Ultrasonic relative positioning for multi-robot systems

Rivard, F.; Bisson, J.; Michaud, François; Létourneau, Dominic

doi:10.1109/robot.2008.4543228

Cited by 61 publications

(45 citation statements)

References 17 publications

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“…However, small field of view (30 o ), low resolution (15 o ) and small range (10m) are some of the major drawbacks of this system. Infrared/ultrasound-based sensor suites have been shown in [23,22] to provide accurate relative range and bearing estimation in indoor flying platforms. However, they are not suitable sensors for outdoor MAVs due to their short working range.…”

Section: State Of the Artmentioning

confidence: 99%

Audio-based Relative Positioning System for Multiple Micro Air Vehicle Systems

Basiri¹,

Schill²,

Floreano³

et al. 2013

Robotics: Science and Systems IX

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Abstract-Employing a group of independently controlled flying micro air vehicles (MAVs) for aerial coverage missions, instead of a single flying robot, increases the robustness and efficiency of the missions. Designing a group of MAVs requires addressing new challenges, such as inter-robot collision avoidance and formation control, where individual's knowledge about the relative location of their local group members is essential. A relative positioning system for a MAV needs to satisfy severe constraints in terms of size, weight, processing power, power consumption, three-dimensional coverage and price. In this paper we present an on-board audio based system that is capable of providing individuals with relative positioning information of their neighbouring sound emitting MAVs. We propose a method based on coherence testing among signals of a small onboard microphone array to obtain relative bearing measurements, and a particle filter estimator to fuse these measurements with information about the motion of robots throughout time to obtain the desired relative location estimates. A method based on fractional Fourier transform (FrFT) is used to identify and extract sounds of simultaneous chirping robots in the neighbourhood. Furthermore, we evaluate our proposed method in a real world experiment with three simultaneously flying micro air vehicles.

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Section: State Of the Artmentioning

confidence: 99%

Audio-based Relative Positioning System for Multiple Micro Air Vehicle Systems

Basiri¹,

Schill²,

Floreano³

et al. 2013

Robotics: Science and Systems IX

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“…and bearing (10 • max.) measurements using Time-ofFlight (TOF) sensing (Shoval and Borenstein 2001;Rivard et al 2008). However, the refresh rate is relatively slow, up to 1.33 Hz for 10 robots, due to the slow propagation of the sound signal (Rivard et al 2008).…”

Section: Related Workmentioning

confidence: 99%

“…Comparing the developed 3-D sensor against the infrared based 2-D relative positioning sensor by Kemppainen et al (2006), shows that it is 200 times faster, has a maximum range that is 1.2 times longer, with an accuracy performance that is 1.2 times better for both range and bearing (comparison at 3 m range due to limited available data). Comparing the developed 3-D sensor against the ultrasonic based 2-D relative positioning sensor by Rivard et al (2008), shows that it is 75 times faster, has a maximum range that is 1.8 6 http://jfroberts.com/phd (Eye-bot hovering collision).…”

Section: Comparison With Other Relative Sensorsmentioning

confidence: 99%

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3-D relative positioning sensor for indoor flying robots

et al. 2012

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Swarms of indoor flying robots are promising for many applications, including searching tasks in collapsing buildings, or mobile surveillance and monitoring tasks in complex man-made structures. For tasks that employ several flying robots, spatial-coordination between robots is essential for achieving collective operation. However, there is a lack of on-board sensors capable of sensing the highlydynamic 3-D trajectories required for spatial-coordination of small indoor flying robots. Existing sensing methods typically utilise complex SLAM based approaches, or absolute positioning obtained from off-board tracking sensors, which is not practical for real-world operation. This paper presents an adaptable, embedded infrared based 3-D relative positioning sensor that also operates as a proximity sensor, which is designed to enable inter-robot spatial-coordination and goal-directed flight. This practical approach is robust to varying indoor environmental illumination conditions and is computationally simple.Keywords Relative positioning sensing · Indoor flying robots · Collective operation · 3D sensor · Spatial-coordination · Proximity sensing J.F.R. developed the concept of relative positioning sensing for enabling goal-directed flight on indoor collective flying robots, wrote the manuscript, developed the sensor hardware/firmware, developed the calibration tools and characterised the sensor. T.S. extensively contributed to the sensor firmware and characterisation. J.-C.Z. and D.F. conceived and directed the project sponsoring the work described in the article. They also provided continue support and feedback towards reaching the attained results.

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“…무선통신을 사용하면 에이전트의 위치를 쉽게 알 수 있도록 도와주지 만 실제 적용할 때 하드웨어는 점점 복잡해진다. 이를 극복 하기 위해 초음파 센서를 사용하여 로봇의 위치를 인식하 는 연구들이 진행되었다 [17,18]. 하지만, 이러한 연구들에서 는 다개체 로봇들을 필요에 따라 여러 가지 포메이션 형태 로 변경하는 것이 어려웠다.…”

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Formation Algorithm with Local Minimum Escape for Unicycle Robots

Jung¹,

Kim²

2013

Journal of Institute of Control, Robotics and Systems

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This paper presents formation control based on potential functions for unicycle robots. The unicycle robots move to formation position which is made from a reference point and neighboring robots. In the framework, a local minimum case occurred by combination of potential repulsed from neighboring robots and potential attracted from a formation line is presented, in which the robot escapes from a local minimum using a virtual escape point after recognizing trapped situation. As well, in the paper, potential functions are designed to keep the same distance between neighboring robots on a formation line, i.e. the relative distance between neighboring robots on a formation line is controlled by a potential function parameter. The simulation results show that the proposed approach can effectively construct straight line, V, and polygon formation for multiple robots.

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Ultrasonic relative positioning for multi-robot systems

Cited by 61 publications

References 17 publications

Audio-based Relative Positioning System for Multiple Micro Air Vehicle Systems

Audio-based Relative Positioning System for Multiple Micro Air Vehicle Systems

3-D relative positioning sensor for indoor flying robots

Formation Algorithm with Local Minimum Escape for Unicycle Robots

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