Computationaly Simple Obstacle Avoidance Control Law for Small Unmanned Aerial Vehicles

Cieśluk, Jakub; Gosiewski, Zdzisław; Ambroziak, Leszek; Romaniuk, Slawomir

doi:10.1515/ama-2015-0010

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Onboard a marine vessel, it is not possible to set up a stationary GNSS reference station, and the corrections taken from land are difficult to download in the middle of the ocean, therefore this solution is more appropriate over land, and as mentioned earlier, it is simply unavailable under maritime conditions in the open sea. Another common approach is to support navigation algorithms with data from vision systems (Cieśluk et al, 2015). Such local navigation systems are based on a camera or a set of cameras supported by additional markers placed on the landing field (Xu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Experimental tests of hybrid VTOL unmanned aerial vehicle designed for surveillance missions and operations in maritime conditions from ship‐based helipads

Ambroziak

Ciężkowski

Wolniakowski

et al. 2021

Journal of Field Robotics

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This article presents research on a hybrid vertical take‐off and landing (VTOL) unmanned aerial vehicle (UAV) supported by a relative positioning system, enabling the deployment of autonomous missions from ship‐based helipads in maritime conditions. A crucial issue to be solved is ensuring precise positioning of the UAV relative to the landing pad in the take‐off and landing phases. To achieve this, an extended Kalman filter (EKF) is implemented on the UAV's onboard computer, which integrates the positioning data from the UAV's global navigation satellite system receiver and the positioning data of the landing pad broadcast by the landing pad navigation station (LNS). The EKF estimates both the absolute and relative position of the UAV, which are required for autonomous take‐off and landing on the moving landing pad. In unfavorable weather conditions, EKF also uses data from an optional local positioning system to keep the accuracy within the range 1–3 m. The research was concluded by experimental verification during a ferry cruise over the Baltic Sea. During the research, the VTOL UAV performed two fully autonomous flight missions at the range about 1 km from the moving ferry in international waters. Each of them ended with a successful landing back on the helipad with an accuracy matching its required level, which was already achieved in the previous research carried out in inland conditions. Data recorded during real flights confirm that the developed system, consisting of a hybrid VTOL UAV and a LNS, is ready to be utilized in autonomous missions at sea. Factors having a critical impact on the safety of use of the VTOL UAV in marine conditions were also identified, which were not observed during the research in inland conditions, and are related directly to turbulence around the landing pad.

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Section: Introductionmentioning

confidence: 99%

Experimental tests of hybrid VTOL unmanned aerial vehicle designed for surveillance missions and operations in maritime conditions from ship‐based helipads

Ambroziak

Ciężkowski

Wolniakowski

et al. 2021

Journal of Field Robotics

Self Cite

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“…Beside those two, there are also phase of arrival (POA) methods and methods that use a received signal strength indicator (RSSI). Lateration based positioning systems utilizing the following measurement technologies were built and successfully evaluated: magnetic field, ultrasonic, infrared, radio frequency (Wi-Fi, Bluetooth), and vision, which can also be used for obstacle avoidance applications [21], [22]. Popular ultrasonic based systems are characterized by high accuracy (up to 1 cm), yet still suffer of low range and significant interference from wind, and other sound sources [23].…”

mentioning

confidence: 99%

Trajectory optimization using learning from demonstration with meta-heuristic grey wolf algorithm

Pawlowski

Romaniuk

Kulesza

et al. 2022

IJRA

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<span>Nowadays, most robotic systems perform their tasks in an environment that is generally known. Thus, robot's trajectory can be planned in advance depending on a given task. However, as a part of modern manufacturing systems which are faced with the requirements to produce high product variety, mobile robots should be flexible to adapt to changing and diverse environments and needs. In such scenarios, a modification of the task or a change in the environment, forces the operator to modify robot's trajectory. Such modification is usually expensive and time-consuming, as experienced engineers must be involved to program robot's movements. The current paper presents a solution to this problem by simplifying the process of teaching the robot a new trajectory. The proposed method generates a trajectory based on an initial raw demonstration of its shape. The new trajectory is generated in such a way that the errors between the actual and target end positions and orientations of the robot are minimized. To minimize those errors, the grey wolf optimization (GWO) algorithm is applied. The proposed approach is demonstrated for a two-wheeled mobile robot. Simulation and experimental results confirm high accuracy of generated trajectories.</span>

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Cooperation of two heterogeneous mobile robots

Nikonowicz

Ambroziak

Kondratiuk

et al. 2018

AIP Conference Proceedings

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Computationaly Simple Obstacle Avoidance Control Law for Small Unmanned Aerial Vehicles

Cited by 5 publications

References 13 publications

Experimental tests of hybrid VTOL unmanned aerial vehicle designed for surveillance missions and operations in maritime conditions from ship‐based helipads

Experimental tests of hybrid VTOL unmanned aerial vehicle designed for surveillance missions and operations in maritime conditions from ship‐based helipads

Trajectory optimization using learning from demonstration with meta-heuristic grey wolf algorithm

Cooperation of two heterogeneous mobile robots

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