Trajectory Planning And Pose Measurement Of Moon-soil Sampling Robotic Arm And End-effector

The moon-soil sampling robotic arm and end-effector installed in space lander isthe essential device to gather moon-soil. The robotic arm composed by waist joint,shoulder joint, elbow joint and wrist joint have four degrees of freedom. theend-effector can complete the sampling task through adjusted the position andorientation by the robotic arm. The whole task is composed by the task from folded stateto expanded state, the task of digging moon-soil, the task of transferring sample. At thewhole process of task, the robotic arm and the end-effector are not allowed to contactwith the moon-rock and the space lander, and the end-effector can be transferred to therecycling containers accurately.In the case of knowing the basic configuration of the robotic arm, though themotion analysis and the mechanical analysis, we can get the joint angle and the jointmoment when it move along the given trajectory. The energy consumption functionestablished by joint angle and joint moment, the global condition number, the massfunction and the workspace function make up the objective function. Through gettingthe minimum value of objective function by genetic algorithms, we can achieve theoptimization of the robotics arm.According to the requirements of avoiding obstacles, at the process of sampling,we should make sure that the robotic arm and the end-effector are not contact with themoon-rock. Because we can’t know the location of moon-rock, we use the artificialpotential field method belonged to the local path planning method to plan the trajectory.At the process of transferring sample, we should make sure that the robotic arm and theend-effector are not contact with the space lander. The arm’s base is stationary relativeto the lander. through the kinematics, we can get the arm’s position and orientation. weuse A*algorithm belonged to the local path planning method to plan the trajectory.The robotics arm should complete the whole task through least possible time andleast possible energy consumption. For each track point, we can get joint angle byinverse-kinematics. For each joint, we use B-Splines to connect the joint angles. At theconstraints of angle, angle velocity, angle acceleration, we complete the optimization ofB-Splines by genetic algorithms. Above all, we get the time optimal B-Splines.We use the industrial robots connecting with nylon rod to execute insertion task toimitate the process of transferring sample. Through measuring the nylon rod’s positionand orientation by laser tracker, we conduct error analysis to insertion task to get themaximum error. We place some obstacles within the robot’s workspace, and plan thetrajectory with the artificial potential field method and A*algorithm, to verify thecorrectness of avoiding-obstacles algorithms.