Abstract: In order to complete the robotic peg-in-hole assembly task in unstructured environment, a DDPG (deep deterministic policy gradient) based variable parameter admittance control algorithm integrated with fuzzy reward mechanism is proposed to improve the assembly efficiency in unknown environment. The mechanical model of contact state for peg-in-hole assembly is established, and the peg-in-hole assembly mechanism is studied, to guide the formulation of robotic assembly strategy. The compliant peg-in-hole assembly is realized based on the admittance controller, whose optimal parameters are online identified by DDPG algorithm. The fuzzy rules are introduced into the reward function to avoid falling into the local optimal assembly strategy, which improves the assembly quality. Finally, assembly experiments are carried out on holes of 5 different diameters, and compared with the results of the fixed parameter admittance model. The experimental results show that the proposed algorithm is obviously superior to the fixed parameter model, and the assembly operation can be completed within 10 steps after the algorithm convergence. The proposed algorithm is expected to meet the requirements of autonomous manipulation in unstructured environment.