Regarding safety, obstacle avoidance has been considered as one of the most important features among ADAS systems for ground vehicles. However, the implementation of obstacle avoidance functions to commercial vehicles are still under progress. In this paper, we demonstrate a complete process of obstacle avoidance strategy for unmanned ground vehicle and has implemented the strategy on the self-developed Arduino based RC Car. In this process, the sensor LIDAR was employed to detect the obstacles on the fore-path. Based on the measured radar data, an optimized path would be automatically generated with accommodation of current car position, obstacle locations, car operation capability and global environmental restrictions. The path planning is updated in real time while new or changing obstacles being detected. The Arduino provides required control inputs to the RC Car to follow the pre-planned path and self-positioned by the observed obstacles data. This algorithm is validated by both the simulation results and practical implementation using RC car. The comparison will be discussed at the end of this paper. The successful implementation of the proposed strategy from simulation to RC car implementation demonstrates the feasibility of the similar methodology can be applied to commercial autonomous vehicle to equip obstacle avoidance system.