Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117724
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Title: Bidirectional thrust control for quadrotor safety
Authors: Zhao, Y 
Lyu, M 
Li, C 
Huang, H 
Issue Date: Mar-2026
Source: IEEE robotics and automation letters, Mar. 2026, v. 11, no. 3, p. 2650-2657
Abstract: Quadrotors performing aerial tasks are vulnerable to sudden external disturbances, which may lead to instability, control loss, or even structural damage such as broken arms or frame failure. These threats are particularly critical during flight, where recovery opportunities are limited. To address this, we propose a bidirectional thrust control framework that improves mid-air impact resilience. A lightweight recurrent neural network (RNN)-attention module detects and evaluates external forces in real time. When the disturbance is mild, a model predictive control (MPC) + active disturbance rejection control (ADRC) controller ensures stability; when it nears a critical level, the system switches to a flipping recovery policy that exploits bidirectional thrust to regain balance. Experiments validate robustness and safety under sudden external disturbances.
Keywords: Aerial systems: applications
Machine learning for robot control
Robot safety
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE robotics and automation letters 
EISSN: 2377-3766
DOI: 10.1109/LRA.2026.3653327
Rights: © 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication Y. Zhao, M. Lyu, C. Li and H. Huang, 'Bidirectional Thrust Control for Quadrotor Safety,' in IEEE Robotics and Automation Letters, vol. 11, no. 3, pp. 2650-2657, March 2026 is available at https://doi.org/10.1109/LRA.2026.3653327.
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