A new hybrid navigation algorithm for mobile robots in environments with incomplete knowledge
Focusing on the navigation problem of mobile robots in environments with incomplete knowledge, a new hybrid navigation algorithm is proposed. The novel system architecture in the proposed algorithm is the main contribution of this paper. Unlike most existing hybrid navigation systems whose deliberative layers usually play the dominant role while the reactive layers are only simple executors, a more independent reactive layer that can guarantee convergence without the assistance of a deliberative layer is pursued in the proposed architecture, which brings two benefits. First, the burden of the deliberative layer is released, which is beneficial to guaranteeing real-time property and decreasing resource requirement. Second, some possible layer conflicts in the traditional architecture can be resolved, which improves the system stability. The convergence of the new algorithm has been proved. The simulation results show that compared with three traditional algorithms based on different architectures, the new hybrid navigation algorithm proposed in this paper performs more reliable in terms of escaping from traps, resolving conflicts between layers and decreasing the computational time for avoiding time out of the control cycle. The experiments on a real robot further verify the validity and applicability of the new algorithm.
hybrid navigation mobile robots incomplete knowledge system architecture bug algorithms