to indicate whether the movement of the shooting robot is smooth; If the motion of the shooting robot is determined to be unstable based on the motion state, the direction of acceleration of the shooting robot is determined. The direction opposite to the acceleration direction is defined as the target acceleration direction. The camera robot is adjusted based on the target acceleration direction.
[0011] In one embodiment of the first aspect, the control module is further configured to: Determine an image processing model; wherein the image processing model is used to optimize the layout of the image; After controlling the robotic arm to adjust the photography device to a shooting position that meets the preset shooting conditions, the initial image of the target is captured. The initial captured image is input into the image processing model to obtain composition optimization parameters; Based on the composition optimization parameters, the shooting robot is controlled to adjust the position of the photography equipment.
[0012] In a second aspect, embodiments of this disclosure provide an intelligent shooting method, comprising: Obtain a site map of the target shooting location, and determine whether the shooting target is within the shooting range based on the site map; If the target is determined to be within the shooting range based on the site map, the robotic arm is controlled to adjust the camera to a shooting position that meets the preset shooting conditions. If it is determined from the site map that the target is not within the shooting range, a movement path is generated based on the site map; The steps include controlling the movable device to move and / or the lifting platform to move within the shooting range, and controlling the robotic arm to adjust the photography equipment to a shooting position that meets the preset shooting conditions.
[0013] In a third aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of an intelligent shooting method.
[0014] In a fourth aspect, a computer-readable storage medium is provided having a computer program / instructions stored thereon, which, when executed by a processor, implement the steps of an intelligent shooting method.
[0015] In a fifth aspect, a computer program product is provided, including a computer program / instructions that, when executed by a processor, implement the steps of an intelligent shooting method.
[0016] As will be described in detail below, an intelligent shooting system, method, electronic device, medium, and product according to embodiments of this disclosure are disclosed. By acquiring a site map through a photographic device, the lack of global environmental perception in existing shooting robots is overcome, enabling the control module to accurately determine the relative position of the shooting target and the shooting range, avoiding blind movement and trial and error, and significantly improving response speed and shooting efficiency. Simultaneously, through the coordinated operation of mobile devices, a lifting platform, and a robotic arm, the range of adjustable shooting posture and height is expanded, and targeted adjustments allow the photographic device to flexibly adapt to preset shooting conditions in different scenarios. This solves the problems of limited shooting angle adjustment and poor scene adaptability in existing technologies, effectively ensuring the quality of the captured images and making the shooting process more flexible and practical. Attached Figure Description
[0017] Figure 1 A structural diagram of the intelligent robot provided in the embodiments of this disclosure; Figure 2 A flowchart illustrating an intelligent shooting method provided in this embodiment of the disclosure; Figure 3A flowchart illustrating the processing of various motion states in an intelligent shooting method provided in this embodiment of the present disclosure; Figure 4 A flowchart of motion planning for an intelligent shooting system provided in this embodiment of the disclosure; Figure 5 This is a schematic diagram of an electronic device provided in an embodiment of the present disclosure. Detailed Implementation
[0018] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present disclosure and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present disclosure are shown in the drawings, not the entire structure.
[0019] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.
[0020] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.
[0021] Research has shown that filming robots can ensure that filming equipment can accurately track the target and quickly adjust to the appropriate shooting position to obtain the desired footage.
[0022] In existing technologies, photography robots are typically equipped with photographic equipment and movable mechanisms, enabling autonomous movement to track shooting targets. However, their ability to adjust shooting posture and height is limited. Because existing photography robots lack the ability to perceive the overall environment of the shooting location and cannot acquire site map information, they can only rely on sensors to detect the surrounding local environment. This makes it difficult to accurately determine the relative position of the shooting target to their own shooting range. When the shooting target exceeds the current shooting range, the robot must blindly move and probe to find a suitable shooting position. This not only results in delayed response and low shooting efficiency but also easily leads to unreasonable movement paths due to incomplete understanding of the site environment. Furthermore, they can only adjust the shooting angle by moving, failing to flexibly adapt to preset shooting conditions in different scenarios, thus affecting the quality of the captured images and scene adaptability.
[0023] Based on the above research, this disclosure provides an intelligent shooting system, including a shooting robot and a control module. The shooting robot integrates a photography device, a robotic arm, a lifting platform, and a movable device. The photography device can acquire a site map of the target shooting location and transmit it to the control module. The control module determines whether the shooting target is within the shooting range based on the site map. If it is, it controls the robotic arm to adjust the photography device to a preset shooting position. If it is not, it generates a movement path, controls the movable device and / or the lifting platform to move to the shooting range, and then adjusts the position of the photography device through the robotic arm.
[0024] By acquiring a site map through photographic equipment, the lack of global environmental awareness in existing shooting robots is compensated for. This allows the control module to accurately determine the relative position of the shooting target and the shooting range, avoiding blind movement and probing, and significantly improving response speed and shooting efficiency. At the same time, with the coordinated operation of mobile devices, lifting platforms, and robotic arms, the range of shooting posture and height adjustment is expanded, and the photographic equipment can be flexibly adapted to preset shooting conditions in different scenarios through targeted adjustments. This solves the problems of limited shooting angle adjustment and poor scene adaptability in existing technologies, effectively ensuring the quality of the shooting images and making the shooting process more flexible and practical.
[0025] To facilitate understanding of this embodiment, a detailed description of the intelligent shooting system disclosed in this disclosure will be provided first, see [link to relevant documentation]. Figure 1 The diagram shown is a structural diagram of an intelligent robot provided in an embodiment of this disclosure. The system includes: The camera robot 1 and the control module 2 are included. The camera robot includes a camera device 11, a robotic arm 12 connected to the camera device 11, a lifting platform 13 connected to the robotic arm, and a movable device 14 connected to the lifting platform.
[0026] In embodiments of this disclosure, the movable device 14 is used to support the upper structure of the shooting robot (i.e., the lifting platform, the robotic arm, and the photography equipment) to complete the ground movements of the shooting robot.
[0027] Lifting platform 13 is a folding lifting platform, used for lifting such as Figure 1 The robotic arm shown above the lifting platform controls the raising and lowering of the filming robot.
[0028] The robotic arm 12 is a folding robotic arm used to control the camera equipment to perform shooting actions such as movement and rotation, and can also fine-tune, control and move the camera equipment within a small range.
[0029] The camera equipment is used to acquire a site map of the target shooting location and transmit the site map to the control module.
[0030] In the embodiments of this disclosure, the framing range of the target shooting location can be determined, and a site map of the target shooting location can be generated based on the framing range.
[0031] After the site map is determined, it can be sent to the control module, so that the control module can determine the location of the shooting robot in the target shooting site based on the site map.
[0032] The control module is used to control the robotic arm to adjust the photography equipment to a shooting position that meets the preset shooting conditions, based on the determination that the shooting target is within the shooting range according to the site map.
[0033] In the embodiments of this disclosure, "the target being photographed is within the shooting range" can be understood as the shooting robot only needing to move the robotic arm mounted on it when photographing the target.
[0034] Here, the control module can collect data on the weight of the camera device and the horizontal and vertical movement range of the robotic arm.
[0035] While the target is within the shooting range, the control module must ensure that the center area of the moving camera device is no larger than the base area of the shooting robot to prevent the shooting robot from tipping over.
[0036] If the target is determined to be outside the shooting range based on the site map, a movement path is generated based on the site map, and the movable equipment and / or the lifting platform are moved into the shooting range. Then, the robotic arm is controlled to adjust the camera equipment to a shooting position that meets the preset shooting conditions.
[0037] In embodiments of this disclosure, if it is determined from the site map that the target is not within the shooting range, the control module can control the shooting robot to move to the shooting range of the target.
[0038] The shooting range includes both the vertical and horizontal dimensions. The movement path includes the horizontal and vertical movement paths of the shooting robot.
[0039] Here, when the control module determines, based on the site map, that the shooting robot is neither in the horizontal nor vertical range of the target shooting site, it can first control the movable device of the shooting robot to move to the horizontal range of the target shooting site based on the horizontal movement path in the movement path, and then control the lifting platform of the shooting robot to move to the vertical range of the target shooting site based on the vertical movement path in the movement path.
[0040] Here, if the control module determines that the shooting robot is not within the horizontal range of the target shooting site based on the site map, it can control the movable device of the shooting robot to move to the horizontal range of the target shooting site based on the horizontal movement path in the movement path.
[0041] Here, if the control module determines that the shooting robot is not within the vertical range of the target shooting site based on the site map, it can control the lifting platform of the shooting robot to move to the vertical range of the target shooting site based on the vertical movement path in the movement path.
[0042] After the shooting robot is moved into the shooting range, the camera equipment can be fine-tuned by controlling the machinery to make it meet the preset shooting conditions.
[0043] The preset shooting conditions include, but are not limited to: the subject being in the golden position of the camera's composition, and the subject being in an environment with a sense of depth.
[0044] In the embodiments disclosed herein, a site map is acquired through a photographic device, which compensates for the lack of global environmental awareness in existing shooting robots. This enables the control module to accurately determine the relative position of the shooting target and the shooting range, avoiding blind movement and probing, and significantly improving response speed and shooting efficiency. At the same time, with the coordinated cooperation of mobile devices, lifting platforms, and robotic arms, the range of adjustment for shooting posture and height is expanded, and the photographic device can be flexibly adapted to preset shooting conditions in different scenarios through targeted adjustments. This solves the problems of single shooting angle adjustment and poor scene adaptability in the prior art, effectively ensuring the quality of the shooting images and making the shooting process more flexible and practical.
[0045] In one alternative implementation, the photographic equipment includes a camera and a lidar; The camera is used to capture images of the target and obtain target images; the lidar is used in conjunction with the camera to scan the target shooting area and generate a site map.
[0046] In the embodiments of this disclosure, the camera is used to capture images of the target to obtain target images, providing an image basis for subsequent intelligent scene analysis, shooting angle fine-tuning, and composition optimization.
[0047] Here, LiDAR is used in conjunction with cameras to perform collaborative scanning of the target shooting area. LiDAR acquires the distance and position information of obstacles in the area, and fuses it with the visual information collected by the camera to generate a scene map that includes the layout of the site environment and the distribution of obstacles. This provides spatial data support for the robot to plan shooting paths, avoid obstacles, and determine shooting positions.
[0048] The collaborative operation of the photography equipment ensures that the shooting robot can accurately locate the shooting position, adjust the height of the lifting platform and the angle of the robotic arm when shooting statically, and track the target and correct the movement path in real time when shooting dynamically, thus ensuring the stability and effectiveness of the shooting process.
[0049] In an optional implementation, the control module is further configured to: First, determine the path prediction model; Secondly, obtain obstacle information of the target shooting site obtained by LiDAR scanning; Finally, if the target is determined to be outside the shooting range based on the site map, obstacle information and site map are input into the path prediction model to obtain the movement path.
[0050] In embodiments of this disclosure, a neural network model to be trained (e.g., a convolutional neural network (CNN) model) can be determined.
[0051] Next, the labeled dataset can be used to train the neural network model to obtain the path prediction model. The labeled dataset includes, but is not limited to, shooting targets in various environments and the shooting locations of the targets, to ensure that the trained neural network model (i.e., the path prediction model mentioned above) can generalize to different scenarios.
[0052] Here, the path prediction model can learn the mapping relationship between different target shooting locations and the optimal movement path under different environmental characteristics based on training.
[0053] The neural network model under training, after multiple iterations and optimizations, is adaptable to complex site environments, can quickly process input site information and output reasonable movement path schemes, ensuring the accuracy and real-time performance of path planning.
[0054] Here, the lidar emits a laser beam to perform a full-range, high-precision scan of the target shooting area. It uses the laser ranging principle to calculate the time difference between laser emission and reflection, and combines the scanning angle information to accurately obtain obstacle information of various obstacles (including fixed facilities, temporary obstructions, etc.) in the area.
[0055] The obstacle information includes, but is not limited to: the three-dimensional coordinates of the obstacle, the distance between the obstacle and the camera robot, and its contour data.
[0056] Among these features, obstacle information can be used to determine the specific location distribution of obstacles in the field, providing accurate obstacle information support for path planning and avoiding collisions during the movement of the shooting robot.
[0057] Here, the path prediction model can comprehensively analyze obstacle information and site map, and combine the location of the shooting target to automatically avoid obstacle areas and plan an optimal movement path that takes into account the shortest movement distance, the least time, and no risk of collision.
[0058] In the above embodiments, the method of determining the movement path avoids the shooting robot blindly moving and probing, improves the efficiency of the shooting robot in responding to shooting needs, and ensures the smoothness and safety of the movement process, laying the foundation for quickly adjusting to a suitable shooting position and improving the shooting effect.
[0059] In an optional implementation, the control module is further configured to: First, with the target in motion, the motion path of the target is captured by the camera equipment; Secondly, the motion path is analyzed to obtain the predicted path of the target at the next moment; Finally, based on the motion path and the predicted path, the future movement path of the camera robot is obtained.
[0060] In the embodiments of this disclosure, the target being photographed is in motion, that is, the photographing state of the target is dynamic shooting.
[0061] Here, the motion path of the target can be continuously acquired through photographic equipment. The camera in the photographic equipment captures continuous frame images of the target in real time, while the LiDAR simultaneously acquires the real-time position coordinates and movement speed data of the target, thereby dynamically monitoring the target and obtaining its motion path.
[0062] The control module can perform temporal correlation and integration of continuously acquired location information and image frame data to determine the position trajectory of the target at different time points, forming the target's motion path and providing comprehensive basic information for subsequent analysis.
[0063] Here, the control module can combine the target's moving speed, acceleration, and direction of motion extracted from the motion path, and use a preset trajectory analysis algorithm (such as a trajectory prediction algorithm based on Kalman filtering) to mine the motion pattern of the captured target.
[0064] The control module can refer to the environmental constraints of the target shooting site (such as site boundaries, obstacle distribution, etc.) to eliminate unreasonable movement possibilities and accurately predict the high probability movement trajectory of the shooting target at the next moment, that is, the predicted path.
[0065] Here, the control module can comprehensively analyze the historical movement trend and future predicted trajectory of the target (i.e., the predicted path of the target at the next moment), and combine the robot's own mobility performance (such as maximum speed, turning flexibility, etc.), the relative relationship between its current position and the shooting range, and the distribution of obstacles in the site map to dynamically plan the robot's movement nodes, turning timing, and movement speed, thereby obtaining the robot's future movement path.
[0066] In the above embodiments, the generated future movement path can ensure that the robot always follows the shooting target and keeps the target within the shooting range, while avoiding obstacles in the field, ensuring the smoothness and efficiency of the movement process, and providing reliable support for stable shooting in dynamic scenes.
[0067] In an optional implementation, the control module is further configured to: First, the motion state of the camera robot is determined as it moves according to the movement path; the motion state is used to indicate whether the movement of the camera robot is smooth. Secondly, based on the motion state, it is determined that the motion of the shooting robot is unstable, and the direction of the acceleration of the shooting robot is determined. Secondly, the direction opposite to the direction of acceleration is determined as the target acceleration direction; Finally, the camera robot is adjusted based on the direction of the target acceleration.
[0068] In the embodiments of this disclosure, the control module can monitor and analyze parameters such as displacement fluctuation, attitude tilt angle, and vibration frequency of the camera robot in real time by combining data from the inertial measurement unit (including components such as accelerometers and gyroscopes) on the camera robot with the wheel speed feedback of the mobile device and the attitude sensor data of the lifting platform and the robotic arm, and obtain real-time monitoring results.
[0069] Then, the real-time monitoring results can be analyzed to obtain the motion state of the camera robot. For example, a stability threshold range can be set, and the real-time monitoring results can be compared with the stability threshold to determine whether the camera robot is in a stable motion state.
[0070] Here, when vibration, tilting, or bumping of the camera robot is detected (i.e., the camera robot's movement is unstable), the control module can perform vector analysis on the acceleration data, combine it with the temporal changes of the motion trajectory, remove environmental interference factors, and accurately identify the direction of acceleration that causes the robot's unstable movement.
[0071] Here, when the motion of the shooting robot is determined to be unstable based on its motion state, the force causing the unstable motion of the shooting robot can be counteracted by applying a reverse acceleration. Therefore, the target acceleration direction is derived in reverse based on the acceleration direction. This direction can specifically counteract the effects of vibration or tilt, allowing the shooting robot to quickly return to a stable state.
[0072] Here, the control module can send coordinated adjustment commands to the drive system of the mobile device, the adjustment mechanism of the lifting platform, and the attitude control system of the robotic arm based on the direction of the target acceleration.
[0073] In the above implementation, a reverse force is applied in the direction of the target acceleration to quickly suppress vibration and correct tilt, so that the shooting robot remains stable during movement, ensuring that the camera can capture images stably and avoiding problems such as image blurring and composition shift caused by unstable movement.
[0074] In an optional implementation, the control module is further configured to: First, the image processing model is determined; the image processing model is used to optimize the layout of the image. Secondly, after controlling the robotic arm to adjust the photography equipment to a shooting position that meets the preset shooting conditions, the initial shooting image of the target is acquired; Secondly, the initial captured image is input into the image processing model to obtain composition optimization parameters; Finally, based on the composition optimization parameters, the shooting robot is controlled to adjust the position of the photography equipment.
[0075] In embodiments of this disclosure, a deep neural network (DNN) model to be trained can be determined.
[0076] Then, the deep neural network model to be trained was trained using a high-quality labeled image dataset to obtain an image processing model.
[0077] Among them, the high-quality image dataset includes various shooting scenarios covering static scenes, dynamic scenes, and different lighting conditions. This enables image processing models to learn and master core aesthetic principles such as the rule of thirds, the golden ratio, and visual guiding lines, as well as composition optimization logic such as target positioning, background coordination, and lighting adaptation.
[0078] Here, after multiple rounds of iterative optimization, the deep neural network model to be trained has the ability to accurately identify layout defects in different types of images and quickly output optimization solutions, which can specifically improve the composition rationality and visual appeal of images.
[0079] Here, meeting the preset shooting conditions means that the basic requirements for shooting have been initially met, such as shooting distance, basic angle, exposure parameters, etc.
[0080] Here, a complete image of the target can be captured by the camera of the photography equipment as the initial image. This image contains the main features of the target, background environmental elements, and color and brightness information under the current lighting conditions, providing raw data support for subsequent composition optimization.
[0081] The control module translates composition optimization parameters into specific control commands, which are then sent to the drive systems of the robotic arm and the lifting platform. Through the rotation and extension of the robotic arm, the horizontal angle and shooting distance of the photographic equipment are fine-tuned to position the target at the golden ratio point or the optimal position conforming to the rule of thirds. The lifting platform's slight height adjustment optimizes the vertical composition ratio of the image, avoiding distracting elements in the background. Simultaneously, the focal length of the photographic equipment is adjusted to ensure the target is clearly defined and the background elements are distinct. This coordinated and precise adjustment of multiple components ensures that the final image composition conforms to aesthetic standards, effectively improving shooting quality and visual effects, achieving professional-level intelligent composition without human intervention.
[0082] In another embodiment, the shooting device can dynamically adjust the camera angle according to the target's position to ensure that the target is always centered in the frame and can be continuously tracked even if the target moves.
[0083] In another embodiment, the control module can intelligently analyze the background and other environmental elements, such as lines and color contrasts, to create compositions with depth and dimension. It automatically identifies and utilizes natural frames (such as doorways and tree branches) to guide the eye, enhancing the visual appeal and interest of the image.
[0084] The control module can also manage light and color: it automatically adjusts exposure, contrast, and saturation based on current lighting conditions to ensure rich and realistic colors. In low-light conditions, it intelligently supplements light while maintaining natural tones, avoiding overexposure or underexposure that could affect the overall aesthetics.
[0085] In another embodiment, the composition is dynamically adjusted as the target moves to maintain its optimal position in the frame, while also considering the direction and speed of movement to predict the next best composition point. For continuous shooting, this ensures a smooth transition in composition between each frame, improving video coherence and viewing experience.
[0086] In another embodiment, the intelligent shooting system also provides an intelligent shooting system user interface, allowing users to set personal preferences, such as a preference for a certain composition style (classical, modern), a specific color scheme, or a priority for target types. It learns user habits and automatically optimizes composition strategies over time to meet the user's aesthetic needs.
[0087] Based on the same inventive concept, this disclosure also provides an intelligent shooting method corresponding to the intelligent shooting system. Since the principle of the method in this disclosure for solving the problem is similar to that of the intelligent shooting system described above, the implementation of the method can refer to the implementation of the system, and repeated details will not be repeated. The executing entity of the intelligent shooting method provided in this disclosure is generally a computer device with certain computing capabilities, such as a terminal device, a server, or other processing devices. In some possible implementations, the intelligent shooting method can be implemented by a processor calling computer-readable instructions stored in memory.
[0088] Reference Figure 2 The diagram shows a flowchart of an intelligent shooting method provided in an embodiment of this disclosure. The method includes steps S201-S204 and is applied to a control module, wherein: S201. Obtain a site map of the target shooting location and determine whether the shooting target is within the shooting range based on the site map; S202. When the target is determined to be within the shooting range based on the site map, control the robotic arm to adjust the camera equipment to a shooting position that meets the preset shooting conditions. S203. If it is determined from the site map that the shooting target is not within the shooting range, generate a movement path based on the site map. S204. Control the movable device to move and / or the lifting platform to move within the shooting range, and execute the step of controlling the robotic arm to adjust the camera equipment to a shooting position that meets the preset shooting conditions.
[0089] In the embodiments of this disclosure, the framing range of the target shooting location can be determined, and a site map of the target shooting location can be generated based on the framing range.
[0090] After the site map is determined, it can be sent to the control module, so that the control module can determine the location of the shooting robot in the target shooting site based on the site map.
[0091] The fact that the target is within the shooting range can be understood as the shooting robot only needing to move the robotic arm installed on the shooting robot when shooting the target.
[0092] Here, the control module can collect data on the weight of the camera device and the horizontal and vertical movement range of the robotic arm.
[0093] While the target is within the shooting range, the control module must ensure that the center area of the moving camera device is no larger than the base area of the shooting robot to prevent the shooting robot from tipping over.
[0094] If the target is determined to be outside the shooting range based on the site map, the control module can control the shooting robot to move into the shooting range of the target.
[0095] The shooting range includes both the vertical and horizontal dimensions. The movement path includes the horizontal and vertical movement paths of the shooting robot.
[0096] Here, when the control module determines, based on the site map, that the shooting robot is neither in the horizontal nor vertical range of the target shooting site, it can first control the movable device of the shooting robot to move to the horizontal range of the target shooting site based on the horizontal movement path in the movement path, and then control the lifting platform of the shooting robot to move to the vertical range of the target shooting site based on the vertical movement path in the movement path.
[0097] Here, if the control module determines that the shooting robot is not within the horizontal range of the target shooting site based on the site map, it can control the movable device of the shooting robot to move to the horizontal range of the target shooting site based on the horizontal movement path in the movement path.
[0098] Here, if the control module determines that the shooting robot is not within the vertical range of the target shooting site based on the site map, it can control the lifting platform of the shooting robot to move to the vertical range of the target shooting site based on the vertical movement path in the movement path.
[0099] After the shooting robot is moved into the shooting range, the camera equipment can be fine-tuned by controlling the machinery to make it meet the preset shooting conditions.
[0100] The preset shooting conditions include, but are not limited to: the subject being in the golden position of the camera's composition, and the subject being in an environment with a sense of depth.
[0101] This embodiment acquires a site map through a photographic device, overcoming the deficiency of existing shooting robots in lacking global environmental awareness. This allows the control module to accurately determine the relative position of the shooting target and the shooting range, avoiding blind movement and probing, and significantly improving response speed and shooting efficiency. At the same time, with the coordinated cooperation of mobile devices, lifting platforms, and robotic arms, the range of shooting posture and height adjustment is expanded, and the photographic device can be flexibly adapted to preset shooting conditions in different scenarios through targeted adjustments. This solves the problems of single shooting angle adjustment and poor scene adaptability in existing technologies, effectively ensuring the quality of the captured images and making the shooting process more flexible and practical.
[0102] In an optional implementation, the following steps are also included: First, with the target in motion, the motion path of the target is captured by the camera equipment; Secondly, the motion path is analyzed to obtain the predicted path of the target at the next moment; Finally, based on the motion path and the predicted path, the future movement path of the camera robot is obtained.
[0103] In the embodiments of this disclosure, the target being photographed is in motion, that is, the photographing state of the target is dynamic shooting.
[0104] Here, the motion path of the target can be continuously acquired through photographic equipment. The camera in the photographic equipment captures continuous frame images of the target in real time, while the LiDAR simultaneously acquires the real-time position coordinates and movement speed data of the target, thereby dynamically monitoring the target and obtaining its motion path.
[0105] The control module can perform temporal correlation and integration of continuously acquired location information and image frame data to determine the position trajectory of the target at different time points, forming the target's motion path and providing comprehensive basic information for subsequent analysis.
[0106] Here, the control module can combine the target's moving speed, acceleration, and direction of motion extracted from the motion path, and use a preset trajectory analysis algorithm (such as a trajectory prediction algorithm based on Kalman filtering) to mine the motion pattern of the captured target.
[0107] The control module can refer to the environmental constraints of the target shooting site (such as site boundaries, obstacle distribution, etc.) to eliminate unreasonable movement possibilities and accurately predict the high probability movement trajectory of the shooting target at the next moment, that is, the predicted path.
[0108] Here, the control module can comprehensively analyze the historical movement trend and future predicted trajectory of the target (i.e., the predicted path of the target at the next moment), and combine the robot's own mobility performance (such as maximum speed, turning flexibility, etc.), the relative relationship between its current position and the shooting range, and the distribution of obstacles in the site map to dynamically plan the robot's movement nodes, turning timing, and movement speed, thereby obtaining the robot's future movement path.
[0109] Reference Figure 3 The diagram shows a flowchart illustrating the processing of various motion states in an intelligent shooting method provided by an embodiment of this disclosure, wherein: S31. Determine whether the target is in motion.
[0110] S32. When the target is not in dynamic shooting mode, find the target and plan the path based on the site map of the target shooting location.
[0111] S33. Take pictures of the target based on the target path.
[0112] S34. When the target is in motion, the motion path of the target is captured by the camera.
[0113] S35. Analyze the motion path to obtain the predicted path of the target at the next moment.
[0114] S36. Based on the motion path and the predicted path, the future movement path of the shooting robot is obtained.
[0115] S37. Track and photograph the target based on its future movement path.
[0116] In the above embodiments, the generated future movement path can ensure that the robot always follows the shooting target and keeps the target within the shooting range, while avoiding obstacles in the field, ensuring the smoothness and efficiency of the movement process, and providing reliable support for stable shooting in dynamic scenes.
[0117] In one alternative implementation, refer to Figure 4 The diagram shows a flowchart of motion planning for an intelligent shooting system provided in an embodiment of this disclosure, wherein: Motion component calculations are performed when the shooting robot of the intelligent shooting system is in motion.
[0118] Here, motion is divided into vertical motion components and horizontal motion components.
[0119] Here, the range of motion can be determined from the calculation results of the vertical motion component and the horizontal motion component respectively.
[0120] If the calculation result indicates a small movement, control the movement of the robotic arm; if the calculation result indicates a small movement, control the movement of the lifting platform.
[0121] After filming is completed, the robotic arm will be retrieved.
[0122] Corresponding to Figure 1 In addition to the gas leakage monitoring method, this disclosure also provides an electronic device 500, such as... Figure 5 The diagram shown is a structural schematic of an electronic device 500 provided in an embodiment of this disclosure, including: The system includes a processor 51, a memory 52, and a bus 53. The memory 52 stores execution instructions and includes main memory 521 and external memory 522. The main memory 521, also called internal memory, temporarily stores the computational data in the processor 51, as well as data exchanged with external memory such as a hard disk. The processor 51 exchanges data with the external memory 522 through the main memory 521. When the electronic device 500 is running, the processor 51 communicates with the memory 52 through the bus 53, causing the processor 51 to execute the following instructions: Obtain a site map of the target shooting location, and determine whether the shooting target is within the shooting range based on the site map; If the target is determined to be within the shooting range based on the site map, the robotic arm is controlled to adjust the camera to a shooting position that meets the preset shooting conditions. If it is determined from the site map that the target is not within the shooting range, a movement path is generated based on the site map; The steps include controlling the movable device to move and / or the lifting platform to move within the shooting range, and controlling the robotic arm to adjust the photography equipment to a shooting position that meets the preset shooting conditions.
[0123] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.
[0124] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.
[0125] Additionally, as used herein, the "or" used in a list of items beginning with "at least one" indicates a separate list, such that a list of, for example, "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not imply that the described example is preferred or better than other examples.
[0126] It should also be noted that in the systems and methods of this disclosure, the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions to this disclosure.
[0127] Various changes, substitutions, and modifications can be made to the technology described herein without departing from the teachings defined by the appended claims. Furthermore, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, events, means, methods, and actions described above. Currently existing or later-developed processes, machines, manufactures, events, means, methods, or actions that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein can be utilized. Therefore, the appended claims include such processes, machines, manufactures, events, means, methods, or actions within their scope.
[0128] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.
[0129] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.
Claims
1. An intelligent shooting system, characterized in that, include: A camera robot and a control module; the camera robot includes a camera device, a robotic arm connected to the camera device, a lifting platform connected to the robotic arm, and a movable device connected to the lifting platform; The photographic device is used to acquire a site map of the target shooting location and transmit the site map to the control module. The control module is used to control the robotic arm to adjust the photographic device to a shooting position that meets preset shooting conditions when the shooting target is determined to be within the shooting range based on the site map; when the shooting target is determined to be outside the shooting range based on the site map, the control module generates a movement path based on the site map and controls the movable device to move and / or the lifting platform to move to the shooting range, and then executes the step of controlling the robotic arm to adjust the photographic device to a shooting position that meets preset shooting conditions.
2. The system as described in claim 1, characterized in that, The photographic equipment includes a camera and a lidar; The camera is used to capture images of the target to obtain target images; the lidar is used in conjunction with the camera to scan the target shooting area to generate the site map.
3. The system as described in claim 2, characterized in that, The control module is also used for: Determine the path prediction model; Obtain obstacle information of the target shooting site obtained by the LiDAR scan; If, based on the site map, it is determined that the target is not within the shooting range, the obstacle information and the site map are input into the path prediction model to obtain the movement path.
4. The system as described in claim 1, characterized in that, The control module is also used for: When the target is in motion, the camera captures the movement path of the target. The motion path is analyzed to obtain the predicted path of the target at the next moment; The future movement path of the shooting robot is obtained by processing the motion path and the predicted path.
5. The system as described in claim 1, characterized in that, The control module is also used for: When the shooting robot moves according to the movement path, the motion state of the shooting robot is determined; wherein, the motion state is used to indicate whether the movement of the shooting robot is smooth; If the motion of the shooting robot is determined to be unstable based on the motion state, the direction of acceleration of the shooting robot is determined. The direction opposite to the acceleration direction is defined as the target acceleration direction. The camera robot is adjusted based on the target acceleration direction.
6. The system as described in claim 1, characterized in that, The control module is also used for: Determine an image processing model; wherein the image processing model is used to optimize the layout of the image; After controlling the robotic arm to adjust the photography device to a shooting position that meets the preset shooting conditions, the initial image of the target is captured. The initial captured image is input into the image processing model to obtain composition optimization parameters; Based on the composition optimization parameters, the shooting robot is controlled to adjust the position of the photography equipment.
7. An intelligent shooting method, characterized in that, include: Obtain a site map of the target shooting location, and determine whether the shooting target is within the shooting range based on the site map; If the target is determined to be within the shooting range based on the site map, the robotic arm is controlled to adjust the camera equipment to a shooting position that meets the preset shooting conditions. If it is determined from the site map that the target is not within the shooting range, a movement path is generated based on the site map; Control the movable device to move and / or the lifting platform to move within the shooting range, and execute the step of controlling the robotic arm to adjust the photography equipment to a shooting position that meets the preset shooting conditions.
8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method as described in claim 7.
9. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method as described in claim 7.
10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method as described in claim 7.