355 results about "Robot path" patented technology

An obstacle detector for a mobile robot while the robot is in motion is disclosed. The detector preferably includes at least one light source configured to project pulsed light in the path of the robot; a visual sensor for capturing a plurality of images of light reflected from the path of the robot; a processing unit configured to extract the reflections from the images; and an obstacle detection unit configured to detect an obstacle in the path of the robot based on the extracted reflections. In the preferred embodiment, the reflections of the projected light are extracted by subtracting pairs of images in which each pair includes a first image captured with the at least one light source on and a second image captured with the at least one light source off, and then combining images of two or more extracted reflections to suppress the background.

A method and a system for use in connection with programming of an industrial robot, the programming comprises teaching the robot a path having a number of waypoints located on or in the vicinity of an object to be processed by the robot. The system comprises: means for obtaining information about the waypoints of the path in relation to the object, a storage unit (16), for storing the obtained information, a simulation unit (18), simulating the robot path based on the obtained information about the waypoints and a model of the robot, a graphics generator (23), generating a graphical representation of the simulated robot path, and a display member (12) displaying a view comprising the object and said graphical representation of the robot path projected on the object.

The invention provides a robot path planning method and an apparatus thereof based on a Bezier curve. The method comprises the following steps that: a robot path planning parameter input unit receives and sets a robot state parameter, a constraint condition, a path discretization minimum time resolution; a robot path generation unit generates a group of Bezier curve control points consisting of four 4-dimension vectors according to the robot state parameter and plans out a continuous path between an origin position to a target position of the robot; the robot path generation unit forms a timepoint sequence according to the path discretization minimum time resolution and calculates a discretization path according to the continuous path; a path point parameter detection unit detects whether a speed, an acceleration and a turn radius of each path point which is corresponding to the time points satisfy the constraint condition; if the speed, the acceleration and the turn radius of each path point do not satisfy the constraint condition, the control points are regenerated; otherwise, a planning path output unit receives and outputs a robot path which is planed by the path point parameter detection unit and satisfies the constraint condition.

A system, method, and computer readable medium. A method for robotic path planning includes receiving a robotic path for a robot and associating a plurality of zones with each location in the robotic path. The method also includes selecting for each location one of the zones associated with the location and simulating motion of the robot over the robotic path using the locations and selected zones. The method further includes determining whether a collision occurred in the simulated motion of the robot. The method still further includes, if there was a collision, identifying a location associated with the collision, selecting a new zone for the identified location other than the currently selected zone, and repeating the steps of simulating motion of the robot and determining whether a collision occurred. The method also includes, if there wasn't a collision, assigning to each location its currently selected zone.

The invention discloses a mixed robot dynamic path planning method which is capable of being applied on the condition that a part of environment information is known, and unknown dynamic and static obstacles exist at the same time. Aiming at the conditions, the mixed robot dynamic path planning method comprises the following steps: utilizing a genetic algorithm (GA) as a global planning method to obtain global paths, and then conducting local planning by means of an improved artificial potential field method. According to the mixed robot dynamic path planning method, in local planning, speed and acceleration information of a robot and a barrier is considered, and therefore the mixed robot dynamic path planning method has better effects on processing dynamic path planning. In addition, effects of global planning path for local planning are also considered. The mixed robot dynamic path planning method is ease to achieve, robot paths obtained are more optimized, and meanwhile good flexibility is shown in the application.

A system and method facilitate machine-vision, for example three-dimensional pose estimation for target objects, using one or more images sensors to acquire images of the target object at one or more positions, and to identify features of the target object in the resulting images. A set of equations is set up exploiting invariant physical relationships between features such as constancy of distances, angles, and areas or volumes enclosed by or between features. The set of equations may be solved to estimate a 3D pose. The number of positions may be determined based on the number of image sensors, number of features identified, and / or number of known physical relationships between less than all features. Knowledge of physical relationships between image sensors and / or between features and image sensors may be employed. A robot path may be transformed based on the pose, to align the path with the target object.

The invention relates to an AGV robot guide deviation correction method and belongs to the robot technology field. The AGV robot guide deviation correction method comprises steps that: step 1, Nth two-dimensional code label information and Nth RFID label information are employed; step 2, the Nth two-dimensional code label information and the Nth RFID label information are read and analyzed; step 3, the present geographic position of a robot is determined; step 4, a deviation state of the robot is determined, if the deviation state does not exist, the step 1 restarts; step 5, a path of the robot is adjusted to control a servo motor system for correcting a walking direction of the robot, after correction, when the robot walks to an N+1 two-dimensional code label or an N+1 RFID label, the step 1 restarts. The guide deviation correction method is applicable to AGV robot path navigation systems including multiple two-dimensional code labels, multiple RFID labels, a two-dimensional image acquisition system, an RFID reading system, a servo motor system, a communication system and an embedded industrial control board, is simple and easy to enforce, can automatically correct the walking direction of the robot and guarantees that the robot smoothly travels along a self path.

A robot simulation device, capable of simulating if a robot can transfer an object without any interference in a working space where obstacles are disposed. The device comprises of an input device, a display, a processing unit, computing programs and an output device of teaching programs. And the device further comprises of: (1) a two-dimensional display part having coordinate axes, (2) a means of displaying the obstacles and working space, a means of displaying a path of the moving robot, and a means of displaying the transferred object by the robot, on the display, (3) a means of interpolating the path by designating moving points of a central point of the moving transferred object, (4) a means of displaying the path of the moving transferred object in the working space, and (5) a means of displaying a region where the path interferes with the obstacles.

A system and method facilitate machine-vision, for example three-dimensional pose estimation for target objects, using one or more images sensors to acquire images of the target object at one or more positions, and to identify features of the target object in the resulting images. A set of equations is set up exploiting invariant physical relationships between features such as constancy of distances, angles, and areas or volumes enclosed by or between features. The set of equations may be solved to estimate a 3D pose. The number of positions may be determined based on the number of image sensors, number of features identified, and / or number of known physical relationships between less than all features. Knowledge of physical relationships between image sensors and / or between features and image sensors may be employed. A robot path may be transformed based on the pose, to align the path with the target object.

A method and an apparatus for planning path of robot in correspondence to environment changes in real time, and a recording medium storing the program for performing the said method. The method includes operating the robot according to a first path; generating a second path if an obstacle is discovered around the robot while the robot is being operated according to the first path, and data of the first path exist in a first space within a first distance from a current location of the robot; and operating the robot according to at least the second path.

A volumetric sensor for mobile robot navigation to avoid obstacles in the robot's path includes a laser volumetric sensor on a platform with a laser and detector directed to a tiltable mirror in a cylinder that is rotatable through 360° by a motor, a rotatable cam in the cylinder tilts the mirror to provide a laser scan and distance measurements of obstacles near the robot. A stereo camera is held by the platform, that camera being rotatable by a motor to provide distance measurements to more remote objects.

The invention relates to a method for planning robot paths on the basis of path expansion ant colony algorithms. The method has the advantages that the ant colony algorithms are applied to the field of robot path planning, path expansion ant colony algorithm optimization strategies are proposed, the robot path optimizing efficiency can be optimized, information element distribution time-varying characteristics, information element updating strategies, path location inflection point optimization and local optimal path expansion are introduced, and location inflection point parameters and general evaluation are additionally used as evaluation standards for the paths; as verified by simulation analysis and practical experiments on the three algorithms, the method is high in robot path planning and searching capacity on the basis of the path expansion ant colony algorithm optimization strategies and is high in algorithm efficiency, and the found paths are short; phenomena that the algorithms run into local optimization can be effectively inhibited, the optimal paths of robots can be searched, and the robots can quickly avoid obstacles to safely arrive at target points.

A method and a system for use in connection with programming of an industrial robot. The programming includes teaching the robot a path having a number of waypoints located on or in the vicinity of an object to be processed by the robot. The system includes elements for obtaining information about the waypoints of the path in relation to the object, a storage unit for storing the obtained information, a simulation unit for simulating the robot path based on the obtained information about the waypoints and a model of the robot, a graphics generator for generating a graphical representation of the simulated robot path, and a display member for displaying a view comprising the object and the graphical representation of the robot path projected on the object.

Disclosed is a mobile robot and method generating a path of the mobile robot, capable of quickly moving the mobile robot to a location at which the mobile robot is able to detect a docking station. A first configuration space map is built by expanding an obstacle area including an obstacle by a first thickness, and a second configuration space map is built by expanding the obstacle area by a second thickness which is less than the first thickness. A path is generated by sequentially using the first configuration space map and the second configuration space map.

The invention discloses a 3D obstacle avoidance indoor robot navigation method and system. The method comprises acquiring a 3D model, an initial position and a final position of a robot, acquiring a global 3D map, carrying out global route planning to produce a series of global path points, carrying out 3D obstacle collision detection on each one of the global path points to obtain the optimal global route plan, making the robot travel according to the optimal global route plan, carrying out 3D obstacle collision detection in the next global path point in travelling, if the robot produces impact, carrying out global route planning through a real-time 3D map as the global 3D map and a real-time position as an initial position, and if the robot does not produce impact, making the robot travel to the final position so that robot autonomous navigation and 3D obstacle avoidance are realized. The method and system can successfully acquire the feasible robot path in the crowded indoor environment, and completes the autonomous navigation and the 3D obstacle avoidance task of the robot from the initial position to the final position.

The invention provides a multi-neural network control planning method for a robot path in an intelligent environment. The method comprises the steps that 1 a global map three-dimensional coordinate system is constructed for the carrying area of a carrier robot to acquire a walkable area coordinate in the global map three-dimensional coordinate system; 2 a training sample set is acquired; 3 the global static path planning model of the carrier robot is constructed; and 4 starting and ending coordinates in a transportation task are input into the global static path planning model based on a fuzzy neural network to acquire the corresponding optimal planning path for the carrier robot. According to the invention, the global static path planning model and a local dynamic obstacle avoidance planning model are separately established; the nonlinear fitting property of the neural network is used to find the global optimal solution quickly; and the problem of falling into a local optimum in common path planning is avoided.

The invention relates to a path planning method for mobile robots based on a particle swarm optimization algorithm. The prior path planning method for the mobile robots has single path selection and is easy to come to a dead end. The method comprises the concrete steps of: modeling the environment first; using a polygon to represent an obstacle; using a point to represent a robot, using a small square frame to represent the original position of the robot; and using a cross to represent a target point, wherein a starting point of the robot is marked as S, and the target point is marked as G; planning paths of the robot by utilizing the particle swarm optimization algorithm; and finally performing the deep first search on the planned paths. The method adds the deep first search into a polar coordinate particle swarm. By the method, the robot can effectively find one collision-free path in most of complex environments, and finally reach target points.

An apparatus, method and computer-readable medium planning a path of a robot by planning an optimal path while satisfying a dynamic constraint. In a process of searching for a motion path from a start point to a goal point while extending a tree from a start point of a configuration space to generate a path, along which a manipulator of the robot is moved in order to perform a task, an optimal path is generated responsive to the dynamic constraint of the manipulator of the robot to generate stable motion satisfying momentum and Zero Moment Position (ZMP) constraint. Accordingly, path planning performance is improved and a path satisfying a kinematic constraint and a dynamic constraint is rapidly obtained.

The invention relates to a transformer substation inspection robot path planning navigation method. The method comprises the steps that a robot walks one circle around a transformer substation, and a two-dimensional grid map of the transformer substation is generated; transformer substation equipment image information is scanned, and a feature image is selected to serve as a road and equipment identification basis; an optimal inspection path is planned; surrounding environment information is scanned to generate a two-dimensional grid map of the surrounding environment, the position where the inspection robot is located is identified by comparing the surrounding environment map with the transformer substation map, and rough positioning is achieved; surrounding equipment image information is acquired, the equipment position is identified by comparing the surrounding environment image information with an equipment feature image, errors generated in the map matching link are corrected, and then higher-precision positioning is achieved; whether map matching positioning and visual positioning are in a same area or not is inspected, if yes, it is proved that positioning is accurate, and if not, it shows that positioning is wrong, and then map matching positioning and visual positioning are conducted again. Therefore, the positioning navigation reliability and accuracy are greatly improved.

The invention, which belongs to the field of intelligent algorithm optimization, provides a reinforced learning robot path planning algorithm based on a potential field in a complex environment, thereby realizing robot path planning in a complex dynamic environment under the environmental condition that a large number of movable obstacles exist in a scene. The method comprises the following steps:modeling environment space by utilizing the traditional artificial potential field method; defining a state function, a reward function and an action function in a Markov decision-making process according to a potential field model, and training the state function, the reward function and the action function in a simulation environment by utilizing a reinforcement learning algorithm of a depth deterministic strategy gradient; and thus enabling a robot to have the decision-making capability of performing collision-free path planning in a complex obstacle environment. Experimental results showthat the method has advantages of short decision-making time, low system resource occupation, and certain robustness; and robot path planning under complex environmental conditions can be realized.

A robot and a method for creating a robot path. The method for planning the robot path includes generating a depth map including a plurality of cells by measuring a distance to an object, dividing a boundary among the plurality of cells into a plurality of partitions according to individual depth values of the cells, and extracting a single closed loop formed by the divided boundary, obtaining a position and shape of the object located at a first time through the extracted single closed loop, calculating a probability that the object is located at a second time after t seconds on the basis of the obtained position and shape of the object located at the first time, and creating a moving path simultaneously while avoiding the object according to the calculated probability, thereby creating an optimum path without colliding with the object.

The invention relates to a robot path planning algorithm based on an optimized ant colony algorithm. The algorithm comprises the following steps: S1, initializing an inspiring factor to construct thecomprehensive inspiring information for the movement of the robot according to a target gravitation generated by an artificial potential field and an ant colony algorithm; S2, updating pheromone in the art colony algorithm by adopting a wolves distribution rule; and S3, optimizing a planned path by utilizing a path optimization algorithm. By adopting the robot path planning algorithm, an optimum path can be rapidly and efficiently planned.

The invention discloses a semantic navigation method and system used for a ground sweeping robot. The method comprises the following steps of step S1, acquiring positioning information of the ground sweeping robot in an environment; step S2: acquiring a depth map corresponding to obstacles in the environment; step S3: acquiring three-dimensional positions of all the obstacles in the depth map; step S4, identifying semantic information corresponding to the obstacles in the environment; step S5: constructing a two-dimensional grid map of a scene with semantics; step S6: planning a path of the ground sweeping robot, and guiding the ground sweeping robot to travel; and step S7: updating the two-dimensional grid map of the scene with semantics in real time. The semantic navigation system used for the ground sweeping robot is also included. In the invention, problems that some places are not swept; repeated sweeping is performed; and wrong sweeping exists are solved, cleaning efficiency of the ground sweeping robot is increased, and the dynamic obstacles can be avoided.

Various disclosed embodiments include systems and methods for determining an efficient robot-base position. The method includes receiving available robot-base positions and determining valid robot-base positions from the available robot-base positions. The method includes generating for the valid robot-base positions respective directed graphs providing a plurality of robotic-paths. The method includes determining the shortest robotic-path between start and end nodes. The method includes determining and storing the efficient robot-base position from the valid robot-base positions, wherein the efficient robot-base position has the shortest, collision-free robotic-path between start and end nodes.

A method for programming an industrial robot having a tool. The method includes obtaining configuration data for the tool and for the robot path and information about the position and orientation of the object in relation to the robot, obtaining a sequence of waypoints, which defines the process in relation to the object, obtaining at least one distance for adjusting the position of a waypoint, deciding whether an obtained waypoint should be modified or not, based on the obtained information about the waypoints, generating a modified sequence of waypoints by modifying the waypoints in the obtained sequence of waypoints, based on the decision, the obtained distance and the obtained information about the waypoints and generating the actual robot path based on the modified sequence of waypoints and the obtained configuration data.

The invention discloses a multi-robot path planning method based on an Ad-Hoc network and relates to the multi-robot path planning method which can be applied to coal mine environments, is based on the Ad-Hoc network and belongs to intelligent control methods. In the method, an ant colony algorithm serves as a core, a complicated environment of a coal mine after a mine disaster is subjected to path planning, an optimum path is searched, and the aim of rescuing is fulfilled. Communication is realized through the Ad-Hoc network, and the problems of lacking of communication and indirectness in communication of the ant colony algorithm are solved. By adoption of the multi-robot path planning method, clear information data can be provided for rescuing operation, so rescuing can be better finished.

A system and process is provided for controlling a robot path of a robot including providing a main path for movement of the robot based on path data having points along the main path and providing a safe evacuation path from each point in the main path to get to a safe position. The main path is formed with safety evacuation path considerations in mind such that along any point on ride path the robot can be safely moved to a safety point or to the unload position or safe position.

The invention discloses a transitional track planning method for a welding robot. The transitional track is used for fusing a straight segment welding line and an arc segment welding line, geometric constraint conditions of adjacent fused straight segment welding line and fused arc segment welding line of a workpiece to be welded are imported into a robot path planning module to generate a transitional segment arc welding line track, and by controlling the arc radius of the transitional segment track, welding constraint conditions and robot welding system dynamic constraint conditions are metwhen the robot welds the transitional segment. The track planning method is suitable for switching different segments of tracks and planning transitional tracks, and solves the problem of smoothness of transiting from the straight segment welding line to the arc segment welding line when the robot performs arc welding.

The invention belongs to the technical field of robot path navigation and discloses a dining room path navigation system and method of a robot. The dining room path navigation system of the robot comprises a control module, a touch screen and a stepping motor, wherein the control module is connected with the touch screen and the stepping motor respectively; the touch screen is used for displaying a dinning room coordinate point, determining the dinning room coordinate point corresponding to an initial position of the robot, sequentially inputting a plurality of adjacent dinning room coordinate points from the dinning room coordinate point corresponding to the initial position of the robot, inputting staying data and sending path data and the staying data to the control module; the control module is used for generating a corresponding pulse signal according to the path data and the staying data and sending the pulse signal to the stepping motor; the stepping motor is used for driving a wheel hub of the robot according to the pulse signal so as to move the robot.

The present invention discloses a dispersedly stacked material pickup apparatus and method. The apparatus comprises a robot, a host computer, and a light measuring system; the light measuring system comprises a projection device, a left camera and a right camera that are respectively located on the left and right sides of the projection device; the projection device sequentially projects a Gray code image in the material pickup scene; the left camera and the right camera respectively collect the Gray code images in the material pickup scene and transmit the Gray code images to the host computer; according to the Gray code images collected by the left camera and the right camera, the host computer reconstructs the point cloud of the target object, carries out identification and locating on the target object in the material pickup scene to obtain the three-dimensional stacking location and the three-dimensional posture of the target object, formulates the pickup strategy, plans the pickup path of the robotic arm of the robot, and transmits the pickup path to the robot; and the robot performs a pickup operation according to the pickup path. According to the apparatus and method disclosed by the present invention, the problem that the robot path is difficult to plan due to the arbitrary posture of the dispersedly stacked material can be effectively solved.