Mobile Robot Path Planning And Research In The Improved Artificial Immune Algorithm

Mobile robot system as a typical multi-agent system, it is provides a good experimentalplatform of the intelligent theory and integration of multiple technologies applications.Therefore, as an important factor in intelligent robots-path planning is very important.The main research topic is the content of the soccer robot research platform, The actualprocess and special state environment in soccer, complete soccer robot to find the target,obstacle actions such as avoidance. Solve the path planning process may be easy to fall intolocal optimal solution and the deadlock in traditional algorithm.Robot path planning is a very complex issue, not only to find a collision-free shortestpath, but also requires the path as smooth as possible and to meet certain security. This articleuse the soccer robot subject group of Xian university of science and technology as researchplatform, First introduced the composition and structure and software platform of soccerrobot,and focused on the transformation of power system, Second, describes the robot pathplanning traditional algorithm and intelligent planning algorithm, Based on the analysis of thecurrent advantages and disadvantages of various path planning algorithm, Thus proposed apath planning algorithm based on modified artificial immune mobile robot.For static path planning, using the grid method to establish the space mathematicalmodel, and then using the artificial potential field to establish the initial path population ofartificial immune algorithm, optimize the mutation operator, proposed a new affinity function,introduced vaccination, the immune mechanisms such as crossover and mutation, allowedbetter individuals to an earlier generation, Thus ensuring the convergence speed and diversityof the population, prevent premature convergence, improve the global search capability,Simulation results show that the method under the static environment have a good ability, caneffectively guarantee the efficiency and improve the quality of path planning.For dynamic path planning, using Two-dimensional Cartesian grid established mobile robot dynamic model of the environment, and then using artificial potential field algorithm tooptimize the initial population, By fitness function of the immune algorithm in a improvingstatic environment to assess individual. Compared by simulation, show that this algorithm forthe dynamic complexity environment of mobile robot path planning.At last, in a real soccer robot system experiment platform and in a real footballenvironment to authentication the improved artificial immune algorithm for path planning.Experiments show that: soccer robots in a variety of state conditions have shown a good lookfor obstacle avoidance and target effects, have demonstrated the superiority of the pathplanning algorithm, success in achieving the design goal of paper. Because the improvementsof power systems in both software and hardware platform of the soccer robot, so that ourschool’s robot soccer team in the national competition over the years has made outstandingachievements.