Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach

Sánchez-López, José Luis; Castillo-Lopez, Manuel; Olivares-Méndez, Miguel A.; Voos, Holger

doi:10.1007/s10846-020-01203-2

Cited by 10 publications

(11 citation statements)

References 54 publications

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“…the position of the center of the mass of a UAV in the world frame, ̇ ∈ ℝ 3 the velocity of the center of the mass of a UAV in the world frame, ̈ ∈ ℝ 3 the acceleration of the center of a mass of a UAV in the world frame, ∈ SO(3) ⊂ ℝ 3×3 the rotation matrix from the body frame of a UAV to the world frame,…”

Section: Multirotor Aerial Vehicle Dynamics Modelmentioning

confidence: 99%

“…However, UAVs, specifically multirotor helicopters, are still under intensive investigation in a wide range of research on all levels of their technological tree. Research in UAVs is still being carried in underlying fields of dynamic system modeling [1], automatic feedback control [2], and trajectory optimization [3]. These fields are vital for understanding and for realizing autonomous flying machines capable of supporting research in higher-level sub-systems for autonomous navigation through an environment, for remote sensing, and for multi-agent systems.…”

Section: Introductionmentioning

confidence: 99%

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The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

Baca,

Petrlik,

Vrba

et al. 2020

Preprint

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We present a multirotor Unmanned Aerial Vehicle (UAV) control and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments, including outdoor-indoor transitions and the execution of redundant estimators for backing up unreliable localization sources. Two feedback control designs are presented: one for precise and aggressive maneuvers, and the other for stable and smooth flight with a noisy state estimate. The proposed control and estimation pipeline are constructed without using the Euler/Tait-Bryan angle representation of orientation in 3D. Instead, we rely on rotation matrices and a novel heading-based convention to represent the one free rotational degree-of-freedom in 3D of a standard multirotor helicopter. We provide an actively maintained and well-documented open-source implementation (http://github.com/ctu-mrs/mrs_uav_system), including realistic simulation of UAVs, sensors, and localization systems. The proposed system is the product of years of applied research on multi-robot systems, aerial swarms, aerial manipulation, motion planning, and remote sensing. All our results have been supported by real-world system deployment that subsequently shaped the system into the form presented here. In addition, the system was utilized during the participation of our team from the Czech Technical University in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions, and also in the DARPA Subterranean challenge. Each time, our team was able to secure top places among the best competitors from all over the world. On each occasion, the competitions and challenges has motivated the team to improve the system and to gain a great amount of high-quality experience within tight deadlines.

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Section: Multirotor Aerial Vehicle Dynamics Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

Baca,

Petrlik,

Vrba

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Appropriate path planning is the foundation of efficient and stable movements of manipulators, which is also one of the significant issues in robotics. Therefore, path planning can be applied in various kinds of fields, such as the automobile [2,3], aerospace [4,5] and agriculture industries [6].…”

Section: Introductionmentioning

confidence: 99%

Optimal Trajectory Planning for Manipulators with Efficiency and Smoothness Constraint

Wang

Chi

et al. 2023

Electronics

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Path planning to generate an appropriate time sequence of positions for a complex trajectory is an open challenge in robotics. This paper proposes an optimization method with the integration of an improved ant colony algorithm and a high-order spline interpolation technique. The optimization process can be modelled as the travelling salesman problem. The greatest features of this method include: (1) automatic generation for complex trajectory and a new idea of selecting the nearest start point instead of using the traditional way of human operation; (2) an optimized motion sequence of the manipulator with the shortest length of the free-load path improves efficiency by nearly 65% and (3) trajectories both in Cartesian space and joint space are interpolated with good smoothness to reduce shocks and vibrations. Simulations and experiments are conducted to demonstrate the good properties of this method.

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“…Therefore, it is essential to develop fully autonomous multi-rotor UAVs that can collaborate with ground-based robots to perform more complex tasks [5,6]. In this case, especially during the takeoff and landing phases, high-precision vehicle position and attitude estimation and motion planning are required [7,8].…”

Section: Introductionmentioning

confidence: 99%

An Autonomous Tracking and Landing Method for Unmanned Aerial Vehicles Based on Visual Navigation

Wang,

Ma,

Zhu

et al. 2023

Drones

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In this paper, we examine potential methods for autonomously tracking and landing multi-rotor unmanned aerial vehicles (UAVs), a complex yet essential problem. Autonomous tracking and landing control technology utilizes visual navigation, relying solely on vision and landmarks to track targets and achieve autonomous landing. This technology improves the UAV’s environment perception and autonomous flight capabilities in GPS-free scenarios. In particular, we are researching tracking and landing as a cohesive unit, devising a switching plan for various UAV tracking and landing modes, and creating a flight controller that has an inner and outer loop structure based on relative position estimation. The inner and outer nested markers aid in the autonomous tracking and landing of UAVs. Optimal parameters are determined via optimized experiments on the measurements of the inner and outer markers. An indoor experimental platform for tracking and landing UAVs was established. Tracking performance was verified by tracking three trajectories of an unmanned ground vehicle (UGV) at varying speeds, and landing accuracy was confirmed through static and dynamic landing experiments. The experimental results show that the proposed scheme has good dynamic tracking and landing performance.

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Trajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach

Cited by 10 publications

References 54 publications

The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

Optimal Trajectory Planning for Manipulators with Efficiency and Smoothness Constraint

An Autonomous Tracking and Landing Method for Unmanned Aerial Vehicles Based on Visual Navigation

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