In this paper, the kinematic path planning of a special hyper-redundant manipulator with lockable joints is studied. In this manipulator the extra cables are replaced by a locking system to reduce weight of the structure and the number of actuators. In this research, the particle swarm optimization is used for path planning. In addition, the kinematic constraints such as joint limits are considered. In the first part of this paper, the minimum switch path planning is solved. This kind of path planning will decrease the vibration and energy consumption and increase the accuracy of manipulator. To validate the result, an innovative test is designed. According to the test results, the performance of the proposed method is shown. In the second part of the paper, the minimum time trajectory planning is studied based on the bang-bang theory. The inverse kinematic of manipulator is calculated such that the sum of legs length changes is decreased. Finally, the result of trajectory planning obtained from particle swarm optimization are compared to simulated annealing optimization results to confirm the performance and correctness of results.