3115 results about "Obstacle avoidance" patented technology

A method for automated lane centering and/or lane changing purposes for a vehicle traveling on a roadway that employs roadway points from a map database to determine a reference vehicle path and sensors on the vehicle for detecting static and moving objects to adjust the reference path. The method includes reducing the curvature of the reference path to generate a reduced curvature reference path that reduces the turning requirements of the vehicle and setting the speed of the vehicle from posted roadway speeds from the map database. The method also includes providing multiple candidate vehicle paths and vehicle speeds to avoid the static and moving objects in front of the vehicle.

Embodiments of the invention provide systems and methods for obstacle avoidance. In some embodiments, a robotically controlled vehicle capable of operating in one or more modes may be provided. Examples of such modes include teleoperation, waypoint navigation, follow, and manual mode. The vehicle may include an obstacle detection and avoidance system capable of being implemented with one or more of the vehicle modes. A control system may be provided to operate and control the vehicle in the one or more modes. The control system may include a robotic control unit and a vehicle control unit.

The invention discloses a service robot control platform system and a multimode intelligent interaction and intelligent behavior realizing method thereof. The service robot control platform system comprises a voice control module, a binocular image acquisition module, an RFID (Radio Frequency Identification Device) receiving and transmitting module, a bottom wheel movement module, an obstacle avoidance module and a mechanical arm control module. The multimode intelligent interaction and intelligent behavior realizing method comprises the following steps of: 1, voice interaction; 2, independent navigation and location; 3, mechanical arm control; and face detection and recognition. According to the invention, a robot carries out intelligent interaction and intelligent behaviors, and the capacity of intelligent grabbing of the robot is enhanced. Except for special person recognition, distinguish of a picture face and an actual face is added, thus the influence to a program by the picture face is effectively eliminated. According to the invention, anthropomorphic mechanical arm grabbing is controlled in a specific anthropomorphic path grabbing manner, so that a service mode of the robot is more intelligent and humanized.

The invention discloses a picking method and picking robot device aiming at fruits which are in size of an apple and is similar to a sphere. The picking robot device comprises a mechanical actuating device, control system hardware and control system software. The mechanical actuating device comprises a picking mechanical arm, an underactuated manipulator, an electric sliding table and an intelligent mobile platform, wherein the control system hardware comprises an IPC (industrial personal computer), a motion control card, a data acquisition card, an AHRS (attitude and heading reference system), a coder, a monocular camera, a binocular camera, a force sensor, a slipping sensor and the like. During operation, the IPC fuses information of the coder, the AHRS, monocular camera components and an ultrasonic sensor to enable the mobile platform to independently navigate and avoid obstacles. A binocular vision system collects images of mature fruits and obstacles and extracts the characteristics of the images so as to realize obstacle avoidance of the mechanical arm and fruit positioning. Finally, the IPC fuses the information of the force sensor, the slipping sensor and the position sensor, thereby further reliably gripping the mature fruits and separating the fruits from fruit branches.

The invention discloses an automatic-navigation crawler-type mobile fruit picking robot which comprises a mechanical execution system and a control system and is characterized in that the mechanical execution system comprises an intelligent movable platform, a fruit picking mechanical arm and a two-finger type manipulator, wherein the intelligent movable platform comprises two crawler assemblies, an experimental facility fixing rack, a supporting stand column, a cross beam, a speed reducer and the like; and the control system comprises an industrial personal computer, a motion control card, a data collecting card, an image collecting card, an encoder, a GPS (global position system), a monocular zooming camera assembly, a binocular camera, a laser ranging sensor, a control circuit and the like. The automatic-navigation crawler-type mobile fruit picking robot integrates the fruit picking mechanical arm, the two-finger type manipulator, the intelligent movable platform and the sensor system, integrates multiple key technologies such as fruit identification, motion of the picking mechanical arm, grabbing of a tail-end executer, automatic navigation and obstacle avoidance of the movable platform, and the like, and really realizes automatic and humanized fruit picking.

An obstacle detecting unit detects an obstacle for a user wearing a head mounted display from an image of the outside world. A distance calculating unit calculates the distance from a detected obstacle to the user wearing the head mounted display. An obstacle replacing unit replaces the detected obstacle with a virtual object. A virtual object synthesizing unit generates a virtual object at a position within a virtual space displayed on the head mounted display, in which the position is determined according to the distance to the obstacle.

The invention discloses an unmanned aerial vehicle obstacle avoidance controlling method. An unmanned aerial vehicle subsystem and a ground station subsystem are arranged, the unmanned aerial vehicle subsystem comprises an embedded flight controller and an airborne terminal of a wireless data chain, a satellite positioning receiver and a height sensor are arranged in the embedded flight controller, the ground subsystem comprises an embedded monitoring computer and a ground terminal of the wireless data chain, and an electronic map containing geographic information of obstacles is arranged in the embedded monitoring computer. On the electronic map in the embedded monitoring computer of the ground station subsystem, the geographic information of the obstacles in a flight area is determined, virtual obstacle polygonal cylinders are established, shape data of the virtual obstacle polygonal cylinders are downloaded in the embedded flight controller which obtains the current position of the unmanned aerial vehicle and calculates space correlation between the unmanned aerial vehicle and the obstacle polygonal cylinders, track-shifting instruction of the unmanned aerial vehicle is generated, and automatic obstacle avoidance of the unmanned aerial vehicle is realized.

Framework may be implemented for transferring knowledge from an external agent to a robotic controller. In an obstacle avoidance/target approach application, the controller may be configured to determine a teaching signal based on a sensory input, the teaching signal conveying information associated with target action consistent with the sensory input, the sensory input being indicative of the target/obstacle. The controller may be configured to determine a control signal based on the sensory input, the control signal conveying information associated with target approach/avoidance action. The controller may determine a predicted control signal based on the sensory input and the teaching signal, the predicted control conveying information associated with the target action. The control signal may be combined with the predicted control in order to cause the robotic apparatus to execute the target action.

The invention relates to a method for planning a path for a mobile robot based on environmental modeling and a self-adapting window, which relates to a method for planning a real-time path for the mobile robot. The method comprises the following steps of: performing modeling and analysis on a multiple constraint local environment; performing passable analysis; performing safety analysis; performing motion smoothness analysis; performing goal-directed analysis; and performing path planning by adopting the self-adapting window. Because the method has better environmental suitability and obstacle avoiding capacity, the method obtains good safety and reachability, has high calculation real-time property, so the method solves the problem that the mobile robot generates an obstacle avoidance path in real time in an uncertain complex environment, provides a path selection method with optimized integration, better meets the requirements on obstacle avoidance for the mobile robot, realizes the real-time path planning and control of the robot, and provides an effective collision-less path planning method for the navigation application of the mobile robot.

The invention discloses a binocular vision-based robot target identifying and gripping system and method. The binocular vision-based robot target identifying and gripping system comprises a binocular image acquisition module, an RFID (Radio Frequency Identification) transceiving module, a chassis movement module, an obstacle avoidance module and a mechanical arm control module. The binocular vision-based robot target identifying and gripping method comprises the following steps of: (1) calibration of a binocular camera; (2) erection and conversion of a coordinate system; (3) target identification and location; (4) autonomous navigation and obstacle avoidance; and (5) control over mechanical arms for gripping a target object. According to the invention, a robot can be intelligently interactive with the environment, and the intelligent gripping capability of the robot is enhanced. According to the binocular vision-based robot target identifying and gripping system and method, except for identification and location to the target object, a navigation database is also established, and the robot can automatically reach an area where the object is located after the target object is positioned; and the binocular vision-based robot target identifying and gripping system and method ensures that a service mode of the robot is more intelligentized and humanized by controlling the human-simulated mechanical arms and adopting a specific personified path gripping manner.

The invention discloses a mobile robot three-dimensional mapping and obstacle avoidance method based on a space bag of words model. The method comprises following steps: 1) collecting Kinect sensor data, and using a space bag of words model which fuses spatial relationships to describe scene image features 2) describing robot three-dimensional SLAM by means of the SDBoW2 model of the scene image to realize closed loop detection, three-dimensional point cloud registration, and graph structure optimization and therefore creating a global environmental three-dimensional point cloud density map; 3) the robot using the created global three-dimensional map and the Kinect sensor information to perform indoor real-time obstacle avoidance guiding. The method is aimed at low cost mobile robots without speedometers or laser distance measuring sensors; reliable real-time three-dimensional map creation and obstacle avoidance can be realized depending only on Kinect sensors; the method can be applied in long time mobile robot operation service at large area of indoor environment such as household places and office rooms, etc.

The invention discloses a multiple obstacle-avoidance control method of an unmanned plane used for electric wire inspection. The multiple obstacle-avoidance control method of the unmanned plane used for the electric wire inspection comprises an unmanned plane subsystem and a ground station subsystem. The unmanned plane subsystem comprises an embedded flight control device, a position detection module, an information processing module and an airborne terminal of a wireless data chain. The position detection module comprises a global navigation satellite system (GNSS) receiver, an electromagnetic field sensor and ultrasonic ranging sensors, wherein the ultrasonic ranging sensors are symmetrically arranged on the periphery of a machine body of the unmanned plane. The ground station subsystem comprises a ground terminal of the wireless data chain and an embedded supervisory control computer. The embedded supervisory control computer is loaded with a data base, wherein the data base contains an electric transmission line electromagnetic field distribution model and an electric transmission line space three-dimensional model. According to the multiple obstacle-avoidance control method of the unmanned plane used for the electric wire inspection, a security constraint area for the operation of the unmanned plane is built, the information processing module is adopted for integration of unmanned plane position information provided by an information detection module, relative distance between the unmanned plane and an electric transmission line is detected, and multiple obstacle-avoidance of the unmanned plane used for the electric wire inspection is achieved.

The invention relates to the technical field of robots, in particular to a robot path planning method and device in an indoor dynamic environment and a robot. Known obstacle environment information and obstacle expansion information are taken as reference in global path planning, a local path is generated according to dynamic obstacle information and obstacle expansion information in local path planning, is spliced with a global path with the minimum path cost value sum and replaces the global path with the minimum path cost value sum in a local window to obtain a target obstacle avoidance path, and the robot is controlled with a path fitting control algorithm to move along the target obstacle avoidance path so as to avoid dynamic obstacles. The obstacle environment information acquired in the global path planning is more complete, global environment is taken into consideration in the global path with the minimum path cost value sum, and the local path is generated according to the dynamic obstacle information and the obstacle expansion information in the local path planning, so that the robot can adapt to the changing environment during operating in the local window and is enabled to walk along the finally planned target obstacle avoidance path.

An autonomous obstacle avoidance and navigation method for unmanned aerial vehicle (UAV)-based field search and rescue provided by the invention includes global navigation based on GPS signals and anautonomous obstacle avoidance and navigation algorithm based on binocular vision and ultrasound. First, a UAV carries out search under the navigation of GPS signals according to a planned path. Aftera target is found, the autonomous obstacle avoidance and navigation algorithm based on binocular vision and ultrasound is adopted. A binocular camera acquires a disparity map containing depth information. The disparity map is re-projected to a 3D space to get a point cloud. A cost map is established according to the point cloud. The path is re-planned using the cost map to avoid obstacles. When there is no GPS signal, a visual inertial odometry (VIO) is used to ensure that the UAV flies according to the planned path, and an ultrasonic sensor is used to detect and avoid obstacles below the UAVto approach the rescued target. UAV autonomous obstacle avoidance and navigation in a field search and rescue scene is realized.

An obstacle avoidance path computing apparatus is provided with a preceding object detecting section, a host vehicle information detecting section, a preceding object arrival region estimating section and a preceding object avoidance path setting section. The preceding object detecting section detects a preceding object. The host vehicle information detecting section detects host vehicle information. The preceding object arrival region estimating section calculates an estimated arrival region within which the preceding object could arrive after a prescribed amount of time has elapsed since the preceding object was detected, based on an estimated attribute of the preceding object from the preceding object information. The preceding object avoidance path setting section calculates an avoidance path that will not encroach on the estimated arrival region based the preceding object information and the host vehicle information.

A method, medium, and apparatus of a self-propelled mobile unit with obstacle avoidance during wall-following. In the self-propelled mobile unit, a carrying unit may move the mobile unit by using a transmitted power, and a sensor unit can detect an obstacle and a wall, which may be respectively placed in front of and to the side of the mobile unit, with respect to a moving direction of the carrying unit. A controller may direct the carrying unit by generating a path along which the carrying unit moves according to a detection result from the sensor unit. Accordingly, the controller can direct the carrying unit to move while maintaining a predetermined distance (within a predetermined range) from the wall. If the sensor unit detects an obstacle, the controller directs the carrying unit to move in an obstacle free direction.

The invention discloses a vision guiding AGV (Automatic Guided Vehicle) system and a method of an embedded system. Two cameras fixed on a trolley are used for acquiring guiding path information in real time, wherein the cameras and the ground form a certain angle to be inclined forwards and is used for acquiring prospect images; and the cameras are arranged at the middle part and the front part of the interior of the trolley, are vertical to the ground and are used for secondary exact location. The vision guiding AGV method comprises the following step of: embedding an anti-metal radio frequency mark on the ground surface of a key position, wherein a vehicle-mounted radio frequency card reader obtains information in the mark when the trolley passes through the upper part of the mark. When a laser scanner scans a front obstacle in real time, obstacle avoidance detection and obstacle avoidance are realized. A control box of the embedded system disclosed by the invention is as an inner kernel for image collection, image treatment and policy control, the acquired image is subjected to Gauss high-pass filtering, edge detection and two-step Hough transformation so that position deviation and angle deviation of the trolley relative to a current path can be calculated, and two-dimensional deviation value of the AGV currently corresponding to a location reference point is fed back at a station point.

The invention relates to the technical field of mobile robot autonomous navigation and particularly relates to an omnidirectional mobile robot autonomous navigation apparatus and method based on a laser range finder. The omnidirectional mobile robot autonomous navigation apparatus based on the laser range finder comprises an encoder for measuring the movement distance of wheels of a mobile robot, and an inertia measurement unit for measuring the rotation angular velocity and the acceleration of the mobile robot. The encoder and the inertia measurement unit are connected with a controller. The omnidirectional mobile robot autonomous navigation apparatus also comprises the laser ranger finder which is connected with a host computer. The host computer is connected with the controller, and the controller is connected with an execution unit. The invention utilizes the laser range finder to position the mobile robot, establishes a two-dimensional planar map of the environment, carries out autonomous navigation according to a target task, and achieves autonomous obstacle avoidance in the movement.

The invention discloses a mobile robot obstacle avoidance navigation method and system. The method includes the following steps that: a global map of a home environment is established; the starting point and destination of the movement of a robot are set; the movement path of the robot is planned according to the A* algorithm; the position of a obstacle is marked in the global map; the movement path of the robot is re-planned according to the A* algorithm; the robot is controlled to move according to the planned path; and the robot arrives at the destination and stops moving. With the mobile robot obstacle avoidance navigation method and system of the invention adopted, unknown environment can be detected, so that the information of unknown obstacles can be obtained, and the estimation function is adopted to plan the shortest and most economical path, and therefore, the equipment cost of the obstacle avoidance navigation of the robot can be decreased; the position and movement attitude of the robot can be monitored in real time, and the walking attitude of the robot can be adjusted and controlled in real time, and the accuracy and effectiveness of the obstacle avoidance navigation of the robot can be ensured.

The invention provides an autonomous navigation and obstacle avoidance system and a method of an indoor mobile robot. The system comprises a wireless sensor network and a mobile robot; the wireless sensor network comprises Cricket sensor beacons, Cricket sensor receiving nodes and ultrasonic sensor nodes; indoor environment is divided into several grids; the ultrasonic sensor nodes are deployed on a ceiling according to set grids; meanwhile four or more Cricket sensor beacons are deployed randomly; an external communication module of a mobile robot master control one-chip microcomputer is connected with the Cricket receiving nodes; a segment maximum likelihood centroid algorithm is employed to locate the robot, establish a three-dimensional environment map and a grid map and construct path grids; and a global path is programmed based on an expansion algorithm and a Dijkstra algorithm. According to the invention, a sensor network with global monitoring capability is employed and introduced into indoor and dynamic environment navigation for robot, and has advantages of accurate positioning, rapid environment modeling and reasonable path programming.

A vision system for a vehicle that identifies and classifies objects (targets) located proximate a vehicle. The system comprises a sensor array that produces imagery that is processed to generate depth maps of the scene proximate a vehicle. The depth maps are processed and compared to pre-rendered templates of target objects that could appear proximate the vehicle. A target list is produced by matching the pre-rendered templates to the depth map imagery. The system processes the target list to produce target size and classification estimates. The target is then tracked as it moves near a vehicle and the target position, classification and velocity are determined. This information can be used in a number of ways. For example, the target information may be displayed to the driver, the information may be used for an obstacle avoidance system that adjusts the trajectory or other parameters of the vehicle to safely avoid the obstacle. The orientation and/or configuration of the vehicle may be adapted to mitigate damage resulting from an imminent collision, or the driver may be warned of an impending collision.

The invention relates to the technology of UAV (unmanned aerial vehicle) control, aims at proposing a UAV locus and attitude cooperative control method and ironing out a defect in the locus planning for each UAV of a conventional UAV cluster, and can effectively reduce the requirements for the positioning precision of the UAV. Therefore, the invention provides a cluster UAV locus and attitude cooperative control method for a safety domain, and the method comprises the following steps: 1, control-oriented four-rotor-wing UAV locus and attitude model building: giving full consideration to the inherent characteristics of a four-rotor-wing UAV and the dynamic factors in flight, and building a locus and attitude mathematic model for the four-rotor-wing UAV; 2, cluster center locus planning: achieving the obstacle avoidance path planning for a cluster UAV central point based on a pseudo-spectral method; 3, safety flight region optimization: completing the optimization of a cluster UAV safetyflight envelope and a cluster UAV optimal formation configuration; 4, distributed cooperative controller design. The method is mainly used in a UAV control occasion.

The invention discloses a parking path planning method and parking motion control method of an auxiliary parking system. A multi-stage smooth parking path which is designed through the parking path planning method based on the B-spline theory meets multiple non-linear constraints such as a vehicle obstacle avoidance constraint, a minimum turning radius constraint and a maximum steering speed constraint; through the path curvature continuity, a pivot steering phenomenon is avoided, and tire wear and steering motor loads are reduced; through the multi-stage smoothness of the path, vehicle tracking is easy to achieve. According to the parking motion control strategy, the requirements of the parking system for the parking speed of a driver are lowered, and the driver only needs to control a vehicle to be driven at low speed. For the phenomenon that in the parking process, the vehicle deviates from the target path and cannot park in the correct position due to the fact that the vehicle speed is too high, a vehicle position posture adjusting strategy based on fixed-point tracking control is presented, and therefore the parking success rate is increased; in addition, fixed-point tracking control is adopted, therefore, the vehicle can be parked to be parallel to a parking space, and vehicle parking standardization is achieved.

A free flight obstacle avoidance system (OAS) is a commanded obstacle resolution feedback system. The system employs insertion of hybridized elements to the existing designs of Adaptive Ground Collision Avoidance Systems and Midair Collision Avoidance Systems along with a newly design module, the obstacle avoidance dispatcher and resolver, to provide a coherent obstacle resolution. The system is capable of filtering data produced by the hybrid ground collision avoidance module and the hybrid air collision avoidance module, inserting evaluating solution status and command directives before routing avoidance data to hybrid modules for validation. The dispatcher and resolver module determines the final obstacle resolution to generate avoidance control guidance and appropriate warnings clearly indicated obstacle situation and obstacle avoidance maneuvers to the flight crew. In addition to the avoidance capabilities, the system also provides extended functions of terrain following guidance and space separation warnings.

The invention discloses an intelligent mobile charging automobile system and method. The system comprises a charging automobile, a large-capacity energy storage battery pack, a DC-DC direct-current converter A, a vehicle-mounted charger, a charging connection device, a charging transfer device, a ground track, a mobile phone client terminal, a scheduling center server and a charging room, wherein the scheduling center server comprises a wireless communication unit, a data receiving unit, a data processing unit and a data feedback unit; the charging automobile comprises a driving system, a whole-automobile controller, a wireless communication module, a sound-light alarm module, a tracking detection module and an obstacle avoidance detecting module. According to the intelligent mobile charging automobile system, navigation and landmark tracks are mounted and paved on the ground on the basis of the existing facilities of parking lots; the charging transfer device is mounted on the ground of the preserved charging automobile parking space; the automatic connection charging is implemented; the problem that charging stations and charging piles are inconveniently built in the existing parking lots can be solved; the system is simple and convenient; the building cost and the maintenance cost are greatly reduced; and the charging time is reduced.

The invention discloses a mobile robot. The mobile robot comprises a central processing module; a distance measuring sensor, an auxiliary obstacle avoidance module, and a man-machine interaction module, which are connected with the central processing module. The distance measuring sensor is used to scan the operation space of the mobile robot to establish an environmental map. The auxiliary obstacle avoidance module is used to detect obstacles and cliff boundaries in the sensing blind area of the distance measuring sensor during the moving of the mobile robot, and then the environmental map is improved. A user can input virtual obstacle information in the environmental map by the man-machine interaction module, and then the environmental map is further improved. The moving path of the operation of the mobile robot is planned according to the environmental map. The mobile robot is used to establish and improve the environmental map of the operation space in a step-by-step manner, and the moving path is planed according to the environmental map, and therefore the obstacles are accurately avoided, time and energy are saved. The invention also discloses the navigation method of the mobile robot.

The invention discloses an ultrasonic distance detection-based unmanned aerial vehicle obstacle avoidance system and a control method thereof. The unmanned aerial vehicle obstacle avoidance system includes a flight control module, an airborne radio frequency communication module, an ultrasonic ranging module and an autonomous obstacle avoidance module, wherein the flight control module is used for controlling the flight of an unmanned aerial vehicle and feeding back the flight condition of the unmanned aerial vehicle to a ground station, the ultrasonic ranging module is used for detecting whether obstacles exist before, above and below the unmanned aerial vehicle as well as at the left and the right of the unmanned aerial vehicle, and detecting the distances between the unmanned aerial vehicle and the obstacles, and the autonomous obstacle avoidance module is used for controlling the unmanned aerial vehicle to perform obstacle avoidance according to measurement results of the ultrasonic ranging module. With the control method of the unmanned aerial vehicle obstacle avoidance system adopted, the unmanned aerial vehicle can autonomously avoid the obstacles, and the avoidance modes of the unmanned aerial vehicle can be more diverse, and the unmanned aerial vehicle can automatically adjust flight routes and accomplish specified flight tasks. The ultrasonic distance detection-based unmanned aerial vehicle obstacle avoidance system of the invention has the advantages of simple structure, convenient use and high practical value.

The invention discloses a flight control method of a small unmanned helicopter. According to the method, a flight execution unit, a state sensor unit, a parachute unit, a flight control unit, a ground control terminal and a remote controller unit are adopted, so that the effects of obstacle-avoidance flight, water-surface-avoidance landing, self-adaptive flight attitude control, power monitoring, automatic parachute opening in case of engine stop, flight control through a flight control panel, flight path generation through a signal panel and the like can be achieved. The flight control method of the small unmanned helicopter has the advantages that the self-adaptive obstacle-avoidance flight capacity of the small unmanned helicopter can be improved; the small unmanned helicopter can operate in a beyond visual range according to a preset instruction, can slowly land by using a parachute in an emergency of the engine stop in the air, is protected from being damaged, and can automatically avoid a water surface during landing.

Embodiments of the present invention provide methods and systems for ensuring that mobile robots are able to detect and avoid positive obstacles in a physical environment that are typically hard to detect because the obstacles do not exist in the same plane or planes as the mobile robot's horizontally-oriented obstacle detecting lasers. Embodiments of the present invention also help to ensure that mobile robots are able to detect and avoid driving into negative obstacles, such as gaps or holes in the floor, or a flight of stairs. Thus, the invention provides positive and negative obstacle avoidance systems for mobile robots.

The invention discloses a planning method for a mixed path of a mobile robot under a multi-resolution barrier environment. The invention aims to solve the problems of blindness of initial planning, environment modeling lack of flexibility and poor real-time obstacle avoidance capability of the present method. According to the technical scheme, a self-adapting inhomogeneous polar-radius polar coordinate modeling method is adopted for performing environment modeling on the motion space of the mobile robot; a gravity particle swarm searching method is adopted for planning an initial overall path from starting point to ending point; according to the initial overall path, a modified artificial potential field method is adopted for performing local dynamic obstacle avoidance by estimating the minimum safe distance and safe collision-preventing angle and for arriving at each initial overall path point in turn; and a final overall collision-free path is output after arriving the planning end point. According to the planning method provided by the invention, the blindness of initial overall planning and the environment modeling flexibility can be effectively improved, the real-time obstacle avoidance capability for dynamic unknown barrier is strong, and the method is high in speed, high in precision and strong in adaptability.