BioDKM: Bio-inspired domain knowledge modeling method for humanoid delivery robots' planning

Authors:
Wanpeng Zhang;Tianjiang Hu;Jing Chen;Lincheng Shen
Affiliations:
College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, Hunan 410073, PR China;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, Hunan 410073, PR China;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, Hunan 410073, PR China;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, Hunan 410073, PR China
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

A bio-inspired human domain knowledge modeling method, BioDKM, is proposed and developed to make delivery robots think more humanly and act more effectively. This presented method focused on feasible fusion between artificial intelligent and bionics in the field of tasks planning or scheduling in delivery robots. BioDKM is designed and implemented with several components, in terms of human knowledge, workflow (WF), hierarchical task network (HTN), and planner. In detail, WF is utilized as the human domain knowledge modeling tool, because of its convenient applications, friendly user interface and explicit representation. Moreover, WF can effectively complement conventional HTN planning with great convenience to formalize human domain knowledge. Translation from WF to HTN is also considered and established to make task planning smooth. Finally, examples and simulations are carried out to validate the effectiveness of this proposed bio-inspired domain knowledge modeling method.