期刊
JOURNAL OF MECHANISMS AND ROBOTICS-TRANSACTIONS OF THE ASME
卷 13, 期 5, 页码 -出版社
ASME
DOI: 10.1115/1.4050998
关键词
control allocation; mobile robotics; multirotor vehicles; nonlinear control systems; dynamics; flying robots; mobile robots; theoretical kinematics
资金
- U.S. Army Research Office
- U.S. Army Special Operations Command [W911-NF-13-C-0045]
This paper presents a robust method for controlling the terrestrial motion of a bimodal multirotor vehicle that can roll and fly, demonstrating good performance and robustness under closed-loop control and showcasing a novel control allocation strategy that minimizes power consumption. The study explores factors influencing the mobility and controllability of the vehicle, comparing it to strictly flying multirotor vehicles and developing unique control and control allocation strategies based on its non-standard configuration. Experimental data collected also show the algorithm's ability to determine a thrust-minimizing solution in real-time.
This paper presents a robust method for controlling the terrestrial motion of a bimodal multirotor vehicle that can roll and fly. Factors influencing the mobility and controllability of the vehicle are explored and compared to strictly flying multirotor vehicles; the differences motivate novel control and control allocation strategies that leverage the non-standard configuration of the bimodal design. A fifth-order dynamic model of the vehicle subject to kinematic rolling constraints is the basis for a nonlinear, multi-input, multi-output, sliding mode controller. Constrained optimization techniques are used to develop a novel control allocation strategy that minimizes power consumption while rolling. Simulations of the vehicle under closed-loop control are presented. A functional hardware embodiment of the vehicle is constructed onto which the controllers and control allocation algorithm are deployed. Experimental data of the vehicle under closed-loop control demonstrate good performance and robustness to parameter uncertainty. Data collected also demonstrate that the control allocation algorithm correctly determines a thrust-minimizing solution in real-time.
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