An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing t...An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing the second order Approximate Voronoi Boundary Network after adding virtual obstacles at joint-close grids. Thismethod embodies the network structure of the free area of environment with less nodes, so the complexity of pathplanning problem is reduced largely. An optimized path for mobile robot under complex environment is obtainedthrough the Genetic Algorithm based on the elitist rule and re-optimized by using the path-tightening method. Sincethe elitist one has the only authority of crossover, the management of one group becomes simple, which makes forobtaining the optimized path quickly. The Approximate Voronoi Boundary Network has a good tolerance to the im-precise a priori information and the noises of sensors under complex environment. Especially it is robust in dealingwith the local or partial changes, so a small quantity of dynamic obstacles is difficult to alter the overall character ofits connectivity, which means that it can also be adopted in dynamic environment by fusing the local path planning.展开更多
基金Project (60234030) supported by the National Natural Science Foundation of China
文摘An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing the second order Approximate Voronoi Boundary Network after adding virtual obstacles at joint-close grids. Thismethod embodies the network structure of the free area of environment with less nodes, so the complexity of pathplanning problem is reduced largely. An optimized path for mobile robot under complex environment is obtainedthrough the Genetic Algorithm based on the elitist rule and re-optimized by using the path-tightening method. Sincethe elitist one has the only authority of crossover, the management of one group becomes simple, which makes forobtaining the optimized path quickly. The Approximate Voronoi Boundary Network has a good tolerance to the im-precise a priori information and the noises of sensors under complex environment. Especially it is robust in dealingwith the local or partial changes, so a small quantity of dynamic obstacles is difficult to alter the overall character ofits connectivity, which means that it can also be adopted in dynamic environment by fusing the local path planning.
