Systems design and implementation with jerk-optimized trajectory generation for UAV calligraphy

Phang, Swee King; Lai, Shupeng; Wang, Fei; Lan, Menglu; Chen, Ben M.

doi:10.1016/j.mechatronics.2015.06.006

Cited by 30 publications

(12 citation statements)

References 36 publications

(33 reference statements)

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“…In this mode, we initially minimize the jerk to obtain a trajectory which facilitates adequate tag acquisition by (implicitly) minimizing motion blur on the vision-based target detection. Such minimum jerk approach produces smooth trajectories and has a long heritage for planning MAV paths [5,24,25]. As the UAV approaches the target, the effect of disturbances increases so the planner minimizes the time spent in the turbulent area.…”

Section: B Dynamic Landing Plannermentioning

confidence: 99%

Autonomous MAV Landing on a Moving Platform with Estimation of Unknown Turbulent Wind Conditions

Paris

Tagliabue

How

2021

AIAA Scitech 2021 Forum

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This paper presents an autonomous landing of a micro aerial vehicle (MAV) on a moving platform immersed in turbulent wind conditions. We estimate the 3D wind vector acting on the vehicle using a model-based and a deep learning-based approach. A disturbance-aware boundary layer sliding controller then uses this estimation to generate a control input that provides trajectory tracking guarantees in the presence of unknown, but bounded disturbances. The approach presented integrates our previous works on control and estimation, and we show its performance in a challenging setting. The experiments show that our methods enable fast landing on a moving platform in turbulent, unknown wind conditions.

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Section: B Dynamic Landing Plannermentioning

confidence: 99%

Autonomous MAV Landing on a Moving Platform with Estimation of Unknown Turbulent Wind Conditions

Paris

Tagliabue

How

2021

AIAA Scitech 2021 Forum

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“…Jerk in technical pain [177]; 20. Jerk in unmanned aerial vehicle (UAV) [11,[178][179][180][181][182][183][184][185][186]; and 21. Jerk in vehicles (ride comfort [12,15,17,19,25,45,95,98-106,108,109,111-113,115,118-121, 123-125,127-131], anti-jerk controller design [95,[98][99][100][101][102]109,111,119,120,130], autonomous vehicles [12,16,114,123,187,188], and other [111,187,[189][190][191][192][193][194][195].…”

Section: Categorisation Of Jerk Applicationsmentioning

confidence: 99%

Jerk within the Context of Science and Engineering—A Systematic Review

et al. 2020

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Rapid changes in forces and the resulting changes in acceleration, jerk and higher order derivatives can have undesired consequences beyond the effect of the forces themselves. Jerk can cause injuries in humans and racing animals and induce fatigue cracks in metals and other materials, which may ultimately lead to structure failures. This is a reason that it is used within standards for limits states. Examples of standards which use jerk include amusement rides and lifts. Despite its use in standards and many science and engineering applications, jerk is rarely discussed in university science and engineering textbooks and it remains a relatively unfamiliar concept even in engineering. This paper presents a literature review of the jerk and higher derivatives of displacement, from terminology and historical background to standards, measurements and current applications.

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“…Quadcopters are known for their highly nonlinear motion dynamics and so nonlinear models are indispensable. A common practical procedure is to linearize the nonlinear quadcopter dynamic model around a hovering mode (the operating steady-state) since, due to its symmetric frame, the linear dynamic model becomes somewhat simplified, and therefore, it is easier to design linear controllers; see ( [26][27][28][29][30], [39]). A drawback of such linearized model, however, is the operation in the immediate proximity of the linearizing state point (hovering mode) must be secured.…”

Section: T mentioning

confidence: 99%

“… Namely, the 6-DoF flying object could not be controlled with a single loop, and thus, a cascade control system is indispensable. In order to recover and keep vicinity of the aforementioned hovering mode, there are various control approaches developed under the cascade control concept, where the inner loop ought to be designed at least 5 times faster than the outer loop; see [27]- [30], [39].…”

Section: T mentioning

confidence: 99%

Stability of Nonlinear Descriptor Systems and Applications to Stabilization of Quadcopters

Bunjaku¹,

Stefanovski²,

Dimirovski³

2020

ACTA POLYTECH HUNG

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In this paper, new sufficient Lyapunov-like stability conditions and new Lyapunov-like, stabilizability conditions for nonlinear descriptor systems, with control, are presented along with their applications to quadcopter's flight stabilization. Most of these results are rather practical because they do not need solving nonlinear differential equations and nonlinear algebraic equations. Thus, the usage of these new results requires only the differentiation of functions. The numerical simulation results prove that the stabilization of the quadcopter is improved, in comparison with pure tracking control.

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Systems design and implementation with jerk-optimized trajectory generation for UAV calligraphy

Cited by 30 publications

References 36 publications

Autonomous MAV Landing on a Moving Platform with Estimation of Unknown Turbulent Wind Conditions

Autonomous MAV Landing on a Moving Platform with Estimation of Unknown Turbulent Wind Conditions

Jerk within the Context of Science and Engineering—A Systematic Review

Stability of Nonlinear Descriptor Systems and Applications to Stabilization of Quadcopters

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