A platform for aerial robotics research and demonstration: The Flying Machine Arena

Lupashin, Sergei; Hehn, Markus; Mueller, Mark W.; Schoellig, Angela P.; Sherback, Michael; D’Andrea, Raffaello

doi:10.1016/j.mechatronics.2013.11.006

Cited by 189 publications

(118 citation statements)

References 23 publications

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“…The exposure time was set to 4 ms and the gain to 0 dB. The bias-generation setting for the DVS were set to "fast" 4 . We interfaced all sensors over USB and evaluated the delays both on a laptop computer (Lenovo W530) and an embedded computer (Hardkernel Odroid U3).…”

Section: A Experimental Setupmentioning

confidence: 99%

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Towards evasive maneuvers with quadrotors using dynamic vision sensors

Mueggler

Baumli

Fontana

et al. 2015

2015 European Conference on Mobile Robots (ECMR)

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We present a method to predict collisions with objects thrown at a quadrotor using a pair of dynamic vision sensors (DVS). Due to the micro-second temporal resolution of these sensors and the sparsity of their output, the object's trajectory can be estimated with minimal latency. Unlike standard cameras that send frames at a fixed frame rate, a DVS only transmits pixel-level brightness changes ("events") at the time they occur. Our method tracks spherical objects on the image plane using probabilistic trackers that are updated with each incoming event. The object's trajectory is estimated using an Extended Kalman Filter with a mixed state space that allows incorporation of both the object's dynamics and the measurement noise in the image plane. Using error-propagation techniques, we predict a collision if the 3-ellipsoid along the predicted trajectory intersects with a safety sphere around the quadrotor. We experimentally demonstrate that our method allows initiating evasive maneuvers early enough to avoid collisions. Abstract-We present a method to predict collisions with objects thrown at a quadrotor using a pair of dynamic vision sensors (DVS). Due to the micro-second temporal resolution of these sensors and the sparsity of their output, the object's trajectory can be estimated with minimal latency. Unlike standard cameras that send frames at a fixed frame rate, a DVS only transmits pixel-level brightness changes ("events") at the time they occur. Our method tracks spherical objects on the image plane using probabilistic trackers that are updated with each incoming event. The object's trajectory is estimated using an Extended Kalman Filter with a mixed state space that allows incorporation of both the object's dynamics and the measurement noise in the image plane. Using error-propagation techniques, we predict a collision if the 3σ-ellipsoid along the predicted trajectory intersects with a safety sphere around the quadrotor. We experimentally demonstrate that our method allows initiating evasive maneuvers early enough to avoid collisions.

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Section: A Experimental Setupmentioning

confidence: 99%

“…In the last few years, impressive demonstrations of aggressive flight and acrobatics with quadrotors have been presented [3], [4]. Among these demonstrations were also interactions with other, fast-moving objects, e.g.…”

Section: Introductionmentioning

confidence: 99%

Towards evasive maneuvers with quadrotors using dynamic vision sensors

Mueggler

Baumli

Fontana

et al. 2015

2015 European Conference on Mobile Robots (ECMR)

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“…The main motivation behind the utilisation of FPGAbased systems in visual navigation tasks is a latency reduction in the robotic navigation system which is especially recognizable in experiments performed in dynamic or confined environments, which impose imminent threats to the mobile robotic platform [1,23] and the reduction of the computational load thus power consumption of the mobile robot platforms.…”

Section: Discussionmentioning

confidence: 99%

On Fpga Based Acceleration of Image Processing in Mobile Robotics

Petr

Faigl

2015

APP

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Abstract. In visual navigation tasks, a lack of the computational resources is one of the main limitations of micro robotic platforms to be deployed in autonomous missions. It is because the most of nowadays techniques of visual navigation relies on a detection of salient points that is computationally very demanding. In this paper, an FPGA assisted acceleration of image processing is considered to overcome limitations of computational resources available on-board and to enable high processing speeds while it may lower the power consumption of the system. The paper reports on performance evaluation of the CPU-based and FPGA-based implementations of a visual teach-and-repeat navigation system based on detection and tracking of the FAST image salient points. The results indicate that even a computationally efficient FAST algorithm can benefit from a parallel (low-cost) FPGA-based implementation that has a competitive processing time but more importantly it is a more power efficient.

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“…The aim of this study was to combine the flying abilities and skills of UAVs with the latest 3D digitization methods. A method is presented for carrying out fast 3D reconstruction on cultural heritage treasures with a small, inexpensive photographic sensor and an UAV, which was tested in a flight test arena, which was used for conducting experiments in the field of aerial robotics [11,12]. We also describe the steps in an automated process designed for these reconstruction purposes.…”

Section: Introductionmentioning

confidence: 99%

A Shape-Adjusted Tridimensional Reconstruction of Cultural Heritage Artifacts Using a Miniature Quadrotor

et al. 2016

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Abstract:The innovative automated 3D modeling procedure presented here was used to reconstruct a Cultural Heritage (CH) object by means of an unmanned aerial vehicle. Using a motion capture system, a small low-cost quadrotor equipped with a miniature low-resolution Raspberry Pi camera module was accurately controlled in the closed loop mode and made to follow a trajectory around the artifact. A two-stage process ensured the accuracy of the 3D reconstruction process. The images taken during the first circular trajectory were used to draw the artifact's shape. The second trajectory was smartly and autonomously adjusted to match the artifact's shape, then it provides new pictures taken close to the artifact and, thus, greatly improves the final 3D reconstruction in terms of the completeness, accuracy and quickness, in particular where the artifact's shape is complex. The results obtained here using close-range photogrammetric methods show that the process of automated 3D model reconstruction based on a robotized quadrotor using a motion capture system is a realistic approach, which could provide a suitable new digital conservation tool in the cultural heritage field.

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A platform for aerial robotics research and demonstration: The Flying Machine Arena

Cited by 189 publications

References 23 publications

Towards evasive maneuvers with quadrotors using dynamic vision sensors

Towards evasive maneuvers with quadrotors using dynamic vision sensors

On Fpga Based Acceleration of Image Processing in Mobile Robotics

A Shape-Adjusted Tridimensional Reconstruction of Cultural Heritage Artifacts Using a Miniature Quadrotor

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