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 work, 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.
Based on our prior work, we present a fast geometric solution to the configuration space computation for truss robots with the physical sizes of mechanical components being considered so that motions of nodes can be planned efficiently by sampling-based motion planners, and other physical and hardware constraints can be easily incorporate to validate sampled motions, including actuator lengths, the collision avoidance, the stability constraint, and the manipulability maintenance. A new sample set generation algorithm is introduced to span every enclosed subspace as much as possible so that an efficient graph search algorithm can be applied to quickly compute a set of topology reconfiguration actions to alter the truss topology. Because of the truss stability constraint, we can apply our motion planning approach to locomote a truss by simply sending a rolling direction to achieve a non-impact rolling locomotion behavior.
Publications
- C. Liu, S. Yu, and M. Yim, “Motion planning for variable topology trusses: reconfiguration and locomotion,” Ieee transactions on robotics, pp. 1-20, 2022.
[Bibtex]@ARTICLE{CL:SY:MY:22, author = {Liu, Chao and Yu, Sencheng and Yim, Mark}, journal = {IEEE Transactions on Robotics}, title = {Motion Planning for Variable Topology Trusses: Reconfiguration and Locomotion}, year = {2022}, volume = {}, number = {}, pages = {1-20}, doi = {10.1109/TRO.2022.3228400} }
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