A three-dimensional (3D) positioning and orientating method based on an adaptive parameter and adaptive mutation particle swarm optimization is proposed in this study to solve the 3D positioning and orientating problem in visible light communication. First, a hybrid 3D visible light positioning (VLP) model based on a ranging model in a complex environment is analyzed, and the positioning problem is transformed into an optimization problem of the joint probability density function. Second, an adaptive parameter and adaptive mutation particle swarm optimization method are designed by calculating the fuzzy closeness between the solution of the particle and the optimal solution of the population. Finally, the theoretical lower bound of the positioning and orientating error of the proposed 3D VLP model, called the Cramer-Rao lower bound (CRLB), is accurately analyzed using mathematical methods. The results show that the time complexity of the proposed algorithm is low, and the positioning and orientating errors are close to the CRLB. The average positioning and average orientating convergence errors of the proposed algorithm are 5.99 cm and 6.65°, respectively, which are significantly better than those of four other iterative-based VLP algorithms.