Configuration information acquisition and matching are two important steps in the self-reconfiguringprocess of self-reconfigurable robots.The process of configuration information acquisition was introduced,and a self-reconfiguring configuration matching strategy based on graded optimization mechanism was pro-posed.The first-grade optimization was to search common connection between matching scheme and goalconfiguration.The second-grade optimization,whose object function was constructed in terms of configu-ration connectivity,was to search common topology according to the results of the first-grade optimization.The entire process of configuration information acquisition and matching was verified by an experiment andgenetic algorithm (GA).The result shows the accuracy of the configuration information acquisition andthe effectiveness of the configuration matching method.
For a self-reconfigurable robot,how to metamorphose to adapt itself to environment is a difficultproblem.To solve this problem,a new relative orientation model which describes modules and their sur-rounding grids was given,a module motion rules database which enables the robot to avoid obstacles wasestablished,and finally a three-layer planner based on dynamic meta-modules was developed.The first-layer planner designates the category of each module in robot by evaluation functions and picks out themodules in dynamic recta-modules.The second-layer planner plans the dynamic recta-module path ac-cording to output parameters of the first-layer planner.The third-layer planner plans the motion of themodules in dynamic meta-module using topology variation oriented methods.To validate the efficiency ofthe three-layer planner,two simulations were given.One is the simulation of a single dynamic meta-mod-ule,the other is the simulation of planning with an initial configuration composed of 8 modules in compli-cated environment.Results show that the methods can make robot with any initial configuration movethrough metamorphosis in complicated environment efficiently.
