Mobile Robot's Path Planning Based On Improved Ant Colony Algorithms

The path planning for mobile robot plays an important role in the field of robotic. It is arising many scholars' interesting and it's already got a series of achievements in this field. At present, there are many advanced algorithms used to solve this optimal problem. However, for those algorithms, it is very difficult to solve some path planning problems containing certain constraint conditions due to the complex background environment. According to different environment on robots'movement choosing right path planning algorithms efficiently is a important research topic. ant colony algorithms is found in the 1990's, it is developing rapidly on path planning According to the present condition of the studying and the intellective and bionics tendency of the field's development, this paper presents a new path planning approach based on the improved ant colony algorithm. The following is the main works:Firstly, this paper introduces the common used planning algorithms for intelligent mobile robot in the country and abroad, and the researching situation is elaborated and summarized, it also analyzing advantages and defaults of each algorithm which made an important basis for the research on mobile robot path planning in the thesis.Secondly, the mobile robot system's hardware configuration is studied. Sensors module and wireless communication module is introduced. Control procedures of mobile robot based on two-level architecture: including PC in high level and DSP in low level. According demos with robots, Foundation class library with mobile robot is expatiated systemically.Thirdly, Grid is used to model the robot global path planning workspace. For convexification with two times, the state of basic ant colony algorithms fell into colony algorithms is reduced. Optimum performance, time performance and robust performance of improved ant colony algorithms are compared with those of basic ant colony algorithms. The simulation results showed that improved algorithms'performances are superior to basic algorithms'.Finally, based on mobile robot infrastructure and beeline trajectory tracking experiment,global path planning with improved ant colony algorithms is presented. The experiment results showed that improved algorithms'operating speed and robustness is improved, adaptability of ant colony algorithms on mobile robot path planning is enhanced.