362 results about "Environmental sensing" patented technology

An Internet appliance, comprising, within a single housing, packet data network interfaces, adapted for communicating with the Internet and a local area network, at least one data interface selected from the group consisting of a universal serial bus, an IEEE-1394 interface, a voice telephony interface, an audio program interface, a video program interface, an audiovisual program interface, a camera interface, a physical security system interface, a wireless networking interface; a device control interface, smart home interface, an environmental sensing interface, and an environmental control interface, and a processor, for controlling a data transfer between the local area network and the Internet, and defining a markup language interface communicated through a packet data network interface, to control a data transfer or control a remote device.

Methods and apparatus for reactively controlling one or more user interfaces associated with a device based on sensed conditions in an environment associated with at least one of the user interfaces are provided. A method of controlling at least one user interface associated with a device includes sensing conditions in an environment which includes the at least one user interface of the device. Then, the method includes presenting data at the at least one user interface as a function of the sensed conditions. For example, the sensing step may include detecting a proximity of a user with respect to the user interface such that the presenting step includes presenting data at the user interface as a function of the detected proximity. The proximity of the user to the user interface may be measured as a distance value between the user and the user interface such that data is presented at the user interface in a different manner or mode based on the distance value. The methods and apparatus also provide for detecting the identity of the user.

The present invention relates to a pilotless automobile system and an automobile. The pilotless automobile system comprises an environmental sensing subsystem, a data fusion subsystem, a route planning and deciding subsystem and a travel control subsystem. Surrounding environment information including image information and three-dimensional coordinate information is fused through the data fusion subsystem, obstacle information, lane line information, traffic sign information and dynamic obstacle tracing information are extracted, and the recognition capability and recognition precision of the surrounding environment information are improved. The route planning and deciding subsystem is used for planning a travel route according to the information extracted by the data fusion subsystem and travel destination information, the travel control subsystem is used for generating a control instruction according to the travel route and controlling the pilotless automobile according to the control instruction, and a high-safety-performance pilotless function is fulfilled.

A roll stability control system (18) for an automotive vehicle (10) includes an external environment sensing system, such as a camera-based vision system, or a radar, lidar or sonar-based sensing system (43) that generates image, radar, lidar, and/or sonar-based signals. A controller (26) is coupled to the sensing system and generates dynamic vehicle characteristic signals in response to the image, radar, lidar, or sonar-based signals. The controller controls the rollover control system (18) in response to the dynamic vehicle control signal. The dynamic vehicle characteristics may include roll related angles, angular rates, and various vehicle velocities.

An electric street light controller apparatus and monitoring method allows automatic street light turn-on and turn-off characteristics to be field programmable using RFID technology, lamp current magnitude recording, auxiliary sensor input, diagnostic alarming and data storage for later retrieval in a remote electric street lighting monitoring system. The apparatus and method includes, from a remotely located exciter apparatus using an antenna to transmit a specific frequency and code key to the antenna of an electric street light control and monitoring apparatus associated with the electric street light allowing remote wireless field programming of turn-on fight levels, turn-off light levels, rate of change of light levels, specific turn-on, turn-off, and turn back on sequences during dark hours, and specific remote wireless sensors or internal sensor inputs useful for radiological, biological, chemical, or environmental sensing and alarming. Additionally the method and apparatus includes a method of providing automatic diagnostics for the street lamp bulb, starter and self diagnostics of the controller itself.

The invention discloses an automobile traveling control system and an automobile traveling control method and belongs to the technical field of automobiles. The automobile traveling control system comprises an acquiring unit, an environment sensing unit, a traveling parameter collecting unit, a planning and decision-making unit and a real-time control unit, the acquiring unit is used for acquiring a driving instruction, the environment sensing unit is used for sensing automobile traveling environment in real time and generating environment information, the environment information includes one or multiple of lane line position, target automobile information, current automobile pose and garage position information, the traveling parameter collecting unit is used for acquiring a current automobile traveling state and generating automobile traveling parameters, the automobile traveling parameters include one or multiple of current automobile speed, front wheel deflection angle and automobile traveling route, the planning and decision-making unit is used for generating a control instruction according to the environment information, the automobile traveling parameters and the driving instruction, and the real-time control unit is used for controlling automobile traveling according to the control instruction. The automobile traveling control system integrates functions of lane line maintaining, self-adpative cruising and automatic parking, so that functions of an intelligent automobile are further enriched.

The present invention discloses a driving behavior decision system of an automatic driving public traffic vehicle. The system comprises an external environment perception module, an information fusion processing module, a driving scene determination module and a driving behavior decision module. The external environment perception module comprises a vision sensor, a laser radar, a millimeter wave radar, a GPS location module and a high-precision map. The driving behavior decision module employs a limitation state machine model, and the driving behavior decision module employs a driving behavior determination decision model based on an ID3 decision tree; and the information fusion processing module performs fusion processing of the environment information sent by an external environment perception module and sends the information after fusion processing to the driving scene determination module and the driving behavior decision module. The driving behavior decision system of the automatic driving public traffic vehicle can improve the driving safety of the automatic driving public traffic vehicle and effectively reduce the probability of traffic accidents.

An apparatus for locating a golf ball during play of a golf game includes a golf ball having a passive transmitter and a mechanism for sensing environmental conditions positioned therein. The apparatus further includes a mechanism for determining and providing a location of the golf ball. A hand-held unit is further provided. The hand held unit includes a mechanism for enabling at least one of the passive transmitter and the environmental sensing mechanism contained within the golf ball. A receiver is contained within the hand-held unit for receiving a location signal from the determining and providing mechanisms. A mechanism positioned on the hand-held unit for indicating to a golfer the location of the golf ball. Upon the location being indicated, the environmental sensing mechanism is able to selectively determine conditions corresponding to the location and provide the conditions to the hand-held unit for further indication to golfer.

This invention relates to one mobile robot 3D sensor method, which comprises steps of environment information acquiring, environment information self adapting filter, environment coordinate exchanging and 3D sensing. This invention gets robot environment information through one sense platform composed of 2D laser radar, rotation bench and step motor. This invention also provides one dynamic self-adaptive filter to realize dynamic filter noise removing aim for environment information interference.

The invention provides a model ship based autonomous navigation control simulation system and method of an under-actuated unmanned ship. The whole system is arranged on a model ship, and the model ship is arranged in a simulated navigation channel; the system comprises an environment sensing sub system, a path programming sub system and a motion control sub system; the environment sensing sub system collects the navigation state of the model ship and simulates environment factor information; according to the navigation state of the model ship and the simulated environment factor information, the path programming sub system carries out navigation programming to obtain the tracking route, the set speed and the set course; and the motion control system combines a course tracking model, a path tracking model, the route deviation, the course deviation and the speed deviation to calculate the rudder angle and propeller rotating speed instruction needed in next navigation of the model ship and control a steering engine and a propeller. According to the invention, simulation experiments are carried out on the model ship, an instance is provided for operation and control experiments of large ships, important guarantee is provided for safe navigation of large ships in inland rivers, and the system reduces the difficult and cost of experiments of the large ships.

The invention belongs to the field of intelligent unmanned intelligent ships, and relates to an unmanned ship water surface target detection, identification and positioning method based on monocular camera and lidar information fusion. The detection, identification and positioning of a water surface target by an unmanned ship are influenced by distances and the fluctuation of the target, so that alidar and a monocular camera are integrated to accurately detect, identify and position the target within a sensing range. According to the method, acquired water surface target images are adopted totrain a neural network-based target detection and recognition model; the lidar employs a conditional removal filter and Euclidean clustering to obtain the position of the water surface target in a world coordinate system; and finally, a camera image information and lidar information fusion method is designed, and therefore, the method is highly robust to uncertain factors. With the method adopted, the unmanned ship is capable of accurately detecting, identifying and positioning the water surface target; and good environment perception can be realized for the target tracking, path planning andautonomous navigation of the unmanned ship. The method has a broad application prospect.

The invention provides an automatic driving system based on a pure electric logistics vehicle and a control method thereof. The system comprises an automatic driving control system, a human-computer interaction system, an automatic driving system gateway and an execution system. The method comprises the steps that step one, an environment perception system acquires the surrounding environment dataof the vehicle and performs fusion, perceives the surrounding obstacle information and passable area information and also acquires the high precision position information of the vehicle and the roadinformation and then generates a driving situation map according to the primary planning path result planned by the lane level navigation system; step two, an intelligent decision system performs secondary planning of the local driving route in real time according to the driving situation map generated by the environment perception system and decomposes the secondary planning result into the transverse control instruction and the longitudinal control instruction; and step three, the execution system receives the executes the transverse control instruction and the longitudinal control instruction from the intelligent decision system so as to complete full-automatic driving. Automatic driving can be realized and the intelligent level of the complete vehicle can be enhanced.

The invention discloses a small portable automatic gravity center control vehicle, and relates to a small highly intelligentized portable automatic gravity center control vehicle. The whole vehicle has the characteristics of small volume and light weight; and due to a folded structure, a handle can be folded into a lifting handle, the vehicle can be carried by people and parking space and the possibility that the vehicle is stolen are reduced. The running of the vehicle is controlled by detecting the gravity center shift state of a driver and the vehicle; and the vehicle is flexible to run even in a narrow space. The vehicle has a ladder chassis structure, so driving is more comfortable and safer; and the vehicle is safe, stable and comfortable to run by adopting an intelligent control mode and environmental perception technology.

A network driving environment integrated perception model based on a convolutional and hollow convolutional structure simultaneously realizes object detection and semantic segmentation. A video imageof a road environment is shot through a forward-looking camera system mounted on a vehicle. The residual network model is used to get the bottom feature map of the image. The converged network is designed, which includes two sub-modules: object detection and semantic segmentation. The two modules share the bottom feature map. Among them, the object detection module is responsible for predicting the confidence level of the object frame and the category, and the semantic segmentation module is responsible for predicting the pixel level of each category. The appropriate loss function is selectedfor each of the two modules, and the perceptual model tends to converge in both modules after alternate training. Finally, the joint loss function is used to train the two modules simultaneously to get the final perceptual model. The model can simultaneously complete object detection and semantic segmentation with small computation amount, and the perceptual model uses a large amount of data of object detection to assist the semantic segmentation module to learn the image distribution law.

The invention discloses an automatic drive robot used in vehicle road tests. The automatic drive robot comprises an execution unit, an environment perception unit, a vehicle running state detection unit, a user interaction unit and a control unit, wherein the environment perception unit is used for detecting the running environment of a vehicle to be tested; the vehicle running state detection unit is used for detecting the running state of the vehicle in real time; the user interaction unit is used for setting correlates of the tests before the road tests are conducted; the control unit comprises a drive control unit and a safety control unit; the drive control unit is used for driving the execution unit to control the running of the vehicle, so that the vehicle to be tested can be tested according to test items preset by a user; and the safety control unit is used for detecting environmental sensor information, vehicle breakdown information and vehicle motion state information, so as to timely find out safety problems and realize safety control over the vehicle. The automatic drive robot can replace manual drive to complete various automobile road tests, and has the advantages of accurate control, long continuous working period, high test efficiency and good repeatability.

The invention discloses a system and a method for controlling an underground coal mine rescue robot, and relates to the technical field of robot control. The system comprises a communication module, an environment perception module, a self perception module, a barrier avoidance module, a motor drive module, an autonomous navigation module, a data acquisition control module, a visual perception module, a remote monitoring module and an automatic cooling module. The system is provided with a remote monitoring mode and an autonomous navigation mode. The distributed control of a dual-layer network framework is adopted, so that the system is flexible in structure; the number of rescue robots is conveniently adjusted due to the flexibility of combination of optical fiber communication with wireless communication, so that the rescue task can be performed by one or more robots; the running safety of the robot is improved and the intelligent level of the robot is increased due to the remote monitoring and autonomous navigation functions; and the robot control system is guaranteed to run reliably due to the automatic cooling system.

The invention discloses a panoramic inertial navigation SLAM method based on multiple key frames. The method comprises the following steps of: building a multi-target panoramic visual model, combiningan inertial navigation unit and tightly coupling a fusion visual feature, and realizing a high-precision positioning and a scene map through multiple key frames nonlinear optimization. The method isused for solving the problems in the prior art of the insufficient information acquisition by environment-aware methods and the uncertainty of fast rotation, and limited view limitation, illuminationinfluence and visual degradation of an existing visual SLAM method, providing an effective automation method for a robot environment modeling and positioning navigation in a complex environment such as strong light/weak texture/motion blur, improving the accuracy and the robustness of the method, so that ensuring the sufficiency of autonomous navigation of the robot, and considering the calculation efficiency, can achieve the real-time performance of the visual SLAM method.

The invention discloses a front barrier detection system and method for an unmanned driving automobile. The system comprises a millimeter wave radar, a vision camera and an information processing system, wherein the millimeter wave radar is connected with an industrial control computer through a CAN bus, the vision camera is connected with the industrial control computer through a 1394 interface,the information processing system comprises functions as follows, space coordinate calibration and time synchronization for the millimeter wave radar and the vision camera are carried out, millimeterwave radar data is acquired and resolved, a data processing algorithm based on Kalman filtering is utilized to analyze the barrier information, false targets are eliminated to determine effective targets, the information of the vision camera is acquired, an image processing algorithm is utilized to detect barriers, the barrier information identified by the millimeter wave radar is compared with the barrier information identified by the vision camera, and the barriers detected by the two types of sensors are taken as the reference to establish an accurate grid map. The method is advantaged in that accuracy is high, cost is relatively low, and practicality of an unmanned automobile environment sensing system can be effectively improved.

Provided is a vehicle surroundings awareness support device capable of providing a prompt for a driver to intuitively direct their attention, without the driver feeling hassled. Captured images comprising a plurality of frames taken sequentially by an onboard camera for imaging the surroundings of the vehicle are received; an optical flow is computed on the basis of feature points contained in the plurality of frames imaged at different times; moving objects in the surroundings of the vehicle are detected on the basis of the optical flow; and a display for showing movement trajectories for the moving objects is superimposed on the captured images on the basis of the optical flow.

The present invention discloses a test method and device applied to a driverless vehicle. According to one embodiment of the invention, the method includes the following steps that: a terminal sends location information to a driverless vehicle in a test site; when a location in a real driving environment, which is corresponding to the driverless vehicle, is a preset location, environment sensing information of a preset event corresponding to the preset location is sent to the driverless vehicle; and the output information of a functional module is obtained, and whether the functional module is normal is judged based on the result of the comparison of the output information and preset information corresponding to the functional module. With the test method and device of the invention adopted, whether the functional modules of the driverless vehicle during various kinds of events in the real driving environment are normal can be tested, and the safety risks of tests in the real driving environment can be avoided.

The present invention provides an intelligent vehicle multi-laser radar fusion recognition method based on target features, relates to the field of intelligent vehicle environment perception. The method comprises the following steps: 1, performing pretreatment of collected data, extracting target geometric features and determining the type of the target; 2, calculating the geometry conformability degree of the target, and performing target matching according to the geometry conformability degree; 3, fusing the target geometric features through adoption of a method based on distance weight fusion; 4, tracking the target through adoption of a multi-feature target tracking method, and obtaining the relative movement features of the target; 5, obtaining the absolute movement features of the target through adoption of the vehicle movement features collected by a global positioning system; 6, correcting the type of the target according to the absolute movement features of the target and a target feature model; and 7, performing rasterization of the target features, and performing grid expression. The intelligent vehicle multi-laser radar fusion recognition method based on target features is configured to fuse the multi-laser radar through adoption of target features to improve the target recognition capability of a system and enhance the safety of a vehicle in the driving process.

The present invention provides an apparatus with surface information displaying, wherein a skin unit comprising a flexible display is covered on the surface of a moving object of the apparatus such that the surface of the apparatus is capable of displaying the information such us color, pattern or text immediately by software control. Meanwhile, the flexible display further has a layer of tactile sensing unit for detecting input of interacting signal. In addition, the moving object further integrates an environmental sensing device, an information identifying device or a combination of both and uses the environmental status, text information or audio/video, which are generated from the environmental sensing device or information identifying device, as an input signal through cable or wireless technology so as to generate responsive action through the flexible display or mechanism of the apparatus so that interactivities of the apparatus can be increased.

The invention relates to a test system for an automatic driving vehicle. A real vehicle data collection module is used for collecting control data; a test bench is used for generating a reaction forceaccording to the control data and scene information and obtaining state data of an automatic driving vehicle according to the reaction force; a scene model establishing module is used for establishing a traffic scene model, a traffic flow model, an automatic driving vehicle dynamics model and an environment perception sensor model and obtaining position data of the automatic driving vehicle; andan evaluation module is used for calculating a return value for evaluating the running state of the automatic driving vehicle according to the position data and the state data. By combining the test bench with a scene model comprising traffic flow data, the environment recognition capability, the dangerous condition recognition response time and the processing mode of the automatic driving vehiclecan be more truly tested, and the safety and the stability of the autonomous recognition capability under a complex traffic environment can be more truly tested.

The invention provides an automatic emergency braking method based on multi-sensor fusion, and the method comprises the following steps of acquiring the coordinate position and the relative speed of an obstacle relative to a vehicle through real-time communication between an environment sensing sensor and a whole vehicle CAN network; screening targets acquired by the environment sensing sensor, and reserving obstacle targets in the running track of the vehicle; acquiring the coordinate position and the relative speed of the obstacle target in the running track of the vehicle relative to the vehicle, calculating the collision time of the vehicle and a front obstacle, comparing the collision time with a preset early warning time threshold value, and if the collision time is less than the early warning time threshold value, sending an alarm prompt through an alarm device; and determining obstacle approximation, and performing active braking in an emergency. According to the invention, obstacle targets are screened, so that the alarm is more accurate; and short-distance blind areas of a millimeter wave radar are compensated by fusing the millimeter wave radar and an ultrasonic radar, so that the continuity of obstacle distance detection is kept, and the braking is safer.