Path planning is an important aspect of on machine verification (OMV), in this article, a strategy that combine global planning and local adjustment is put forward. Additionally, this paper proposes a new type of hybrid discrete particle swarm optimization algorithm, which absorbs the advantages of optical optimization algorithm, genetic algorithm and chaos optimization. The algorithm is used for global planning. This paper firstly introduce the principle of path planning and how to acquire the testing data; then explain the principle, steps and flow chart of the algorithm detailed; at last, the simulation research of the algorithm is carried on and is compared with ant colony algorithm. From the simulation result, it is obvious that the algorithm possesses the advantages of high search precision, favorable stability and fast convergence rate, it has a good practical application value.