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Research On Path Planning Method Of Robotic Arm Based On Improved Artificial Potential Field Method

Posted on:2024-02-16Degree:MasterType:Thesis
Country:ChinaCandidate:Y X HouFull Text:PDF
GTID:2568307076476774Subject:Control Science and Engineering
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With the rapid development of robotics and intelligent technologies,robotic arms are playing an increasingly important role in various fields such as healthcare services,agricultural cultivation,and specialized operations.Industrial production has always been the most widely applied area for robotic arms.Most industrial production environments are complex and constantly changing,with many irregular and dynamic obstacles.The challenge lies in enabling robotic arms to autonomously plan optimal paths based on the movement of obstacles.To address this issue,this thesis takes the Robot Anno V6+ robotic arm as the research subject and proposes a robotic arm end-effector path planning algorithm that is versatile,simple to apply,convenient,efficient,and capable of autonomous obstacle avoidance.The main research contents of this thesis are as follows:(1)The kinematic characteristics of the Robot Anno V6+ robotic arm were analyzed.The joint coordinate system was established based on the actual robotic arm.By combining the D-H parameter method with the actual robotic arm parameters,the D-H parameter table was obtained,and the forward and inverse kinematic equations were derived.This clarified the transformation relationship between the robotic arm’s joint space and Cartesian space.Finally,the accuracy of the established kinematic model was verified using the Matlab Robotics Toolbox.(2)For obstacle avoidance planning of the robotic arm in a static environment,an improved Rapidly-exploring Random Tree(RRT)algorithm based on the cellular decomposition method is proposed.Firstly,in the initial stage of the algorithm,the map is divided into feasible regions and obstacle regions using the cellular decomposition method.Then,based on the adjacency relationships between regions,the selection of random sampling points is restricted to neighboring regions until reaching the region where the target point is located.Finally,the obtained path is optimized to improve the issue of excessive turning points in the path.(3)For obstacle avoidance planning of the robotic arm in a dynamic environment,an improved Artificial Potential Field(APF)method is proposed.Building upon the traditional APF method,a leapfrog search algorithm is introduced to effectively address the problem of getting stuck in dangerous regions during the planning process,which leads to planning failure.A 3rd-degree uniform B-spline function is employed to further smooth and optimize the final path,enabling the robotic arm to stably and efficiently complete the task while satisfying its own kinematic constraints.Two-dimensional and three-dimensional complex environments are constructed in Matlab,and obstacle avoidance path planning simulations are conducted for the traditional APF method as well as other improved algorithms,validating the effectiveness of the new algorithm.(4)In the ROS(Robot Operating System)environment,the Move It package is used for programming the robotic arm motion planning program,and simulation experiments are conducted in the Rviz platform.The Solidworks 3D model of the Robot Anno V6+ six-degree-of-freedom robotic arm is utilized to generate a universal URDF model in ROS,and the entire robotic arm system is set up accordingly.The Move It package is utilized to configure the motion planning,and in Rviz,a simulated environment with different obstacle distributions is created to test the performance of the proposed algorithm in path planning and obstacle avoidance processes.
Keywords/Search Tags:RobotAnno V6+ robot arm, path planning, dynamic obstacles, RRT, artificial potential field, jump point search method, ROS
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