136 results about "Motion direction" patented technology

The invention provides an elevation map path planning method and system based on a terrain adaptive potential energy field, and relates to the technical field of path planning. Comprising the steps of calculating the gradient and roughness of the position of an intelligent agent, setting a terrain adaptive gain, dynamically adjusting the gradient and roughness, and obtaining a terrain adaptive repulsive force field and a composite potential energy field in combination with a basic repulsive force field; determining the motion direction of the agent based on the composite potential energy field, and determining the next position of the agent; in the process that the intelligent agent moves to the next position, whether local re-planning needs to be carried out on the next position of the intelligent agent or not is judged based on a preset environment change judgment rule; and when re-planning is needed, recalculating the terrain adaptive repulsive force field and the dynamic obstacle repulsive force field, updating the composite potential energy field, and re-determining the next position of the intelligent body. According to the invention, the terrain can be effectively sensed, the planning strategy is adaptively adjusted, and high precision, high efficiency and strong robustness are considered.

The invention provides an intelligent control method and system for obstacle avoidance sudden stop of an AMR robot and a medium, and the method comprises the steps: determining the position coordinates of an obstacle based on the original image data and point cloud data of the AMR robot in a target scene; the linear distance between the obstacle and the AMR robot is determined on the basis of the position coordinates in combination with real-time positioning information of the AMR robot, and the movement speed and the movement direction of the obstacle are determined on the basis of position time sequence changes of the position coordinates of the obstacle in continuous time; determining the shortest predicted meeting time between the obstacle and the AMR robot based on the linear distance, the movement speed and the movement direction in combination with the driving speed and the driving direction of the AMR robot; and if the shortest predicted meeting time is smaller than the corresponding dynamic safety threshold value, generating a sudden stop control instruction and sending the sudden stop control instruction to a motion control system so as to control the AMR robot to execute sudden stop operation. According to the invention, balance of safety and efficiency of the AMR in a dynamic environment is realized.

This invention discloses a target tracking method for unmanned aerial vehicles (UAVs), relating to the field of computer vision, aiming to solve the problems of target occlusion, rapid movement, and efficiency in dynamic scenes. The method includes: acquiring the target's bounding box and confidence score through a detector, and predicting the target's position and state using a noisy adaptive Kalman filter; proposing a confidence-based feature extraction and judgment strategy, performing IoU matching between the trajectory and the detection box; for targets with a matching degree below a threshold and a confidence score change rate above a threshold, extracting appearance features using a lightweight feature re-identification network (Rep-OSNet); otherwise, reusing features from the previous frame; designing a cost function that fuses motion direction and appearance similarity to perform cascaded matching between the target and the confirmed trajectory; performing secondary association matching on targets and trajectories that mismatch in the cascaded matching; updating the matched trajectory state using a noisy adaptive Kalman filter, deleting long-term lost mismatched trajectories, and outputting the target trajectory prediction box and ID.

The invention relates to a target track association method in a multi-target environment. The method comprises the following steps: firstly, preprocessing a new received trace point; secondly, predicting the next position of each track by using the existing track historical information and adopting a Kalman filtering algorithm, meanwhile, adjusting a state transition matrix and a process noise covariance matrix in real time by considering factors such as ocean current and wind direction in an offshore environment, and adjusting an observation noise covariance matrix according to meteorological information; then comprehensively considering distance, speed difference and motion direction difference to calculate a correlation degree magnitude between a new receiving trace point and each predicted track position; and finally, judging whether the newly received trace point belongs to the existing target track or forms a new target by adopting a threshold judgment method according to the correlation degree value, and updating the state of the track. The method can effectively cope with multi-target intersection, observation loss and clutter interference, improves the stability of a matching result, can realize continuous tracking of a marine target, can adjust parameters according to the environment and target characteristics, and has high adaptability.

The present invention discloses a multi-target tracking method based on weak clues and trajectory prediction, which belongs to the technical field of deep learning multi-target tracking. The present invention first sets a target detection model, and then sets a target tracking algorithm. When occlusion occurs, the position-speed-LSTM model is used to predict the future trajectory of the target and calculate the motion direction cost; when there is no occlusion, the Kalman filter is used to predict the trajectory; when calculating the position cost, the appearance feature model is used to extract the appearance features based on the designed mixed height intersection-union ratio using the altitude state as a weak clue. After obtaining each clue, the trajectory of the target is assigned using the strong and weak clues through the Hungarian algorithm. In order to balance and utilize each cost, the present invention realizes multi-target tracking through three-dimensional association based on the configured allocation cost strategy. The present invention solves the problems of occlusion, similar objects, appearance degradation, etc. to a certain extent, and enhances the model generalization ability and target tracking ability for complex scenes.

The invention discloses an unmanned ship path optimization method based on visual detection, and belongs to the technical field of unmanned ships, and the method comprises the steps: receiving first image information collected by a visual sensor carried by an unmanned ship and navigation parameter information from the unmanned ship, and constructing an environment perception model; performing motion trend prediction and unmanned ship collision risk comprehensive evaluation on the dynamic target; constructing a multi-dimensional threat assessment function, carrying out quantitative sorting on all known collision risk sources, defining a threat assessment index for each risk source, and optimizing a multi-target conflict logic; and dynamically adjusting the course and speed of the unmanned ship based on the output threat assessment result. In the implementation process of the technical scheme, the surrounding environment is perceived in real time through visual detection, parameters such as obstacle types, distances, relative speeds and movement directions are input into a multi-dimensional threat assessment function, and dynamic weighted sorting of different risk sources is realized, so that navigation path optimization is performed on the unmanned ship.

The invention relates to the technical field of computer vision, in particular to a motion perception rockfall intelligent monitoring method and device based on deep learning. The method comprises the following steps: receiving a monitoring video from a monitoring area; constructing a rockfall detection and tracking framework based on a YOLOv8 target detection network and a ByteTrack target tracking algorithm; preprocessing the monitoring image, inputting the monitoring image into a YOLOv8 detection network to carry out moving target feature extraction, and outputting a rockfall detection result; and track matching is carried out by using a ByteTrack algorithm in combination with Euclidean distance and motion direction constraint, and a rockfall motion track is generated. According to the method, a traditional image algorithm and a deep learning algorithm are combined, moving target detection and multi-target tracking are constructed, and rockfall in a complex rock background is accurately captured from multiple dimensions; according to the method, the space coordinate position of the rockfall target can be accurately obtained, a complete movement track can be generated for each rockfall target, statistical information of rockfall events is effectively obtained, and a reliable basis is provided for disaster grade evaluation and early warning.

The invention relates to a pure vision autonomous navigation method for a mobile robot based on ground structure line guidance. The method comprises the following steps: binocular-inertia joint perception and state estimation; carrying out ground area constraint and two-dimensional line segment extraction; performing line segment screening and geometric fitting based on motion direction constraint; carrying out three-dimensional parametric modeling and category discrimination on multiple types of ground structure lines; calculating a pose error of a relative structure line and constructing a reference trajectory; performing closed-loop motion control based on the Lapunov stability; carrying out key position judgment and motion decision making based on an image template; compared with the prior art, by introducing a visual guidance mechanism based on a ground structure line and fully utilizing natural ground structure characteristics such as a space structure boundary line, stable autonomous navigation of the mobile robot is realized without depending on artificial markers such as a high-precision map, GNSS (Global Navigation Satellite System) positioning, a two-dimensional code and a magnetic stripe; the dependence of the system on complex sensors and environment modification is effectively reduced, and the deployment and maintenance cost is remarkably reduced; meanwhile, through unified modeling of multi-type structural line features, the adaptive capacity and robustness of the navigation method in various application scenes such as warehouse logistics, park inspection, in-plant transportation and semi-structured roads are improved, high navigation stability and reliability can be kept in tasks such as fixed route inspection, lane keeping and back-and-forth running, and the navigation method is suitable for large-scale popularization and application. And the method has good engineering practical value and popularization and application prospects.

The invention discloses a salamander-imitating robot omni-directional motion control method and system based on reinforcement learning, and belongs to the field of electromechanical system control. The method comprises the following steps: acquiring robot state information and a motion instruction; a periodic phase variable is generated through a phase integration module, and target actions of all joints are output through a track generator; designing a reward function based on behavior constraint, and constraining motion directivity and attitude stability; the morphological symmetry of the body structure of the salamander-imitating robot is utilized to symmetrically enhance the state-action sample so as to expand training data; and a reinforcement learning algorithm is adopted, and a stable and efficient omnidirectional motion control model is obtained according to a reward feedback and symmetric enhancement data iteration updating control strategy. The method can realize the generation of the omni-directional motion strategy driven by reinforcement learning without presetting a gait model, has the advantages of natural motion mode, high control precision and strong adaptability, and can be widely applied to the fields of complex terrain detection, intelligent inspection and the like.

The invention discloses an object tracking method and device and electronic equipment, and relates to the technical field of vehicles and the technical field of automatic driving. The method comprises the following steps: acquiring historical state data, a current prediction state and to-be-matched data corresponding to a scene object; based on the historical state data, the current prediction state and the to-be-matched data, determining the motion direction similarity between the tracking frame and the candidate frame; calculating a region overlapping degree between the tracking frame and the candidate frame by using the current prediction state and the to-be-matched data; performing matching analysis on the tracking frame and the candidate frame according to the motion direction similarity and the region overlapping degree to obtain a matching result; and determining the candidate frame as the tracking frame matched with the scene object at the current moment in response to the fact that the matching result indicates that the tracking frame is successfully matched with the candidate frame. According to the invention, the technical problems of easy mismatching and low tracking accuracy of an object tracking method in the prior art are solved.

A display method and an electronic device, which are applicable to the technical field of display, and can reduce the risk of motion sickness caused by the inconsistency between motion information seen by eyes and motion information perceived by other organs of the body. The electronic device moves along with the movement of a vehicle. The method comprises: determining a motion state of a vehicle, wherein the motion state indicates a motion direction and / or a motion speed of the vehicle, and the motion direction comprises a horizontal direction and a vertical direction; and then displaying, in a preset area in a display interface of an electronic device, a dynamic effect corresponding to the motion state. A dynamic effect corresponding to a motion state of a vehicle is displayed in a preset area in a display interface of an electronic device, and the motion state of the vehicle is simulated, so that motion information seen by eyes of a user is consistent with motion information perceived by other organs of the body.

The invention provides a course rapid initial alignment method and device for vehicle-mounted integrated navigation, and relates to the technical field of navigation calibration, and the method comprises the following steps: based on three-axis acceleration data, eliminating a component of gravitational acceleration in a horizontal direction through attitude compensation, and obtaining a horizontal longitudinal acceleration measurement value; carrying out plane coordinate projection based on the GNSS positioning data to obtain a track point sequence; determining the horizontal displacement length of the current track point and other track points in the track point sequence; on the basis of the horizontal longitudinal acceleration measurement value and the track point sequence, the motion direction is judged through the speed change trend and the horizontal acceleration direction, the current track angle is corrected, and a corrected course angle is obtained; and based on the corrected course angle and the Z-axis angular velocity of the gyroscope measured by the IMU module, estimating the course angle error and the zero offset of the gyroscope by adopting an adaptive Kalman filtering algorithm, and outputting the corrected course angle. According to the invention, fast and accurate course initialization of combined navigation in a low-speed equipment operation scene can be realized.

The application belongs to the technical field of radio positioning and motion control, and specifically discloses a kind of exoskeleton control filtering methods based on UWB and IMU fusion, comprising: deploying UWB base station, UWB label and IMU module;First displacement of knee joint in horizontal direction is measured by UWB label, first forward speed is calculated, second displacement of knee joint in horizontal direction is measured by IMU module, and second forward speed is calculated;State equation and observation equation are constructed, Sigma point is generated and untraceable Kalman filtering iteration is executed, and prediction result is optimized until the confidence of prediction result reaches a preset value.The application applies PDOA algorithm to solve angle, the angle and angular velocity measured by IMU module are fused by untraceable Kalman filtering, the motion direction error caused by single sensor is avoided, and the attitude estimation precision of exoskeleton control is improved.The application is suitable for exoskeleton control.

The application provides a crane group boom anti-collision early warning method and system based on digital twinning, which comprises the following steps: based on the data collected by a rotary encoder, an angle sensor, an inertial measurement unit, a laser radar and a ship body attitude measuring device, a dynamic three-dimensional digital twinning model is constructed and updated in real time; in the model, real-time path planning is performed on each crane boom, the spatial interference risk with the bulkhead, hatch coaming and other booms is evaluated, and a collision-free optimal action path is generated; the path nodes are dynamically risk evaluated, the minimum distance, relative speed, motion direction angle and ship body swing disturbance are comprehensively considered, and a collision risk score is generated; according to the score, hierarchical intervention control is implemented, the collision is avoided, and the attitude stability of the suspended goods is maintained. The application realizes the safety early warning and intelligent regulation and control of multi-machine cooperative operation under high dynamic sea conditions, and effectively improves the operation efficiency and safety.

The invention discloses a task-aware robot availability prediction method based on retrieval enhancement and cross-image alignment. The method comprises the following steps: constructing an accessibility memory bank containing object appearance characterization and interaction prior; performing semantic filtering on the memory bank based on the task tag, and retrieving a reference sample according to appearance similarity; a prediction process is divided into two parts, namely static contact point positioning and dynamic action direction prediction, contact points are correspondingly positioned by querying dense features of an image and a reference sample, and an action direction is regressed by a retrieval-enhanced cross-image alignment model; the model performs action vector modulation on the reference features, and performs gating cross-attention fusion with the query image features, and the fusion weight is jointly determined by the similarity and the learnable weight; and finally, the two-dimensional contact point and the action direction are lifted into a three-dimensional pose and a three-dimensional trajectory, and executable grabbing and post-contact actions are generated. According to the method, cross-category robust generalization under the condition of few samples can be realized, and the operation success rate of the robot is improved.

The invention belongs to the technical field of virtual reality, and provides a ball training scene simulation method, device and equipment, a medium and a program product, and the method comprises the steps: obtaining the motion data, collected by multiple sensors, of a target player in a training field; the target player is any player participating in training; the motion data comprises a motion track, a motion speed, a motion direction and a three-dimensional position of the target player; generating an obstacle projection strategy according to the motion data, and sending the obstacle projection strategy to projection equipment; and the projection device projects an obstacle in the training field according to the obstacle projection strategy so as to simulate an obstacle scene for training of the target player. The movement condition of the target player is captured through multiple sensors, and the obstacle projection strategy is generated, so that the projection of the obstacle is dynamically adjusted according to the movement condition of the player, the dynamic nature and complexity of training scene simulation are improved, and the training requirements of the player can be better met.

Embodiments of the present application disclose a motion control method, device, equipment and medium, wherein the method comprises: acquiring a control force parameter on a motion control component of a target control object through a three-dimensional force sensor; determining a target motion parameter of at least one motion mechanism of the target control object according to a mapping relationship between the control force parameter and a preset motion parameter in a corresponding motion direction; and controlling the motion mechanism to move according to the target motion parameter. The technical solution of the embodiments of the present application solves the technical problem that the existing motion equipment cannot accurately perceive the control force to move, and can accurately perceive any direction and size of the control force to accurately control the motion of the target control object, thereby improving the accuracy and flexibility of the motion control of the target control object.

A method, a device (800), a medium for controlling the movement of a virtual body (107), including: a target determining step, in the first frame, based on the moving direction and position of the virtual body (107), selecting a virtual object (103) in a predetermined area as a virtual target (202); a dynamic adjusting step, calculating a horizontal moving direction (302a) of the virtual body (107), a direction of a connecting line between a vertical projection (107′a) of the virtual body (107) on the horizontal plane and a vertical projection of the virtual target on the horizontal plane, and an included angle (θ1) between the horizontal moving direction (302a) of the virtual body (107) and the direction of the connecting line in each frame, and controlling the horizontal moving direction (302a) of the virtual body (107) based on the included angle (θ1) (204).

To provide a working device capable of controlling the position of a moving body while accurately detecting the moving amount of the moving body in the moving direction with an inexpensive constitution.SOLUTION: Height detector 45 of component placing device 1 including rising and falling body 41 and height detector 45 that detects the height of rising and falling body 41 includes mark member 52 that rises and falls together with rising and falling body 41 and includes the plurality of slits 60 disposed along the rising and falling direction, and two mark detectors 53 that detect the presence or absence of slit 60 at each of two detection positions (first detection position KP1 and second detection position KP2) set in movement path R of the plurality of slits 60 that rise and fall according to the movement of mark member 52. Counter 16c counts the number of changes in the combination of the presence or absence of slits 60 detected by each of two mark detectors 53 and height calculator 16d calculates the height of lift 41 based on the counted number of changes in the combination of the presence or absence of slits 60.SELECTED DRAWING: Figure 7

Embodiments of the present application disclose a collision behavior prediction method and device, electronic equipment and medium. The method comprises: predicting the movement direction and trajectory of a target according to the movement correlation information of the target; wherein the target comprises a first target and a second target; determining the blind area of the target at a prediction time according to the movement direction and trajectory of the target; wherein the prediction time is any time after the current time; determining a collision behavior prediction result according to the positional relationship between the blind area of the first target and the blind area of the second target at the prediction time, and the positional relationship between the blind area of the second target and the blind area of the first target at the prediction time; wherein the blind area of the first target is the blind area corresponding to the first target, and the blind area of the second target is the blind area corresponding to the second target. Through the above technical solution, the collision behavior of the second target and the first target can be accurately predicted, and the timeliness and accuracy of the collision behavior prediction are improved.

The invention relates to a driver control method and device and computer equipment. The method is applied to an ultrasonic endoscope, the ultrasonic endoscope comprises a driver, and the method comprises the steps that motion parameters of the driver are obtained; under the condition that the motion parameters meet preset conditions, the motion direction of the driver is controlled to be switched from the first motion direction to the second motion direction; the first movement direction is opposite to the second movement direction. By adopting the method, the phenomenon that the shape of the bourdon tube connected with the driver does not conform to the expectation due to the fact that the driver always moves in the fixed direction can be avoided, so that the image distortion phenomenon caused by the phenomenon that the shape of the bourdon tube does not conform to the expectation can be avoided, and the imaging quality of the ultrasonic endoscope is remarkably improved.

The invention discloses a ship automatic driving method capable of automatically avoiding obstacles, which comprises the following steps of: partitioning images shot in four directions of a ship in the driving process of the ship, capturing the contours of all constituent elements, and analyzing the change condition and the movement direction of each contour in adjacent time intervals; the ship automatically sails through a set coping method based on each condition, collision avoidance and automatic driving are carried out on obstacles through a method of combining vision with radar detection, the judgment on the obstacles is more accurate, and the detection distance is farther.

This application discloses a sensor-based intelligent prediction method, device, and medium for accompanying robots, belonging to the technical field of accompanying robots. The method includes: collecting user behavior, visual, and environmental data; filtering and standardizing the data using a Kalman filter algorithm to generate standard data; processing the standard data using an action recognition algorithm to determine user behavior; constructing a digital model based on standard environmental data, and combining this model with a preset target and reward function to select a navigation path; predicting the user's next position and direction of movement based on historical environmental data and a parallel interactive multi-model Kalman filter algorithm; and calculating the accompanying robot's motion commands based on the navigation strategy and user prediction information. This application effectively integrates data from multiple sensors, improves the accuracy of user behavior recognition, and enables the development of flexible and efficient navigation strategies.

The application discloses a multi-person redirection walking and position prediction method based on an artificial potential field, and belongs to the technical field of virtual reality and robot navigation. In view of the problems of fixed repulsion force weight, high collision risk, frequent resetting and short-term position prediction accuracy deficiency leading to collision in the traditional redirection walking algorithm in a multi-user dynamic scene, a dynamic potential field weight optimization mechanism is used to adjust the weight distribution of repulsion force between the environment and the user in real time according to the user density, to enhance the repulsion force intensity when the user approaches an obstacle or a dense area, and to introduce a safety distance and a direction perception mechanism, to analyze the user motion direction and the obstacle angle, to preferentially guide the deviation from a high-risk area, and to reduce the number of invalid resets. A prediction model adopts an encoder-decoder architecture, and a multi-layer long short-term memory network is embedded with an attention mechanism to dynamically capture key timing features in the space-time trajectory, and to improve the short-term position prediction accuracy.

Provided in the present application are a trajectory control method for a virtual projectile, and a related apparatus. The embodiments of the present application can be applied to scenarios such as games, virtual reality and augmented reality. The method comprises: when a user controls launching of a virtual item, in response to the launching operation, after a target virtual projectile that possesses a function of changing the motion trajectory along with the movement trajectory of a virtual object is launched, acquiring in real time the distance between the target virtual projectile and the virtual object or the included angle between the motion direction of the target virtual projectile and the movement direction of the virtual object; and, if the distance between the target virtual projectile and the virtual object is less than a distance threshold, or the included angle between the motion direction of the target virtual projectile and the movement direction of the virtual object is greater than or equal to an included angle threshold, controlling the target virtual projectile to stop changing the motion trajectory along with the movement trajectory of the virtual object. Thus, the present application can change invalid operations into valid operations, so as to reduce the occurrence frequency of invalid operations, thereby reducing the possibility of system performance problems and ensuring stable system operation.

The application discloses a security and warning robot instruction execution system for quick tracking of a holder, which acquires continuous image frames, a current angle of the holder and a circumferential obstacle distance, extracts center coordinates, scale variation, a motion direction and confidence of a warning target, constructs a warning intention propagation graph containing a target, a warning sector, a holder margin, a chassis pass, an obstacle suppression and a loss risk node to obtain a tracking intention value, generates a boundary pressure value according to a distance from the target to a boundary of the image, an interframe displacement towards the boundary, a remaining rotation angle of the holder and a circumferential passable distance of the chassis, determines a current main tracking target, and generates a pre-rotation angle of the holder, a segmented rotation speed curve and a chassis compensation rotation angle, and generates a target residual sector and recaptures the target when the confidence is reduced, so that the tracking stability in a quick moving and short-time shielding scene is improved.

This invention discloses a speed-controlled inertial force cancellation system and its cancellation method, comprising a worktable mounted on a frame, a worktable drive unit, a movable compensation unit, and a control unit. The worktable drive unit drives the worktable to accelerate and decelerate along a preset trajectory. The movable compensation unit is a moving body independent of the worktable drive unit, with a constant mass, and moves in the opposite direction to the worktable's motion direction under the control of the control unit. The control unit calculates the velocity and acceleration of the movable compensation unit based on the worktable's mass, real-time velocity and acceleration, and the movable compensation unit's mass, and calculates the movable compensation unit's velocity and acceleration based on the law of conservation of momentum, thereby driving the movable compensation unit to generate a compensation force equal in magnitude and opposite in direction to the worktable's inertial force, thus suppressing vibration transmitted to the frame. This invention can effectively cancel the worktable's inertial force without increasing the mechanism's or the overall weight, thus suppressing frame vibration.

The application discloses a path planning method, a path planning device, a self-moving device and a computer storage medium. The method is applied to the self-moving device, the self-moving device comprises a first front wheel and a second front wheel, the first front wheel and the second front wheel are arranged in a non-parallel manner, and the method comprises the following steps: when it is detected that the self-moving device is located on a slope, the direction of the slope is determined according to the current posture of the self-moving device; the first angle between the direction of the slope and the first front wheel and the second angle between the direction of the slope and the second front wheel are determined; the target motion direction of the self-moving device is determined according to the first angle and the second angle; the slope moving path is planned according to the target motion direction, and the self-moving device is controlled to move along the slope moving path. The method can improve the climbing ability of the self-moving device, and further improve the operation coverage and operation effect.

The invention provides a gyroscope null drift online calibration method and device based on a servo system position loop steady state and a readable storage medium thereof. The method is applied to a servo system comprising a position closed loop and a speed closed loop, and the position closed loop is set to be in a pure proportion (P) control mode; controlling the servo system to move to the same position reference point from a first motion direction and an opposite second motion direction respectively, and reaching a first static steady state and a second static steady state respectively in a P control mode; acquiring and recording a first steady-state position deviation and a second steady-state position deviation under the two steady states; and finally, averaging the first steady-state position deviation and the second steady-state position deviation, and determining the zero drift value of the gyroscope according to the average deviation value and the proportional gain of the position ring. According to the method disclosed by the invention, the interference of the static friction force of the servo system on the calibration result is eliminated in the mathematical principle by utilizing a bidirectional approximation averaging mode, online, high-precision and anti-interference gyroscope null drift calibration can be realized without external equipment, and a closed-loop verification mechanism is provided.

The invention discloses a two-dimensional correction method for a photoelectric coding disc of a translation rotating platform. The invention relates to the technical field of engineering measurement, and aims to solve the problem that errors generated by a photoelectric coding disc of a translation rotating platform in the vertical direction cannot be compensated in the prior art. According to the invention, coding array images and precision measurement light spot images on the photoelectric coding disc are acquired through the camera. And identifying a coarse precision absolute position according to the coding array image. And the light spot gravity center is extracted based on the light spot image, and the column pixel variation in the movement direction is calculated to obtain accurate displacement or angle. The line pixel variation in the vertical movement direction is calculated, and the axial movement and pitching error amount is determined. And the positioning result is compensated and corrected by using the error amount. According to the invention, not only can position displacement or angle be accurately measured in the movement direction, but also normal position movement and pitching bounce values of a translation or rotation plane can be accurately measured, so that positioning errors caused by the displacement or angle can be compensated.