The invention discloses a control method of a manipulator grabbing control system based on binocular stereoscopic vision. The control method comprises the following steps: camera parameters are calibrated, and a teaching manipulator is used for realizing conversion of a camera coordinate system and a manipulator coordinate system; line laser performs an arc surface scanning cloud motion, and a camera acquires images; laser lines of the images shot by the camera are respectively extracted; the positions of the laser lines are precisely determined by using a sub pixel algorithm; the homonymy point matching is performed for the laser lines extracted in the images; three-dimensional space coordinates of all points on the laser lines are calculated through a triangular measuring principle to finish scanning of workpieces in a scene so as to obtain point cloud data in the viewing field of the camera; a workpiece point cloud template is built, a manipulator grabbing point position is selected, and the obtained point cloud data is matched with the workpiece point cloud template to calculate a conversion relation of the two; the manipulator grabbing point position in the point cloud template is converted to a present coordinate, is converted to a coordinate under the manipulator coordinate system, and is transferred to the manipulator; and the manipulator finishes actuation actions.

Control method of manipulator grabbing control system based on binocular stereoscopic vision

The present invention relates to a binocular vision-based workpiece grabbing method. The method includes following steps that: (1) a binocular vision system is calibrated; (2) a left camera and a right camera simultaneously collect images and correct the images; (3) a template matching algorithm is adopted to identify and position a workpiece in the left image and right image; (4) the three-dimensional attitude of the workpiece is calculated according to the identification and positioning information of the workpiece of the images of the left camera and the right camera; and (5) an industrial robot automatically grabs the workpiece according to the three-dimensional attitude information. The binocular vision-based workpiece grabbing method of the invention has the advantages of high real-time performance, high applicability, accurate grabbing, high working efficiency and the like.

Binocular vision-based workpiece grabbing method

The invention discloses a stack breaking method based on binocular vision. The method mainly includes the steps that a binocular camera is installed at the front end of a mechanical arm and moved along with the mechanical arm, a stack breaking system moves the front end of the mechanical arm to the proper position according to the regionalization condition, binocular images are acquired synchronously, and a target is identified and located; according to the posture of a stack breaking robot, the target direction under a camera coordinate system is converted into the target direction under a robot coordinate system; the stack breaking robot conducts gripping operation according to the target direction, so that a stack is broken in a layered regionalization manner. The invention further discloses the stack breaking system. By the adoption of the method and system, the stack can be accurately and reliably broken through the robot, the work space range and the stack breaking range of the stack breaking robot are broadened, stack breaking flexibility is improved, and the problem existing in localization of the stack breaking robot is effectively solved.

Novel stack breaking method and method

The invention discloses a mechanical arm hand-eye calibrating method and device based on three-dimensional object identification. The calibrating method comprises the following steps: (S1) first calibrating data of calibrated objects under a three-dimensional perspective coordinate system is obtained; (S2) second calibrating data of the calibrated objects under a mechanical arm coordinate system is obtained; and (S3) transfer matrixes of coordinates in the three-dimensional perspective coordinate system to the mechanical arm coordinate system are obtained according to the first calibrating data and the second calibrating data by using an ICP iterative closest point algorithm. The calibrating method still can realize high-precision calibration under darker environments, is simple in step and high in operability, and overcomes the defects of low precision, complicated steps, weak operability and high illumination influence in a traditional calibrating method.

Mechanical arm hand-eye calibrating method and device based on three-dimensional object identification

The embodiment of the invention discloses a robot intelligent transporting and loading and unloading integrated method and device. The method comprises the following steps that an operation track map in the new environment is constructed and stored; visual navigation is utilized to the target place according to the map; and a loading instruction is received, and the loading and unloading task at the target place is realized through a hand-eye recognition system. According to the scheme, the robot can autonomously construct the map in the new environment and navigate to the target place of product transporting according to the drawn map and finally complete loading and unloading of the product through the recognition system. The whole process is autonomously completed by the robot so that the working efficiency can be enhanced and the robot is enabled to be more intelligent.

Robot intelligent transporting and loading and unloading integrated method and device

The invention discloses a robot unstacking method based on binocular stereoscopic vision. The robot unstacking method includes the following steps of: simultaneously obtaining images within views of left and right eyes by using a binocular camera fixed right above a working area, and positioning a target by using a shape template matching method to obtain a three-dimensional coordinate under the camera coordinate system; converting from the camera coordinate system into a robot base coordinate system; arranging depth information and unstacking in a layered manner according to the detected target coordinate. According to the robot unstacking method based on binocular stereoscopic vision, target identification and three-dimensional positioning of product in an unstacking area are achieved directly through collecting binocular images, and thereby automatic unstacking task of the product is achieved, and the problems that manual unstacking is large in labor intensity and low in efficiency can be effectively overcome.

Fan Xinjian

Papers

Robot unstacking method based on binocular stereoscopic vision