Reserch On Kinematics And Path Planning Of 7-dof Redundant Manipulator

In recent years,robotics technology has developed rapidly.As the main branch of the robotics industry,redundant manipulators are more flexible,reliable and fault-tolerant than traditional six-degree-of-freedom manipulators,and are widely used in various industries and fields of society.As the actual application scenarios become more complex,higher requirements are put forward for its load capacity,obstacle avoidance ability,and human-computer interaction capabilities.Therefore,the related research of redundant degrees of freedom manipulators has become an important direction in this field.This paper takes the seven-degree-of-freedom redundant manipulator KINOVA Gen 3 as the research object,and studies its kinematics and path planning.The main components of the dissertation are shown below:Firstly,this thesis analyzes the forward and inverse kinematics of the redundant manipulator with seven degrees of freedom.The classic D-H parameter method and homogeneous coordinate transformation are used to establish the forward kinematics model and forward motion equation of the redundant manipulator;The gradient projection method is used to analyze its inverse kinematics and solve seven joint angles of the manipulator.The forward and inverse kinematics of the seven-degree-of-freedom redundant manipulator are simulated and verified by the Robotic Toolbox in MATLAB.Secondly,the path planning method of manipulator under the obstacle-free environment is studied.This thesis analyzed the cubic polynomial interpolation algorithm and trapezoidal velocity interpolation algorithm in the joint space.By comparing the planning results of the two algorithms,the path planning simulation experiment was carried out in the joint space using the cubic polynomial interpolation algorithm with the joint angular velocity as the constraint condition.The linear and arc path planning algorithm based on the parabolic transition algorithm is studied in cartesian space,and the accuracy of the algorithm is verified through simulation experiments too.Thirdly,aiming at the problems of random search strategy and low success rate of the original algorithm,an improved RRT algorithm is studied.Bidirectional search strategy and goal-oriented strategy are adopted on the original algorithm.The simulation verification of path planning is carried out on the two-dimensional multi-obstacle distribution environment and the redundant manipulator studied in this paper.The simulation results show that whether it is in low-dimensional space or high-dimensional space,the improved algorithm in this paper can not only successfully plan a feasible path,but also greatly reduce the number of sampling points and planning time,and effectively improves the path planning efficiency and real-time performance of the basic RRT algorithm.Finally,the path planning experiments under two kinds of obstacles are carried out on the experimental platform of the KINOVA Gen 3 redundant manipulator,and the experimental results verify the effectiveness of the improved algorithm.