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

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.

► We propose a bionic approach for modeling and acquiring human domain knowledge. ► We utilize and extend workflow (WF) as the human domain knowledge modeling tool. ► WF can effectively formalize human domain knowledge with great convenience. ► Our approach can remarkably improve the planning performance.