Abstract: The forward kinematics problem of 6-SPS parallel manipulator can be transformed into an equivalent optimization problem and solved through numerical optimization methods. The artificial bee colony algorithm(ABC) is a meta-heuristic optimization method which mimics the foraging behavior of honey bee swarm. To the best of our knowledge, there is very little research work on ABC for forward kinematics problem of parallel manipulator. An improved artificial bee colony algorithm(IABC) is presented for computing numerical solutions to the forward kinematics problem of parallel manipulator. By changing nectar position multi-dimensionally in IABC algorithm, two strategies are combined for the employed bees, that is, DE/rand/1 differential operator is adopted as the main optimizing scheme, and genetic arithmetic crossover operator is used as auxiliary manner to enhance the diversity of the bee colony; while for the onlookers, the DE/best/2 differential operator is employed to find better solution in its vicinity. In additional, during the onlookers selection nectar sources phase, non-linear ranking selection is adopted to alleviate premature problem that caused by the super nectar sources in the colony. The experimental results of benchmark functions show that this IABC algorithm greatly improves both the optimal solution quality and the search solution reliability. Based on these, a 6-SPS parallel manipulator is used as an example, and then the proposed IABC is used to solve the forward kinematics problem. Numerical simulation results demonstrate the effectiveness of this algorithm to solve the forward kinematics problem of parallel manipulators.

Key words: 6-SPS parallel manipulator, Artificial bee colony, Differential evolution, Forward kinematics, Genetic operator