Obstacle Avoidance Strategy for Micro Aerial Vehicle

Kownacki, Cezary

doi:10.1007/978-3-642-19817-5_10

Cited by 5 publications

(14 citation statements)

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“…A 3D laser scanner with a limited field of view of 30x40 degrees has been used in [13] on an outdoor helicopter with a payload of 29kg. Mini laser range finders have been used by [14], [15], for detection of large obstacles located directly in front of a drone. However, due to their single point/planar detection ability they are not suitable for measuring position of other robots in 3D.…”

Section: Introductionmentioning

confidence: 99%

On-Board Relative Bearing Estimation for Teams of Drones Using Sound

Basiri

Schill

Lima³

et al. 2016

IEEE Robot. Autom. Lett.

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Abstract-In a team of autonomous drones, individual knowledge about the relative location of teammates is essential. Existing relative positioning solutions for teams of small drones mostly rely on external systems such as motion tracking cameras or GPS satellites that might not always be accessible. In this letter, we describe an onboard solution to measure the 3-D relative direction between drones using sound as the main source of information. First, we describe a method to measure the directions of other robots from perceiving their engine sounds in the absence of self-engine noise. We then extend the method to use active acoustic signaling to obtain the relative directions in the presence of self-engine noise, to increase the detection range, and to discriminate the identity of robots. Methods are evaluated in real world experiments and a fully autonomous leader-following behavior is illustrated with two drones using the proposed system.

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Section: Introductionmentioning

confidence: 99%

On-Board Relative Bearing Estimation for Teams of Drones Using Sound

Basiri

Schill

Lima³

et al. 2016

IEEE Robot. Autom. Lett.

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“…In spite of that many researchers are still attempting to demonstrate autonomous UAV having at least partial possibilities of obstacle avoidance (Beyeler et al, 2009;Griffiths et al, 2007]. Such case of partial obstacle avoidance is an autonomous flight in unknown canyons (Kownacki, 2009;Kownacki, 2010;Kownacki, 2011;Hrabar et al, 2006). It assumes that UAV flies between obstacles like buildings or canyon walls.…”

Section: Introductionmentioning

confidence: 99%

“…Ranges from canyon walls can be determined by Fig. 1): -a pair of laser rangefinders (Kownacki, 2009;2010;2011), -optical flow sensors or miniature cameras (Beyeler et al, 2009;Griffiths et al, 2007;Hrabar et al, 2006;2009), -a single camera and optical flow processing (Andert et al, 2010). In (Hrabar et al, 2009) authors presented results of vehicle flights in urban canyons using two miniature cameras and optical flow image processing.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, we aim to realize the control of UAV flight across the canyon in a little bit different way. Instead of optical flow sensors or cameras we employed two tiny laser rangefinders (MLR100) (Kownacki, 2009;2010;2011). These robust sensors determine ranges from obstacles at the vehicle front on both sides of the canyon (Fig.…”

Section: Introductionmentioning

confidence: 99%

“…These robust sensors determine ranges from obstacles at the vehicle front on both sides of the canyon (Fig. 2) (Kownacki, 2009;2010;2011). The effective sensing range is about 150 meters without disturbances.…”

Section: Introductionmentioning

confidence: 99%

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Real Flight Demonstration of Pitch and Roll Control for Uav Canyon Flights

Kownacki¹

2013

Acta Mechanica Et Automatica

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The paper presents results of an experiment prepared to validate the autonomous control of obstacle avoidance designed for a micro UAV to fly in urban canyons. The idea of the obstacle avoidance assumes usage of two miniature laser rangefinders responsible for obstacle detection and range measurement. Measured ranges from obstacles placed on both sides of UAV can be used to simultaneous control of desired roll and pitch angles. Such combination of controls allows achieving high agility of UAV, because during a maneuver of obstacle avoidance UAV can make a turn and climb at the same time. In the experiment, controls of roll and pitch angles were verified separately to ensure high reliability of results and clearance of UAV behavior in the real flight. Because of lack of appropriate objects, which can be used as obstacles, laser rangefinders were directed vertically to the ground instead of the original horizontal configuration. So sensors determine ranges from the ground during a descent flight of UAV, and if their values are lower than defined threshold, it could be interpreted as obstacle detection. The experiment results present UAV behavior adequate to designed controls of roll and pitch angle. The vehicle turns in the opposite direction to the sensing axis of laser rangefinder detecting an obstacle and starts climbing when both sensors detect obstacles at the same range below the threshold.

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