Workspace Analysis for a 9-DOF Hyper-redundant Manipulator Based on An Improved Monte Carlo Method and Voxel Algorithm

In view of the importance of workspace to robotic configuration optimization, motion planning and control. This paper presents an improved Monte Carlo method and Voxel Algorithm to analyse the workspace of a 9-DOF hyper-redundant manipulator. By considering the problem that the traditional Monte Carlo method is not accurate enough when calculating the workspace of a robot, an improved Monte Carlo method is proposed. First, a seed workspace is generated by the traditional Monte Carlo method, and then the seed workspace is expanded based on the normal distribution with the standard deviation dynamically adjustable. By setting a precision threshold during the extension process, ensure that every region in the resulting workspace is accuray described. Based on the obtained workspace, a voxel algorithm is proposed to get the volume of the workspace, find the boundary part and the non-boundary part of the workspace, and the result error is reduced by continuously refining the boundary part. With the improved Monte Carlo method and voxel algorithm, the reachable workspace and dexterous workspace of the 9-DOF hyper-redundant manipulator are analyzed. The simulation results verify the validity and practicality of the method.