Team NimbRo at MBZIRC 2017: Fast landing on a moving target and treasure hunting with a team of micro aerial vehicles

Beul, Marius; Nieuwenhuisen, Matthias; Quenzel, Jan; Roşu, Radu Alexandru; Horn, Jannis; Pavlichenko, Dmytro; Houben, Sebastian; Behnke, Sven

doi:10.1002/rob.21817

Cited by 36 publications

(24 citation statements)

References 36 publications

(48 reference statements)

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“…Figure 17 shows an image of one of our simulations. The simulation is based on Gazebo and it uses the Software-In-The-Loop (SITL) framework of PX4, 12 which allows us to also simulate the autopilot firmware with the rest of the system. The main objective is to test extensively the multi-UAV architecture without risking the actual platforms, in order to ease the integration of all software functionalities.…”

Section: A Simulation Experimentsmentioning

confidence: 99%

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Experimental Evaluation of a Team of Multiple Unmanned Aerial Vehicles for Cooperative Construction

et al. 2021

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This article presents a team of multiple Unmanned Aerial Vehicles (UAVs) to perform cooperative missions for autonomous construction. In particular, the UAVs have to build a wall made of bricks that need to be picked and transported from different locations. First, we propose a novel architecture for multi-robot systems operating in outdoor and unstructured environments, where robustness and reliability play a key role. Then, we describe the design of our aerial platforms and grasping mechanisms to pick, transport and place bricks. The system was particularly developed for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC), where Challenge 2 consisted of building a wall cooperatively with multiple UAVs. However, our approach is more general and extensible to other multi-UAV applications involving physical interaction, like package delivery. We present not only our results in the final stage of MBZIRC, but also our simulations and field experiments throughout the previous months to the competition, where we tuned our system and assessed its performance. Multirobot systems, unmanned aerial vehicles, construction. INDEX TERMS

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Section: A Simulation Experimentsmentioning

confidence: 99%

“…We used two UAVs not to overload the simulation. The results are 12 https://github.com/PX4/sitl_gazebo presented in Table 1. No errors (i.e., crashes) occurred during pick operations, and UAVs kept trying until the brick was successfully picked.…”

Section: A Simulation Experimentsmentioning

confidence: 99%

Experimental Evaluation of a Team of Multiple Unmanned Aerial Vehicles for Cooperative Construction

et al. 2021

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“…The attitude loop directly adopts the Pixhawk Autopilot including a PID controller for tracking. Research groups in other institutions have also studied the autonomous landing of a multirotor using the MPC method, including the University of Bonn [25], ETH Zurich [26] and the Czech Technical University in Prague [27], among others. In [28], a nonlinear MPC is proposed to guide the quadrotor to land on a maneuvering inclined platform, which includes an objective function that can ensure the position, speed, and attitude deviations in the terminal are minimized.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Landing of a Quadrotor on a Moving Platform via Model Predictive Control

Guo

Tang²,

Wang

et al. 2022

Aerospace

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Landing on a moving platform is an essential requirement to achieve high-performance autonomous flight with various vehicles, including quadrotors. We propose an efficient and reliable autonomous landing system, based on model predictive control, which can accurately land in the presence of external disturbances. To detect and track the landing marker, a fast two-stage algorithm is introduced in the gimbaled camera, while a model predictive controller with variable sampling time is used to predict and calculate the entire landing trajectory based on the estimated platform information. As the quadrotor approaches the target platform, the sampling time is gradually shortened to feed a re-planning process that perfects the landing trajectory continuously and rapidly, improving the overall accuracy and computing efficiency. At the same time, a cascade incremental nonlinear dynamic inversion control method is adopted to track the planned trajectory and improve robustness against external disturbances. We carried out both simulations and outdoor flight experiments to demonstrate the effectiveness of the proposed landing system. The results show that the quadrotor can land rapidly and accurately even under external disturbance and that the terminal position, speed and attitude satisfy the requirements of a smooth landing mission.

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“…Also some researchers utilize the the gripper [9,10] as the manipulating device, but the workspace is limited while too small distance between MAR and ground will lead to severe ground effect. In the robot competition named MBZIRC 2017, rigid rods are adopted for the picking device by some teams [11,12] while the workspace is still not big enough. A parallel mechanism and an electromagnetic end-effector are used to realize the building in MBZIRC 2020 [13].…”

Section: Introductionmentioning

confidence: 99%

Modeling and control of a hexacopter with a passive manipulator for aerial manipulation

Deng

et al. 2021

Complex Intell. Syst.

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In this paper, a multi-propeller aerial robot with a passive manipulator for aerial manipulation is presented. In order to deal with the collision, external disturbance, changing inertia, and underactuated characteristic during the aerial manipulation, an adaptive trajectory linearization control (ATLC) scheme is presented to stabilize the multi-propeller aerial robot during the whole process. The ATLC controller is developed based on trajectory linearization control (TLC) method and model reference adaptive control (MRAC) method. The stability of the proposed system is analyzed by common Lyapunov function. Numerical simulations are carried out to compare the ATLC with TLC controller facing collision, external disturbance and changing inertia during an aerial manipulation. Experimental results prove that the developed robot can achieve aerial manipulation in the outdoor environment.

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Team NimbRo at MBZIRC 2017: Fast landing on a moving target and treasure hunting with a team of micro aerial vehicles

Cited by 36 publications

References 36 publications

Experimental Evaluation of a Team of Multiple Unmanned Aerial Vehicles for Cooperative Construction

Experimental Evaluation of a Team of Multiple Unmanned Aerial Vehicles for Cooperative Construction

Autonomous Landing of a Quadrotor on a Moving Platform via Model Predictive Control

Modeling and control of a hexacopter with a passive manipulator for aerial manipulation

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