Path planning is critical to the efficiency and fidelity of robot navigation. The solution of robot path planning is to seek a collision-free and the shortest path from the start node to target node. In this paper, we propose a new improved artificial fish swarm algorithm (IAFSA) to process the mobile robot path planning problem in a real environment. In IAFSA, an attenuation function is introduced to improve the visual of standard AFSA and get the balance of global search and local search; also, an adaptive operator is introduced to enhance the adaptive ability of step. Besides, a concept of inertia weight factor is proposed in IAFSA inspired by PSO intelligence algorithm to improve the convergence rate and accuracy of IAFSA. Five unconstrained optimization test functions are given to illustrate the strong searching ability and ideal convergence of IAFSA. Finally, the ROS (robot operation system) based experiment is carried out on a Pioneer 3-DX mobile robot; the experiment results also show the superiority of IAFSA.

In this paper, the weighted couple‐group consensus of continuous‐time heterogeneous multiagent systems with input and communication time delay is investigated. A novel weighted couple‐group consensus protocol based on cooperation and competition interaction is designed, which can relax the in‐degree balance condition. By using graph theory, general Nyquist criterion and Gerschgorin disc theorem, the time delay upper limit that the system may allow is obtained. The conclusions indicate that there is no relationship between weighted couple‐group consensus and communication time delay. When the agents input time delay, the coupling weight between the agents, and the systems control parameters are satisfied, the multiagent system can converge to any given weighted coupling group consistent state. The experimental simulation results verify the correctness of the conclusion.