283 results about "Stationary object" patented technology

The disclosed inventions include personal Unmanned Aerial Vehicles (UAV's) and UAV universal docking ports “docking ports” to be incorporated into and / or attached to headwear, including helmets, hard hats and hats and face masks, as well as footwear including boots and shoes, clothing and outerwear, devices, gear and equipment, land, air, water and space vehicles, buildings, wireless towers and other mobile or stationary objects and surfaces referred to collectively as “docking stations”. A docking station may have one or more docking ports for docking, networking and charging or refueling compact personal UAVs, and for providing data communications between said UAVs and other electronic devices that remain with the person while the UAV is in flight or driving or landed on terrain. Said docking ports may also incorporate wireless power transmission for remote wireless charging of one or more UAV's. Supplemental power for recharging said UAVs when docked may be supplied by integrated battery(s) in said docking port or me be provided directly from the docking station or other connected power source.

This document describes techniques and systems related to a radar system using a machine-learned model for stationary object detection. The radar system includes a processor that can receive radar data as time-series frames associated with electromagnetic (EM) energy. The processor uses the radar data to generate a range-time map of the EM energy that is input to a machine-learned model. The machine-learned model can receive as inputs extracted features corresponding to the stationary objects from the range-time map for multiple range bins at each of the time-series frames. In this way, the described radar system and techniques can accurately detect stationary objects of various sizes and extract critical features corresponding to the stationary objects.

The invention discloses a slow space driving anti-collision early warning method based on a risk field model, and the method comprises the steps: firstly constructing a potential energy field intensity model for static objects and road traffic markings in a slow shared space on an urban non-motor vehicle lane, and then constructing a kinetic energy field intensity model for non-motor vehicles driving on the urban non-motor vehicle lane, a behavior field intensity model is constructed for non-motor vehicle drivers driving on urban non-motor vehicle lanes, then potential energy field, kinetic energy field and behavior field force models in a risk field model are calculated, and finally a comprehensive risk field model is obtained. Based on field force vector analysis, the application path of the potential energy of the risk field in the shared space of the non-motor vehicles is defined, and a conflict evaluation index under the risk field theory is provided on the basis. The index can be used for dynamically identifying potential conflicts, and provides a basis for early warning and intervention of non-motor vehicles.

The invention discloses an occupied grid labeling method and device, and the method comprises the steps: extracting an inter-frame pose transformation matrix and a detection frame tracking identifier corresponding to time sequence data when multiple frames of time sequence data are received; according to the inter-frame pose transformation matrix, carrying out occupied grid labeling on a static object in the time sequence data, and generating a static labeling result; tracking the position of the detection frame in each frame of time sequence data in real time according to the detection frame tracking identifier, and constructing a motion track of a target to which each detection frame belongs; in each frame of time sequence data, carrying out occupied grid labeling on the region where each motion track is located, and generating a motion labeling result; and fusing the static labeling result and the motion labeling result to generate an occupied grid labeling result corresponding to the time sequence data. Therefore, the occupancy grid label of the static object is propagated in combination with the inter-frame pose transformation matrix, and meanwhile, by fusing the occupancy grid label of the static object and the occupancy grid label of the motion trail, the requirements of the occupancy grid label for efficiency, precision and generalization are effectively met.

Provided is a driving assistance device that is safe and convenient in a situation where reverse playback cannot be performed in passing each other on narrow paths or the like. Driving operation of driver and surrounding obstacle information are stored at forward movement. At this time, the information of the front sensor (or the front camera) and the information of the rear sensor are integrated to determine and store the object type (stationary object, moving object). After the backward movement assistance is started, the surrounding obstacles of the rear sensor are collated with the stored surrounding obstacles, and execution of the backward movement assistance based on the stored driving operation is determined according to the collation result.

A method and device for vehicle camera autocalibration during vehicle travel for driver assistance systems and automated driving. A vehicle camera images a region of vehicle surroundings through a window. The method includes: providing a vehicle camera projection model including multiple extrinsic parameters, at least one intrinsic vehicle camera parameter and at least one window parameter; capturing a sequence of camera images during vehicle cornering; determining a curve type during the cornering; estimating the parameters using pixels in the sequence of images of stationary objects in the vehicle surroundings, the current vehicle movement, and the determined curve type, by minimizing an error function indicating the deviation between pixels which correspond to stationary objects in the vehicle surroundings and which are established from the sequence of images and pixels of the stationary objects which are projected by the projection model; and outputting at least one of the estimated parameters.

Methods and apparatus for monitoring user performance in launching objects at sporting events are described. A described method includes capturing, with a camera on glasses worn by a player participating in a sporting event, a plurality of two-dimensional (2-D) images of an object launched by a player participating in the sporting event. The launched object is identified and tracked with the camera for which an orientation is determined using an accelerometer. Based on the tracking, a position of the launched object at a point along a trajectory relative to a stationary object is determined, and an output indicative of user performance is provided based on the determined position of the launched object.

A vehicle travel control device (10) for controlling the travel of an own vehicle based on a predicted route which is a future travel route of the own vehicle, the device comprising: Object detection means (11, 12) for detecting the position of a stationary object located on the roadway or along the side of the roadway on which the host vehicle is traveling; Position storage means (25) for time-serially storing a position of a preceding vehicle, which is a position of the preceding vehicle traveling ahead of the host vehicle; Movement trajectory determining means (20) for comparing a movement locus of another vehicle, which is the movement trajectory of the position of the preceding vehicle stored in the position storing means, with the position of the fixed stationary object detected by the object detecting means to determine whether or not the movement locus of the other vehicle lies along the roadway; and Course calculation means (20) for validating the movement locus of the other vehicle when the movement locus of the other vehicle has been determined by the movement trajectory determination means to be along the road course, for invalidating the movement locus of the other vehicle when it is determined that it is not along the road course, and for calculating the predicted route based on the validated movement locus of the other vehicle.

Provided is a steering assist apparatus configured to perform a steering assist control for changing a steering angle of a vehicle in such a manner that the vehicle moves along a target path; determine whether a newly-detected object is a stationary object or a moving object; cancel the steering assist control and inform a driver that the steering assist control is cancelled when the newly-detected object is the stationary object and a cancel condition is satisfied; pause the steering assist control and inform the driver that the steering assist control is paused when the newly-detected object is the moving object and a pause condition is satisfied; and resume the steering assist control when a resume condition is satisfied.

A method of headlight evaluation can include receiving from a camera mounted on a vehicle, one or more images that include at least a portion of an illumination pattern projected by a headlight of the vehicle upon a surface of an object. The object can be a stationary object or a moving object such as, for example, a traffic sign or another vehicle. The surface can be a front portion of the traffic sign or a rear vertical surface of the other vehicle. The illumination pattern may be evaluated based on a positional relationship of the camera, the headlight, and the surface of the object. A headlight position status and / or a headlight orientation status can be output based on evaluating the illumination pattern.

To provide a technique that improves estimation accuracy of an error in an azimuth angle in a radar device.SOLUTION: A signal processing unit 7 includes an object detection unit 31, a vehicle speed detection unit 33, a stationary object determination unit 35, an azimuth error estimation unit 37 and an azimuth error offset estimation unit 39. The azimuth error estimation unit 37 estimates an angle error for each azimuth angle of an object detected by the object detection unit 31 by utilizing dependency of a relative speed on the azimuth angle for the stationary object. The azimuth error offset estimation unit 39 estimates an azimuth error offset which represents a value corresponding to an axis deviation angle of the radar device on the basis of the relative speed and azimuth angle of the stationary object. The stationary object determination unit 35 changes a determination condition for the stationary object according to the azimuth error offset, and the azimuth error estimation unit 37 estimates the angle error for each azimuth angle on the basis of the changed determination condition for the stationary object.SELECTED DRAWING: Figure 3

An impact monitoring system includes multiple sensor nodes including multiple stationary sensor nodes affixed to stationary objects in an environment, the multiple stationary sensor nodes including a first stationary sensor node affixed to a first stationary object; and one or more mobile sensor nodes affixed to mobile objects in the environment, the one or more mobile sensor nodes including a second mobile sensor node affixed to a second mobile object; and a monitor configured to wirelessly receive first data characterizing an impact event experienced by the first stationary sensor node and second data characterizing the impact event experienced by the second mobile sensor node, and to identify that the second mobile object impacted the first stationary object based at least in part on the first data and the second data.

An apparatus for winding at least one cable includes a cover, a top portion attached to the cover, and a base attached to the top portion. A surface of the base is configured to be attached to a stationary object. The top portion includes a sloped surface configured to receive the at least one cable, such that the at least one cable remains detangled and is externally invisible when is fully wound around the sloped surface.

Methods and systems are disclosed for employing an ultrasonic sensor to estimate a range for a moving object. At least one processor separates returned signals received by an ultrasonic transducer into a stationary object signal and a moving object signal. A gain is determined based at least in part on the stationary object signal. The stationary object signal is combined with the moving object signal using the gain and then filtered. The range for the moving object is estimated using the filtered combined stationary and moving object signal.

A driver assist apparatus includes one or more processors configured to collectively provide instructions of settings with group, the settings being set to driver assist functions included in the group, and the group being configured so that the driver assist function of a vehicle is allowed to be added to or deleted from the group, wherein a plurality of the driver assist functions included in the group, to which the instructions are provided, is a driver assist function group including at least a function concerned with alert in a case where the vehicle approaches an obstacle and a function concerned with detection of a stationary object around when parking.

To provide a radar device with which it is possible to calculate azimuth errors with high accuracy.SOLUTION: A radar device is mounted to a mobile body 80, and comprises a detection unit 410, a speed acquisition unit 411, a tracking unit 413, a stationary object determination unit 414, a distance acquisition unit 415, an assumed angle calculation unit 416, and an error calculation unit 417. The tracking unit acquires the time sequence of object information corresponding to at least one object which is determined to be the same as a first object. The distance acquisition unit acquires a first distance which was acquired when a vehicle passed through the side of the first body out of the acquired time sequence of object information, when it is determined that the first object is a stationary object. The assumed angle calculation unit calculates an assumed angle on the basis of the acquired first distance and a second distance detected at this round of time. The error calculation unit calculates the difference between the calculated assumed angle and a first azimuth angle as the amount of an azimuth error at the first azimuth angle detected at this round of time.SELECTED DRAWING: Figure 9A

The invention discloses an active sonar target identification method based on message passing multi-hypothesis tracking, and belongs to the technical field of underwater target detection. The method comprises the following steps: firstly, processing single-cycle sonar data by using adaptive constant false alarm detection, obtaining observation points, and forming an effective observation set through hierarchical clustering; thirdly, extrapolating the existing target, calculating the association probability of the existing target and the current observation by adopting a message passing method, and generating a plurality of groups of association hypotheses; then, the target state is corrected through Kalman filtering, target rejection and new management are executed, and a high-probability hypothesis is reserved; and finally, estimating the motion speed based on the target multi-period position sequence, and distinguishing a static object from a suspicious motion target according to a speed threshold. Through the multi-hypothesis tracking and probability message passing mechanism, clutter interference and static target influence in a complex underwater environment are effectively overcome, and the stability of target tracking, the accuracy of speed estimation and the overall reliability of system identification are remarkably improved.

An outside sensing information processing device for suppressing adverse influence on warning of an advanced vehicle safety system. The vehicle safety system receives position information of an object detected by another vehicle or a road, the positions of feature points of a stationary object, and configuration information of an environmental map. When the system receives the information, the position of the object on the environmental map is calculated. Another vehicle also transmits position information of itself. The present vehicle checks an error of the position information of the vehicle detected by the other vehicle from the position information of the another vehicle and the relation of the position of a feature point detected by the another vehicle and the position of the feature point detected by the present vehicle. In the case where the error is large or unstable, use of the position information from the other vehicle is avoided.

This document describes techniques and systems for stationary object detection and classification based on low-level radar data. Raw electromagnetic signals reflected off stationary objects and received by a radar system may be preprocessed to produce low-level spectrum data in the form of range-Doppler maps that retain all or nearly all the data present in the raw electromagnetic signals. The preprocessing may also filter non-stationary range-Doppler bins. The remaining low-level spectrum data represents stationary objects present in a field-of-view (FOV) of the radar system. The low-level spectrum data representing stationary objects can be fed to an end-to-end deep convolutional detection and classification network that is trained to classify and provide object bounding boxes for the stationary objects. The outputted classifications and bounding boxes related to the stationary objects may be provided to other driving systems to improve their functionality resulting in a safer driving experience.

The present application relates to an apparatus for determining the ego-motion of a radar apparatus, the apparatus configured to: process radar-point-cloud information comprising a plurality of points by neural network models, the processing comprising: pointwise mapping the features thereof to a greater number of mapped-features to provide mapped-radar-point-cloud information, determining a global feature vector indicative of characteristics of the mapped-radar-point-cloud information, generating a feature matrix wherein each point therein is characterized by a feature-set based on a combination of the features, the mapped-features and the global feature vector, determining a pointwise-weight representing a likelihood that the point represents a stationary object in the space, a pointwise-offset comprising a correction to be applied to the Doppler velocity measurement to at least reduce the Doppler velocity measurement for points having a greater than expected Doppler velocity, and providing an estimate of the motion of the radar apparatus.

The invention relates to a method for determining a position of a stationary object (1), comprising the steps of: detecting (S1) by a plurality of vehicles (2) a distance of the object (1) from the respective vehicle (2); determining (S2) a distance between the detected stationary object (1) and a building (3) running along the road; determining (S3) an absolute longitudinal position component of the stationary object (1) along the direction of extension of the road and a relative lateral position component of the stationary object (1), wherein the absolute longitudinal position component is determined from a respective geodetic position of a vehicle (2), and wherein the determined distance of the stationary object (1) from the building (3) is used as the lateral position component.

The utility model discloses intelligent sensing radar monitoring equipment, and relates to the technical field of monitoring equipment, the radar monitoring equipment comprises a shell, and the interior of the shell is hollow; the monitoring camera is fixedly arranged on the shell and is used for monitoring a preset monitoring area; the circuit board is fixedly arranged in the shell, and a radar sensing device and a main control device are arranged on the circuit board; the radar sensing device is used for sensing a moving object or a static object in the predetermined monitoring area, and the main control device is connected with the monitoring camera and the radar sensing device through different interfaces and is used for sending the moving object or the static object to the radar sensing device under the condition that the radar sensing device senses an object of a preset type. And controlling the monitoring camera to start video recording. The utility model aims to improve the sensing accuracy of the sensing monitoring equipment.

The embodiment of the invention provides a road curvature determination method and device, electronic equipment and a readable storage medium, and relates to the field of data processing, and the method comprises the steps: obtaining environment data around a vehicle; wherein the environment data comprises environment point cloud data and / or environment image data; performing target object detection based on the environment data to obtain a target object detection result; establishing a road geometric model by adopting a target object detection result; a road curvature is determined based on the road geometry model. According to the method, the road geometric model can be established according to the static objects above the ground, the road curvature can be predicted according to the road geometric model, and the static objects above the ground are generally not easy to shield, so that the detection accuracy of the road curvature can be improved under the condition that accurate road surface information is difficult to obtain.

This route acquisition system includes: a plurality of marks for identifying installation positions, the plurality of marks being provided at different positions in a travel passage or on a stationary object in the vicinity of the travel passage; a sensor that is mounted on a moving body and reads the marks; and a route acquisition device that, on the basis of the result of reading by the sensor, detects a passing position and a passing time of the moving body and acquires the travel route of the moving body.

To provide an information processing device capable of suitably mediating the communication between an occupant of a mobile body and a user existing outside the mobile body.SOLUTION: An in-vehicle device 1, an off-vehicle terminal 2, or a server device 5 is an information processing device used in a system mediating the communication between an occupant of a vehicle being a mobile body and a user existing outside the vehicle. The information processing device comprises acquisition means, processing means, and display control means. The acquisition means acquires a peripheral captured image obtained by capturing the periphery of the vehicle from the vehicle. The processing means subjects a predetermined non-stationary object to image processing among the objects existing in the peripheral captured image. The display control means displays the peripheral captured image having been subjected to image processing on the terminal device used by the user.SELECTED DRAWING: Figure 8

A radar system includes a processor and a non-transitory computer-readable medium storing machine instructions. The processor obtains an ego velocity Vego of a radar system, a range R of an object in an environment of the radar system, and a radial velocity Vr of the object. The processor determines a simplified two-dimensional (2D) angular search grid and performs a grid-based direction-of-arrival algorithm using the simplified 2D angular search grid. In some implementations, the processor determines a ring of possible positions for a stationary object based on the ego velocity Vego, the range R, and the radial velocity Vr, and includes the ring of possible positions in the simplified 2D angular search grid. In some implementations, the processor determines an arc of possible positions for a moving object based on the range R, and includes the arc of possible positions in the simplified 2D angular search grid.

A computer-implemented method is provided for estimating velocity of a moving object. The method includes receiving an image, which includes a first strip generated by a first sensor and a second strip generated by a second sensor, and recognizing a moving object in the first strip of the image. The method also includes selecting a plurality of stationary objects that are captured with the moving object in the first strip of the image, while excluding stationary object(s) in the second strip of the image, wherein the plurality of stationary objects are non-moving features. The method further includes combining misregistration values for the plurality of stationary objects in the first strip of the image and calculating a velocity of the moving object, based on a raw velocity of the moving object and the combined misregistration values.

A method for moving a vehicle to a component of an object at a distance therefrom, the vehicle having a navigation module which has a camera and an evaluation electronics, and an identification element is attached to the object in a predetermined position in such a way that it is recognized by the camera in a far range (Dmax) of the vehicle from the object, and a reverse driving line of the vehicle is calculated by the evaluation electronics from the perspective position of the camera in relation to the identification element. The method improves the approach of a vehicle to a stationary object. In a start position (S) of the vehicle, the navigation module generates a static object coordinate system (KO) and a reverse driving line is calculated from the start position (S) to a pre-positioning point (SVi, SVii, SViii).

A motorized turf trimming system with integrated control for a carrier vehicle and rotary trimming attachments is disclosed. The system can be configured for automatically trimming around stationary objects such as trees, signposts, guard rail posts, barrier posts, light bases, etc.

Example embodiments of the present disclosure relate to apparatuses, methods, and a computer readable storage medium for adjustment for sensing coverage area. In the solution, an apparatus including a sensing management function may determine that a sensing coverage area of a sensing system is to be adjusted to sense a moving target, and the apparatus may transmit a sensing static power adjustment indication to a sensing transition device, where the sensing static power adjustment indication indicates to the sensing transition device to adjust static power of signals reflected from one or more stationary objects in the sensing coverage area. The sensing transition device may adjust static power of signals reflected from one or more stationary objects in a sensing coverage area based on the sensing static power adjustment indication. Accordingly, the sensing coverage area may be adjusted as the static power adjustment.