Autonomous Cooperative Transportation System involving Multi-Aerial Robots with Variable Attachment Mechanism
Koshi Oishi, Tomohiko Jimbo
TL;DR
The paper tackles the challenge of transporting unknown payloads larger than carrier aerial robots using an autonomous cooperative system that integrates hardware rails around the payload with a software stack for end-to-end operation. It combines Bayesian payload parameter estimation, information-theoretic formation selection, and controllability-based optimization to determine attachment positions, followed by flight control with a recalculated mixing matrix; key expressions include the posterior p(theta|z_i) = p(z_i|theta) p(theta) / sum_theta p(z_i|theta) p(theta) and the objective det(BB^T) for formation. Validation includes simulations and real-world experiments with eight robots carrying payloads around 3.2 kg and up to 1.76 m, showing that the optimized formation improves takeoff stability and flight performance across unknown payload shapes. This approach enables autonomous, scalable cooperative transportation without extensive pre-characterization and enhances safety and robustness in aerial payload transport.
Abstract
Cooperative transportation by multi-aerial robots has the potential to support various payloads and improve failsafe against dropping. Furthermore, changing the attachment positions of robots according payload characteristics increases the stability of transportation. However, there are almost no transportation systems capable of scaling to the payload weight and size and changing the optimal attachment positions. To address this issue, we propose a cooperative transportation system comprising autonomously executable software and suitable hardware, covering the entire process, from pre-takeoff setting to controlled flight. The proposed system decides the formation of the attachment positions by prioritizing controllability based on the center of gravity obtained from Bayesian estimations with robot pairs. We investigated the cooperative transportation of an unknown payload larger than that of whole carrier robots through numerical simulations. Furthermore, we performed cooperative transportation of an unknown payload (with a weight of about 3.2 kg and maximum length of 1.76 m) using eight robots. The proposed system was found to be versatile with regard to handling unknown payloads with different shapes and center-of-gravity positions.