Hierarchical Markov Decision Based Path Planning for Palletizing Robot

Jiufu Liu, Zhengqian Wang, Zhe Chen, Zhong Yang, Zhisheng Wang, Chunsheng Liu

Abstract


On account of the complex application environment and the large number of uncertain conditions for the palletizing robot, we do path-planning for the multiple joints robot by the algorithm based on Hierarchical Markov Decision Process. First, according to the actual working environment, we set the range of the robot’s motion and select the conventional movement combination as the basic set of the robot’s behaviors. We can get the possible reward of various situations. We divide the state space in accordance with the location information of the obstacle space into a small number of state clusters, sub-level step by step to determine the precise trajectory of palletizing robots. We simulate 3D robot motion trajectory, including barrier-free and spherical obstacle conditions. Finally, experimental verification is carried out, the algorithm has been proved to control the compatible movements of each joint effectively and keep the error within the allowed range. The experiment results meet the requirement well.

 

DOI : http://dx.doi.org/10.11591/telkomnika.v12i3.3851

 


Keywords


Palletizing robot; path planning; Hierarchical Markov Decision Process; state clustering

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License