In many robot operation scenarios, the end-effector’s attitude constraints of movement are indispensable for the task process, such as robotic welding, spraying, handling, and stacking. Meanwhile, the inverse kinematics, collision detection, and space search are involved in the path planning procedure under attitude constraints, making it difficult to achieve satisfactory efficiency and effectiveness in practice. To address these problems, we propose a distributed variable density path planning method with attitude constraints (DVDP-AC) for industrial robots. First, a position–attitude constraints reconstruction (PACR) approach is proposed in the inverse kinematic solution. Then, the distributed signed-distance-field (DSDF) model with single-step safety sphere (SSS) is designed to improve the efficiency of collision detection. Based on this, the variable density path search method is adopted in the Cartesian space. Furthermore, a novel forward sequential path simplification (FSPS) approach is proposed to adaptively eliminate redundant path points considering path accessibility. Finally, experimental results verify the performance and effectiveness of the proposed DVDP-AC method under end-effector’s attitude constraints, and its characteristics and advantages are demonstrated by comparison with current mainstream path planning methods.