A simple visual navigation system for an UAV

Krajník, Tomáš; Nitsche, Matıas; Pedre, Sol; Přeučil, Libor; Mejail, Marta

doi:10.1109/ssd.2012.6198031

Cited by 46 publications

(28 citation statements)

References 26 publications

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“…There are several applications of SURF, like face detection [26], target tracking [27,28], simple visual navigation [29] and some works with UAVs. One of these is [30], which uses a simple bang-bang control.…”

Section: Related Workmentioning

confidence: 99%

Obstacle Avoidance Based-Visual Navigation for Micro Aerial Vehicles

2017

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This paper describes an obstacle avoidance system for low-cost Unmanned Aerial Vehicles (UAVs) using vision as the principal source of information through the monocular onboard camera. For detecting obstacles, the proposed system compares the image obtained in real time from the UAV with a database of obstacles that must be avoided. In our proposal, we include the feature point detector Speeded Up Robust Features (SURF) for fast obstacle detection and a control law to avoid them. Furthermore, our research includes a path recovery algorithm. Our method is attractive for compact MAVs in which other sensors will not be implemented. The system was tested in real time on a Micro Aerial Vehicle (MAV), to detect and avoid obstacles in an unknown controlled environment; we compared our approach with related works.

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Section: Related Workmentioning

confidence: 99%

Obstacle Avoidance Based-Visual Navigation for Micro Aerial Vehicles

2017

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“…We will employ a navigation system based on SURF features detection in an image provided by an on-board camera. The system was developed for navigation of a UGV robot [1] and later extended for an MAV [13]. This system (referred as GeNav) is suited for guidance of robots along path that consists of set of straight segments.…”

Section: Problem Statement and Preliminariesmentioning

confidence: 99%

Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles

Saska

Krajník

Vonásek

et al. 2013

2013 International Conference on Unmanned Aircraft Systems (ICUAS)

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Abstract-A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav), which together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions.

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“…We will employ a navigation system based on detection of SURF features in an image provided by an on-board camera. The system was developed for navigation of a single UGV robot [2] and later extended for a quadrocopter [35]. This system (called as GeNav) is suited for guidance of robots along path that consists of a sequence of straight segments.…”

Section: Problem Statement and Preliminariesmentioning

confidence: 99%