Path Planning of Mobile Robot Based on Improved Artificial Immune Algorithm

The path planning of robot is a very complex problem, not only to find a shortest path without collision, but also requires the path as smooth as possible and meet certain safety. This paper first introduces the hardware structure and the software platform of robot soccer, and focus on the transformation of power system, then, introduces the traditional algorithm for robot path planning and intelligent planning algorithm, on the basis of the above work analyzed the advantages and disadvantages of the present various path programming method, thus put forward a kind of path planning of mobile robot improved artificial immune algorithm. According to the static path planning, spatial model is set up using the grid method, and the initial path populations need build artificial immune algorithm using artificial potential field method, the optimization of the mutation operator, puts forward new function of affinity, and the introduction of vaccination, crossover and mutation and other immune mechanism, which can generate good individuals earlier, thus ensuring the convergence rate of the algorithm and the diversity of population, prevent premature convergence, improves the global search ability. The simulation results show that, the method has good adaptability in a static environment, can effectively guarantee the quality and improve the efficiency of path planning and path planning.