Mechanical arm motion control method and system based on visual real-time teaching and self-adaptive DMPS

Abstract

The invention relates to a mechanical arm motion control method and system based on visual real-time teaching and self-adaptive DMPS. The method comprises the steps that a teaching object is set, theteaching object is controlled to do demonstration motion, Kinect is used for obtaining a depth map and cooperated with a PnP algorithm to carry out three-dimensional pose positioning and tracking on the teaching object, a space mapping system is built to map the pose of the teaching object to the tail end of a mechanical arm, control information of all joints of the mechanical arm is calculated according to inverse kinematics and sent in real time so as to indirectly control the mechanical arm to move, finally, the demonstration motion information is recorded on line, and the self DMPS algorithm is applied to carry out local linear optimization and learning on the information. Constraint of hardware structures of a mechanical arm and dependency to a complex sensor in a traditional teachingmode are omitted, the teaching hardware cost and teaching difficulty are lowered, safety of the teaching process is improved due to the non-contact characteristic, meanwhile, applicability is high, and the self-adaptive DMPS method enables the whole system to have good anti-interference performance.

Description

technical field [0001] The invention belongs to the field of robotic arm motion planning, and in particular relates to a motion control method and system for robotic arm online visual teaching and learning based on QR codes (a kind of two-dimensional barcode). Background technique [0002] Motion planning is mainly aimed at the robotic arm module with high-dimensional motion space on the robot. Different from the plane path planning, it is mainly divided into two categories: joint space trajectory planning and Cartesian space trajectory planning. The former mainly uses spline interpolation in the traditional The latter mainly uses planning methods such as space straight lines or space arcs. Due to the multi-degree-of-freedom space characteristics of the manipulator, these methods are not only complex in planning and calculation, but also recalculate each posture of the manipulator during the movement process for each new target, especially when the manipulator is used. When...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems of difficult teaching and poor learning anti-interference in the teaching and learning mode in the field of manipulator motion planning, the present invention proposes a manipulator motion control method and system based on visual real-time teaching and self-adaptive DMPS. The number of sensors and the guaranteed accuracy get rid of the shackles of the hardware structure of the manipulator in the traditional teaching mode and the dependence on complex sensors, reducing the hardware cost and difficulty of teaching, and the non-contact feature enhances the safety of the user while also It has wide applicability, and for problems such as interference in the teaching information, the adaptive DMPS method proposed by the present invention makes the whole system have good anti-interference performance

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