HyCAR - A Robust Hybrid Control Architecture for Autonomous Robots.

摘要

This work presents a new hybrid architecture applied to autonomous mobile robot control HyCAR (Hybrid Control for Autonomous Robots). This architecture provides a robust control for robots as they become able to operate and adapt themselves to different environments and conditions. We designed this new hybrid control architecture, integrating the two main techniques used in robotic control (deliberative and reactive control) and the most important environment representation techniques (grids, geometric and topological maps), through a three-layer architecture approach (vital, functional and deliberative layers). To guarantee the robustness of our control system, we also integrated a localization module based on Monte Carlo localization method. This localization module possesses an important role in our control system, and supplies a solid base for the control and navigation of autonomous mobile robots. In order to validate our control architecture, a realistic simulator of mobile robots was implemented (SimRob3D) allowing the practical use of the proposed system. We implemented several three-dimensional environment models, as well as diverse sensorial and kinematics models found in actual robots. Our simulation results had demonstrated that the control system is perfectly able to determine the mobile robot position into a partially known environment, considering local or global localization, and also to determine if the robot needs to re-localize itself given an incorrect localization. In navigation tasks the robot was able to plan and follow self-generated trajectories in a dynamic environment, which can include several unexpected static and mobile obstacles. We also demonstrated that with the integration of topological and grid information we improved planning algorithm