Integration and Scheduling of Core Modules

In this chapter, a theoretical framework of brain-inspired intelligence is finally established in synergetical implementation of the vision–brain, including the geospatial modeling (seen), the robotic integrated intelligence (understanding) and the brain-inspired decision system (response). For a better interpretation of these core modules and for the convenience of readers’ understanding, the planetary exploration wheeled mobile robot is employed as an example and double-layer human–machine interfaces are utilized to display how the vision–brain will function in the future. Based on the vision–brain hypothesis and the results of Chaps. 3 and 4, in order to solve a robot path-planning problem and decide an optimal path to the targets or regions of interest, obstacle avoidance through a geospatial modeling is essentially necessary. Scheduling of core modules can be further interpreted as a hierarchical cooperation process of the vision–brain with other technological modules. Alternatively, the architecture of a vision–brain can be interpreted as three-layer intelligence—seen, understanding and response. Such multilayer architecture of brain-inspired intelligence makes a better chance for extending related technologies, supporting the R&D of tele-operated machine intelligence, and has a universal significance for any future intelligent systems, especially for improving the cognition efficiency and robustness of a machine brain through a scene understanding.