Geometrically Constrained Trajectory Optimization for Multicopters

Wang, Zhepei; Zhou, Xin; Xu, Chao; Gao, Fei

doi:10.1109/tro.2022.3160022

Cited by 119 publications

(57 citation statements)

References 71 publications

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“…the coefficient c will be calculated in an efficient way according to Theorem 2 in [12], and the degree k = 2s−1, s ∈ N + .…”

Section: B 6-dof Trajectory Optimizationmentioning

confidence: 99%

“…To deal with the constraints which may bring trouble to the optimization process, as shown in [12], we can use some techniques to handle them. The continuous-time constraints (13h) to (13k) can be softened as integral penalty terms and incorporated into the objective function; this method allows users to add any custom constraints for specific tasks rather than just those listed, which significantly enhances the extensibility of the framework.…”

Section: B 6-dof Trajectory Optimizationmentioning

confidence: 99%

“…To solve the unconstrained optimization problem (15) efficiently, we need to obtain the gradient of the objective function w.r.t the object variables. We first find the gradient w.r.t c and T, then the gradient w.r.t object variables ξ, q σ , and τ can be obtained using the method proposed in [12].…”

Section: Gradient Calculationmentioning

confidence: 99%

“…However, planning in R 3 only is not enough to exploit the obstacle avoidance potential of OMAVs. Recently, an optimization-based trajectory generation framework GCOPTER for multicopters was proposed in [12]. By constructing a class of piecewise polynomial trajectories called MINCO and using some constraint processing techniques, the framework well settles the contradiction between computational efficiency, extensibility, and solution quality.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, inspired by [12], [13], an optimizationbased collision-free 6-DoF trajectory generation framework considering the vehicle's overall shape and dynamics constraints is designed. Just input the SFC, then a collision-free smooth trajectory that satisfies the boundary conditions and dynamic constraints will be obtained efficiently.…”

Section: Introductionmentioning

confidence: 99%

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Collision-Free 6-DoF Trajectory Generation for Omnidirectional Multi-rotor Aerial Vehicle

Liu¹,

Quan²,

Liu³

et al. 2022

Preprint

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As a kind of fully actuated system, omnidirectional multirotor aerial vehicles (OMAVs) has more flexible maneuverability than traditional underactuated multirotor aircraft, and it also has more significant advantages in obstacle avoidance flight in complex environments. However, there is almost no way to generate the full degrees of freedom trajectory that can play the OMAVs' potential. Due to the high dimensionality of configuration space, it is challenging to make the designed trajectory generation algorithm efficient and scalable. This paper aims to achieve obstacle avoidance planning of OMAV in complex environments. A 6-DoF trajectory generation framework for OMAVs was designed for the first time based on the geometrically constrained Minimum Control Effort (MINCO) trajectory generation framework. According to the safe regions represented by a series of convex polyhedra, combined with the aircraft's overall shape and dynamic constraints, the framework finally generates a collision-free optimal 6-DoF trajectory. The vehicle's attitude is parameterized into a 3D vector by stereographic projection. Simulation experiments based on Gazebo and PX4 Autopilot are conducted to verify the performance of the proposed framework.

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“…the coefficient c will be calculated in an efficient way according to Theorem 2 in [12], and the degree k = 2s−1, s ∈ N + .…”

Section: B 6-dof Trajectory Optimizationmentioning

confidence: 99%

Section: B 6-dof Trajectory Optimizationmentioning

confidence: 99%

Section: Gradient Calculationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Collision-Free 6-DoF Trajectory Generation for Omnidirectional Multi-rotor Aerial Vehicle

Liu¹,

Quan²,

Liu³

et al. 2022

Preprint

View full text Add to dashboard Cite

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Unmanned Aerial Vehicle Mediated Drug Delivery for First Aid

et al. 2023

Self Cite

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Timely administration of key medications toward patients with sudden diseases is critical to saving lives. However, slow transport of first‐aid therapeutics and the potential absence of trained people for drug usage can lead to severe injuries or even death. Herein, an unmanned aerial vehicle (UAV)‐mediated first‐aid system for targeted delivery (uFAST) is developed. It allows unattended administration of emergency therapeutics‐loaded transdermal microneedle (MN) patches toward patients to relieve symptoms by a contact‐triggered microneedle applicator (CTMA). The implementability and safety of the uFAST for first aid is demonstrated in a severe hypoglycemic pig model by automatically delivering a glucagon patch with immediate and bioresponsive dual release modes. This platform technique may facilitate the development of UAV‐mediated first‐aid treatments for other sudden diseases.

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