In order to improve the speed of motion planning, this paper proposes an improved RRTConnect algorithm (SDPS-RRTConnect) based on sparse dead point saved strategy. Combining sparse expansion strategy and dead point saved strategy, the algorithm can reduce the number of collision detection, fast convergence, avoid falling into local minimum, and ensure the completeness of search space. The algorithm is simulated in different environments. The results show that in complex environments, the sparse dead point saved strategy plays a good effect. In simple environments, the greedy connection strategy works well. Compared with the standard RRT algorithm, the standard RRTConnect algorithm, and the SDPS-RRT algorithm, the SDPS-RRTConnect algorithm has the shortest planning time, and it is suitable for both simple and complex environments. The 500 experiments show that the algorithm has strong robustness. The actual robot experiments show that the path planned by SDPS-RRTConnect algorithm is effective.
In recent years, dual-arm robots have attracted more and more attention due to their advantages such as strong cooperation ability and high flexibility. With the improvement of real-time requirement of dual-arm cooperation, the inverse kinematics solution of robot becomes a key problem to be solved urgently. To solve the time-consuming problem of inverse kinematics of robot arm, a closed inverse kinematics solution algorithm for humanoid dual-arm robot was proposed. The effectiveness of the algorithm was verified by simulation.
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