Robot path planning in uncertain dynamic environment is a hot issue in the field of Unmanned ground vehicle(UGV).Starting from the practical demands of UGV,we propose a novel dynamic obstacle avoidance algorithm based on Collision time histogram(CTH).Given current steering angle,an effective collision check model,which is called Collision check circles(CCC),is firstly calculated.The local environment information is then combined with CCC to generate the proposed CTH.The nonholonomic nature of the vehicle is embedded in this process.Finally,the proposed algorithm calculates the executing steering angle by considering both the CTH and the target point.Extensive experiments and comparisons are conducted to evaluate the performance of the proposed algorithm.Simulation experiments are firstly conducted to verify its feasibility.Furthermore,real-world experiment is conducted to verify its effectiveness.Experimental results demonstrate the practical value of the proposed algorithm. Robot path planning in uncertain dynamic environment is a hot issue in the field of Unmanned ground vehicle (UGV). Starting from the practical demands of UGV, we propose a novel dynamic obstacle avoidance algorithm based on Collision time histogram (CTH) .Given current steering angle, an effective collision check model (CCC), is to calculate the local environment information is then combined with CCC to generate the proposed CTH. Nonholonomic nature of the vehicle is embedded in this process. , the proposed algorithm calculates the the steering angle by both of CTH and the target point. Extensive experiments and comparisons are conducted to evaluate the performance of the proposed algorithm. Simulating experiments are conducted to verify its feasibility. Future, real-world experiment is conducted to verify its effectiveness. Experimental results demonstrate the practical value of the proposed algorithm.