182 results about "Sensor observation" patented technology

A transparent, capacitive sensing system particularly well suited for input to electronic devices is described. The sensing system can be used to emulate physical buttons or slider switches that are either displayed on an active display device or printed on an underlying surface. The capacitive sensor can further be used as an input device for a graphical user interface, especially if overlaid on top of an active display device like an LCD screen to sense finger position (X/Y position) and contact area (Z) over the display. In addition, the sensor can be made with flexible material for touch sensing on a three-dimensional surface. Because the sensor is substantially transparent, the underlying surface can be viewed through the sensor. This allows the underlying area to be used for alternative applications that may not necessarily be related to the sensing system. Examples include advertising, an additional user interface display, or apparatus such as a camera or a biometric security device.

Aspects of the present disclosure relate generally to modeling a vehicle's view of its environment. This view need not include what objects or features the vehicle is actually seeing, but rather those areas that the vehicle is able to observe using its sensors if the sensors were completely un-occluded. For example, for each of a plurality of sensors of the object detection component, a computer may an individual 3D model of that sensor's field of view. Weather information is received and used to adjust one or more of the models. After this adjusting, the models may be aggregated into a comprehensive 3D model. The comprehensive model may be combined with detailed map information indicating the probability of detecting objects at different locations. A model of the vehicle's environment may be computed based on the combined comprehensive 3D model and detailed map information and may be used to maneuver the vehicle.

A vehicle detection and classification sensor provides accurate 3D profiling and classification of highway vehicles for speeds up to 100 mph. A scanning time-of-flight laser rangefinder is used to measure the distance to the highway from a fixed point above the road surface and then measure the distance to the surfaces of any vehicle that is viewed by the sensor. A rotating polygon scans a beam laser into two beams projected across the road surface at a fixed angle between them. The beam is pulsed at a high repetition rate for determining vehicle speeds with a high accuracy and uses the calculated speed and consecutive range measurements as the vehicle moves past the sensor to develop a three-dimensional profile of the vehicle. An algorithm is applied to the three-dimensional profile for providing a vehicle-classification.

A platform residing viewing sensor and a pointing system/weapon. An operator system is remotely monitoring the scene on a display as viewed by the viewing sensor such that an operator system can gaze, acquire and track targets by scanning the scene with eyes and locking the eyesight onto a selected target and track the target with the eyes. The system further includes a dual camera sensor that follows and monitors the operator system's eyes motion so that the operator system can simultaneously monitor the external viewing sensor's scene, locking and tracking some selected target. The display coordinates of the selected target are utilized to point the pointing system/weapon on the external platform so that the operator system can fire at the target as desired. The problem is thus summarized as one of controlling the weapon pointing, movement and firing on a target that has been selected and is tracked by the eyes of an operator system viewing a display.

The invention relates to a visual inertial navigation SLAM method based on ground plane hypothesis. According to the method, feature points are extracted from an image to perform IMU pre-integration,a camera projection model is established, and camera internal parameter calibration and external parameter calibration between an IMU and a camera are performed; a system is initialized, a visually observed point cloud and a camera pose are aligned to the IMU pre-integration, and a ground equation and the camera pose are restored; the ground is initialized to obtain a ground equation, the ground equation under the current camera pose is determined and back projected to an image coordinate system, and a more accurate ground region is acquired; and based on state estimation, all sensor observation models are derived, camera observation, IMU observation and ground feature observation are fused to do state estimation, a graph optimization model is used to do state estimation, and a sparse graph optimization and gradient descent method is used to realize overall optimization. Compared with previous algorithms, the precision of the method is greatly improved, estimation of the camera pose can be limited globally, and therefore accuracy is greatly improved.

An apparatus and method for providing a context-aware service are provided. The apparatus includes a context-aware service object (CAS) management module managing information on a CAS and a context defined by the CAS, a sensor management module managing information on a sensor and requesting the sensor to observe knowledge, and a context management module informing the CAS management module of a CAS defining a context provided by the CAS management module when observed knowledge satisfies the context defined by the CAS, wherein upon being informed of the CAS by the context management module, the CAS management module requests the CAS to provide a service.

A vehicle service system and method to determine spatial parameters of a vehicle, employing a display system under processor control, to display or project visible indicia onto surfaces in proximity to a vehicle undergoing a safety system service or inspection identifying one or more locations, relative to the determined vehicle centerline or thrust line, at which a calibration fixture, optical target, or simulated test drive imagery is visible for observation by a sensor onboard the vehicle.

The need for geo-registered features is avoided by a system for estimating a motion of a first sensor during a time interval. The system has a second sensor where the first sensor and the second sensor sense the same geo-location during the time interval. The first sensor computes a first target location error from sensing the geo-location. The second sensor also computes a second target location error from sensing the geo-location. A data link interconnects the first sensor and the second sensor, the data link transmitting the second target location error computed by the second sensor to the first sensor during the time interval. A processor at the first sensor combines the first target location error and the second target location error in a first sensor observation model, where the sensor observation model is descriptive of the motion of the first sensor. The observation model is used with a Kalman filter to update the position of the first sensor. This combination of the first sensor observation model and the second sensor observation model generates a more accurate target location error at the first sensor. The principle is extended to a plurality of platforms.

A system for providing integrated detection and deterrence against an unmanned vehicle including but not limited to aerial and similar technology unmanned systems using a detection element, a tracking element, an identification element and an interdiction or deterrent element. Elements contain sensors that observe real time quantifiable data regarding the object of interest to create an assessment of the object of interests risk or threat to a protected area of interest. This assessment is based on the application of machine learning and data mining techniques and protocols to the set of data related to the object of interest. This data product is available to third parties via a set of defined interface protocols and available API. The deterrent element, using other machine learning or artificially intelligent algorithms, selects from a variable menu of possible deterrent actions not limited to those actions currently included in this embodiment, but includes those actions available from third parties such as specialized “hunter drones”. Though designed for autonomous action, a Human in the Loop may override the automated system solutions.

An apparatus for, and method of, imaging printed and electronic codes associated with transactions or objects to be processed, support a window on a housing, illuminate the codes through the window with illumination light from an energizable illumination system, capture return illumination light from the illuminated codes through the window with an array of light sensors looking at a field of view of a solid-state, exposable imager, and process the captured return illumination light. A printed code is read by exposing the imager for a first exposure time and by also energizing the illumination system during the first exposure time. An electronic code is read by exposing the imager for a second exposure time that is longer than the first exposure time and by also deenergizing the illumination system during the second exposure time.

The invention discloses a microminiature unmanned aerial vehicle controlling method having a network random delay problem. The microminiature unmanned aerial vehicle controlling method belongs to the technical field of flight control, and comprises the following steps of: establishing an unmanned aerial vehicle system model and designing a control law; analyzing random robustness of a system having the network random delay problem; determining a network updating cycle, an optimization index and index weight; designing a robustness control law by a random robustness designing method; and implementing closed loop six-freedom degree nonlinearity Monte Carlo simulation verification, wherein in the step 2, the network random delay problem includes sensor observation delay, executor control delay and hybrid delay with superposition of observation and control. According to the controlling method, shortcomings of high requirement on communication quality and poor robustness of a conventional linear secondary regulator are overcome; a controlling method based on robustness analysis and design is introduced to control the unmanned aerial vehicle based on a network, thereby reducing a requirement on updating rate of a formation wireless data chain of the unmanned aerial vehicle, and enhancing robustness of formation of the unmanned aerial vehicle.

A linear actuator is disclosed, that comprises a stator containing more than one coil, a mover containing more than one magnet, each said magnet separated from the adjacent magnet by a spacer, a power supply operable to provide current to said coils of said stator, at least one magnetic flux sensor, and a controller operable to control the relative motion between said stator and said mover, the controller comprising a module to measure the magnetic flux observed by the sensor and use that as feedback to control the motion of the mover relative to the stator. In a preferred embodiment, this linear actuator is used in a sexual appliance with user control over the linear actuator motion profiles.

The invention relates to a multifunctional photoelectric detection instrument and a target position observing and determining method implemented by the same. The multifunctional photoelectric detection instrument comprises refrigerating infrared sensors, a laser range finder, a visible light channel, a GPS (global positioning system) module, a magnetic compass, a comprehensive information processing unit, a power module and a control panel, the comprehensive information processing unit is respectively connected with the refrigerating infrared sensors, the laser range finder, the GPS module, the magnetic compass, the display module and the control panel, and the visible light channel is connected onto the laser range finder. The method includes methods for observing a target via the visible light channel, a method for observing the target and determining target direction via the refrigerating infrared sensor and a method for automatically solving coordinates of the target position. The multifunctional photoelectric detection instrument and the target position observing and determining method have the advantages that the target is detected and positioned by a single person, and images, the direction, the distance and position information of the target are accurately provided in real time. Besides, the various sensors are integrated, a miniaturization design is adopted, portability is high, and single-person detection capacity and information acquisition capacity are improved.

Performance prediction systems and method of an Internet of Things (IoT) platform and applications includes obtaining input(s) comprising one of (i) user requests and (ii) sensor observations from sensor(s); invoking Application Programming Interface (APIs) of the platform based on input(s); identifying open flow (OF) and closed flow (CF) requests of system(s) connected to the platform; identifying workload characteristics of the OF and CF requests to obtain segregated OF and segregated CF requests, and a combination of open and closed flow requests; executing performance tests with the APIs based on the workload characteristics; measuring resource utilization of the system(s) and computing service demands of resource(s) from measured utilization, and user requests processed by the platform per unit time; executing the performance tests with the invoked APIs based on volume of workload characteristics pertaining to the application(s); and predicting, using queuing network, performance of the application(s) for the volume of workload characteristics.

Devices, systems and methods for detecting in vivo pathology are provided. An in vivo sensing device comprises a reacting layer with at least one type of binding agent attached thereon, a sensor configured for sensing an optical change occurring on the reacting substrate, and at least one illumination source. In-vivo fluids are in constant contact with the reacting substrate so that in vivo marker indicating pathology may bind to the binding agent attached onto the reacting layer and may be viewed by the sensor.

The invention discloses a pseudo-measurement-based asynchronous track fusion algorithm with a feedback maneuvering target. Firstly, input interaction is carried out on a model set, and the filtering initial value of each model is calculated according to the model probability and the model transfer probability; secondly, a fusion center calculates one-step prediction values on the basis of the Kalman filtering algorithm, after new sensor measurement information in the filtering period is obtained, the one-step prediction values are distributed in a time shaft sequence, recurrence is conducted on a fusion moment, information such as sensor observation matrixes, noise and model prediction are added, and asynchronous track fusion is conducted; thirdly, secondary filtering is carried out for calculating model output, output interaction is performed in the fusion center to obtain a fusion center estimated value and an estimation error matrix, and the fusion center estimated value and the estimation error matrix are fed back to a sensor according with feedback conditions. The overall precision of the algorithm is improved by introducing a fusion structure with feedback so that a better effect can be achieved in multi-sensor maneuvering target tracking.

A vehicle state quantity prediction apparatus has sensors such as a GPS receiver that observe prescribed state quantities representing a movement state of a vehicle and a Kalman filter that inputs the state quantities observed by the sensors into a model of the movement state of the vehicle to predict a state quantity including the prescribed state quantities representing a movement of the vehicle. The reliability of the prescribed state quantities observed by the sensors is evaluated, and the degree to which the prescribed state quantities are reflected in the Kalman filter is set based on the evaluated reliability.

An active or passive sensor observes a region, and generates evidence of the type of target or object viewed. The evidence is processed to determine the prior probability that the object is of a particular type. The prior probability so determined is thresholded to produce an indication of the presence of multiple targets or objects in a range bin, suggestive of shadowing of a target.

The invention discloses a particle filtering-based SLAM optimization method and relates to robot simultaneous positioning and map construction. The problem of failure task execution of a robot causedby noise interference received by the robot during task execution is solved. The particle filtering-based SLAM optimization method comprises the following steps of 1, defining a variable; 2, buildinga probability model according to the variable, wherein the probability model building comprises motion probability model building, sensor observation model building and grid map model building; and 3,optimizing an SLAM according to the particle filtering and probability model, wherein the step of optimizing the SLAM comprises the steps of automatically determining a position by the robot after the map is updated each time, and the automatic position determination of the robot comprises initialization, sampling, scanning, matching, weight calculation and sampling again. The particle filtering-based SLAM optimization method has the advantages that a true state of a target is obtained, and the failure task execution of the robot caused by noise interference received by the robot during taskexecution is prevented.