TY - GEN
T1 - Planning and Control for Active Morphing Tensegrity Aerial Vehicles in Confined Spaces
AU - Hao, Siyuan
AU - Tao, Zichen
AU - Gui, Yun
AU - Liu, Songyuan
AU - Shi, Jiaxu
AU - Cao, Xu
AU - Yang, Qingkai
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Morphing quadrotors are capable of adapting to constrained environments through geometric reconfiguration. However, existing systems are limited by mechanical complexity and rigid links, which affect both safety and performance in such environments. In this paper, we propose a strut-actuated tensegrity aerial vehicle that integrates shape adaptation with collision resilience. By incorporating deformable struts and a cable network, our vehicle enables real-time morphological adjustments during flight while maintaining stability. We present a hierarchical planning framework that ensures the entire vehicle remains confined within an icosahedral space, thereby guaranteeing full-body safety. An on-manifold Model Predictive Controller (MPC) is employed to track these optimized trajectories and compensate for inertia shifts during shape deformation. Simulation results validate the effectiveness of the proposed framework, demonstrating its capability to navigate in restricted scenarios.
AB - Morphing quadrotors are capable of adapting to constrained environments through geometric reconfiguration. However, existing systems are limited by mechanical complexity and rigid links, which affect both safety and performance in such environments. In this paper, we propose a strut-actuated tensegrity aerial vehicle that integrates shape adaptation with collision resilience. By incorporating deformable struts and a cable network, our vehicle enables real-time morphological adjustments during flight while maintaining stability. We present a hierarchical planning framework that ensures the entire vehicle remains confined within an icosahedral space, thereby guaranteeing full-body safety. An on-manifold Model Predictive Controller (MPC) is employed to track these optimized trajectories and compensate for inertia shifts during shape deformation. Simulation results validate the effectiveness of the proposed framework, demonstrating its capability to navigate in restricted scenarios.
UR - https://www.scopus.com/pages/publications/105029926313
U2 - 10.1109/IROS60139.2025.11246008
DO - 10.1109/IROS60139.2025.11246008
M3 - Conference contribution
AN - SCOPUS:105029926313
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 20138
EP - 20145
BT - IROS 2025 - 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, Conference Proceedings
A2 - Laugier, Christian
A2 - Renzaglia, Alessandro
A2 - Atanasov, Nikolay
A2 - Birchfield, Stan
A2 - Cielniak, Grzegorz
A2 - De Mattos, Leonardo
A2 - Fiorini, Laura
A2 - Giguere, Philippe
A2 - Hashimoto, Kenji
A2 - Ibanez-Guzman, Javier
A2 - Kamegawa, Tetsushi
A2 - Lee, Jinoh
A2 - Loianno, Giuseppe
A2 - Luck, Kevin
A2 - Maruyama, Hisataka
A2 - Martinet, Philippe
A2 - Moradi, Hadi
A2 - Nunes, Urbano
A2 - Pettre, Julien
A2 - Pretto, Alberto
A2 - Ranzani, Tommaso
A2 - Ronnau, Arne
A2 - Rossi, Silvia
A2 - Rouse, Elliott
A2 - Ruggiero, Fabio
A2 - Simonin, Olivier
A2 - Wang, Danwei
A2 - Yang, Ming
A2 - Yoshida, Eiichi
A2 - Zhao, Huijing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025
Y2 - 19 October 2025 through 25 October 2025
ER -