Truss robots are highly redundant parallel robotic systems and can be applied in a variety of scenarios. The variable topology truss (VTT) is a class of modular truss robot. As self-reconfigurable modular robots, variable topology trusses are composed of many edge modules that can be rearranged into various structures with respect to different activities and tasks. These robots are able to change their shapes by not only controlling joint positions which is similar to robots with fixed morphologies, but also reconfiguring the connections among modules in order to change their morphologies. Motion planning is the fundamental to apply a VTT robot, including reconfiguration to alter its shape, and non-impact locomotion on the ground. This problem for VTT robots is difficult due to their non-fixed morphologies, high dimensionality, the potential for self-collision, and complex motion constraints. In this paper, a new motion planning framework to dramatically alter the structure of a VTT is presented. It can also be used to solve locomotion tasks much more efficient compared with previous work. Several test scenarios are used to show its effectiveness.