The Reconfigurable Aerial Robotic Chain: Shape and Motion Planning
This work addresses the challenge of navigating complex, obstacle-filled spaces for aerial robotic systems, offering incremental improvements in planning efficiency.
The paper tackles the motion planning problem for a reconfigurable aerial robotic chain, achieving fast collision-free pathfinding in constrained environments through a library of optimized configurations and probabilistic shape sampling.
This paper presents the design concept, modeling and motion planning solution for the aerial robotic chain. This design represents a configurable robotic system of systems, consisting of multi-linked micro aerial vehicles that simultaneously presents the ability to cross narrow sections, morph its shape, ferry significant payloads, offer the potential of distributed sensing and processing, and allow system extendability. We contribute an approach to address the motion planning problem of such a connected robotic system of systems, making full use of its reconfigurable nature, to find collision free paths in a fast manner despite the increased number of degrees of freedom. The presented approach exploits a library of aerial robotic chain configurations, optimized either for cross-section size or sensor coverage, alongside a probabilistic strategy to sample random shape configurations that may be needed to facilitate continued collision-free navigation. Evaluation studies in simulation involve traversal of constrained and obstacle-laden environments, having narrow corridors and cross sections.