Visual 3D self localization with 8 gram circuit board for very compact and fully autonomous unmanned aerial vehicles

Konomura, Ryo; Hori, Koichi

doi:10.1109/icra.2014.6907625

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…A miniature module with a low-cost FPGA and MCU for a visual navigation is presented in [12]. A reduced PTAM algorithm [13] (mapping top of 200 features due to memory limitations) is utilized for an estimation of the visual odometry based on the on-line FPGA implementation of the FAST [14] features detection and BRIEF [15] feature description.…”

Section: Related Workmentioning

confidence: 99%

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Low-latency image processing for vision-based navigation systems

Čížek

Faigl

Diar

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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This paper concerns a problem of the latency reduction in the vision-based mobile robot navigation, which is considered as the crucial system property to determine a control command based on visual data in practical deployments of mobile robots. The problem is addressed by a processor centric FPGA-based System-on-Chip design allowing power and computationally efficient on-line image processing. The proposed architecture is considered in an autonomous visionbased navigation with a teach-and-repeat algorithm based on detection and tracking of image salient points. The architecture has been evaluated and compared with a CPU-based solution on different platforms and the results indicate that the proposed FPGA-based implementation outperforms pure CPU solutions in the overall latency, speed, and power consumption.

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Section: Related Workmentioning

confidence: 99%

“…The MCU performs the visual odometry calculation and the whole system operates on 160×120 images at 30 fps. Compared to our approach, the method [12] uses a complex memory access pattern for the feature response function calculation.…”

Section: Related Workmentioning

confidence: 99%

Low-latency image processing for vision-based navigation systems

Čížek

Faigl

Diar

2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…The process of extracting colours is executed in about 10 fps. Without hands, the quadcopter keeps hovering at its place by detecting the feature points of its environment [6], which helps a great deal in making smooth interaction and in avoiding bumping into surroundings.…”

Section: Vision-based Approachmentioning

confidence: 99%

Entertainment Multi-rotor Robot that realises Direct and Multimodal Interaction

Hutchinson

Race

Rouncefield

2014

Electronic Workshops in Computing

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We explore direct interaction of human and multi-rotor robots and its applications for entertainment. In this paper, we present our system that realises direct and multimodal interaction using onboard cameras and a microphone. With these onboard sensors to detect human actions, the robots' reaction chains and expands one after another. In addition, as all the processing is executed within the onboard computer, there is no need to use external devices. We describe its interaction scenario from take-off to landing, and present the pilot evaluation of our system.

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“…Authors of [17] presented a miniature module with a low-cost FPGA and MCU for visual navigation of MAVs. They utilize a reduced version of the PTAM algorithm [8] (mapping maximum of 200 features due to memory limitations) for an estimation of the visual odometry.…”

Section: Related Workmentioning

confidence: 99%

“…However, the most promising are the approaches ( [17][18][19][20]) based on the FAST feature detector [6] because this detector is widely adopted by the robotic community due to its low computational complexity. Hence, it represents a base for further methods.…”

Section: Related Workmentioning

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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Visual 3D self localization with 8 gram circuit board for very compact and fully autonomous unmanned aerial vehicles

Cited by 9 publications

References 14 publications

Low-latency image processing for vision-based navigation systems

Low-latency image processing for vision-based navigation systems

Entertainment Multi-rotor Robot that realises Direct and Multimodal Interaction

On Fpga Based Acceleration of Image Processing in Mobile Robotics

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