Truss robots are highly redundant parallel robotic systems that can be applied in a variety of scenarios. The variable topology truss (VTT) is a class of modular truss robots. As self-reconfigurable modular robots, a VTT is composed of many edge modules that can be rearranged into various structures depending on the task. These robots change their shape by not only controlling joint positions as with fixed morphology robots but also reconfiguring the connectivity between truss members in order to change their topology. The motion planning problem for VTT robots is difficult due to their varying morphology, high dimensionality, the high likelihood for self-collision, and complex motion constraints. In this article, a new motion planning framework to dramatically alter the structure of a VTT is presented. It can also be used to solve locomotion tasks that are much more efficient compared with previous work. Several test scenarios are used to show its effectiveness.

The Variable Topology Truss (VTT) is a new class of self-reconfigurable robot that can reconfigure its truss shape and topology depending on the task or environment requirements. Motion planning and avoiding self-collision are difficult as these systems usually have dozens of degrees-of-freedom with complex intersecting parallel actuation. There are two different types of shape changing actions for a VTT: geometry reconfiguration and topology reconfiguration. This paper focuses on the geometry reconfiguration actions. A new cell decomposition approach is presented based on a fast and complete method to compute the collision-free space of a node in a truss. A simple shape-morphing method is shown to quickly create motion paths for reconfiguration by moving one node at a time.