Safe Gap based (SG) reactive navigation for mobile robots

Mujahed, Muhannad; Fischer, Dirk; Mertsching, Bärbel

doi:10.1109/ecmr.2013.6698862

Cited by 16 publications

(2 citation statements)

References 22 publications

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“…However, implementing a mobile robot to perform navigation tasks rapidly, robustly and energy efficiently can be challenging especially in cluttered environments [4]. A reactive navigation methodology is a solution to this problem that combines sensory information with robot control directly [5] through processing of sensor data [6]. A number of approaches for visual reactive ground navigation have been proposed in recent and past years.…”

Section: Introductionmentioning

confidence: 99%

Agile reactive navigation for a non‐holonomic mobile robot using a pixel processor array

Liu

Bose

Greatwood

et al. 2021

IET Image Processing

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This paper presents an agile reactive navigation strategy for driving a non-holonomic ground vehicle around a pre-set course of gates in a cluttered environment using a lowcost processor array sensor. This enables machine vision tasks to be performed directly upon the sensor's image plane, rather than using a separate general-purpose computer. The authors demonstrate a small ground vehicle running through or avoiding multiple gates at high speed using minimal computational resources. To achieve this, target tracking algorithms are developed for the Pixel Processing Array and captured images are then processed directly on the vision sensor acquiring target information for controlling the ground vehicle. The algorithm can run at up to 2000 fps outdoors and 200 fps at indoor illumination levels. Conducting image processing at the sensor level avoids the bottleneck of image transfer encountered in conventional sensors. The real-time performance of onboard image processing and robustness is validated through experiments. Experimental results demonstrate the algorithm's ability to enable a ground vehicle to navigate at an average speed of 2.20 m/s for passing through multiple gates and 3.88 m/s for a 'slalom' task in an environment featuring significant visual clutter. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Introductionmentioning

confidence: 99%

Agile reactive navigation for a non‐holonomic mobile robot using a pixel processor array

Liu

Bose

Greatwood

et al. 2021

IET Image Processing

View full text Add to dashboard Cite

show abstract

“…However, implementing a mobile robot to perform navigation tasks rapidly, robustly and energy-efficiently can be challenging especially in cluttered environments [4]. A reactive navigation methodology is a solution to this problem that combines sensory information with robot control directly [5] through processing of sensor data [6].…”

Section: Introductionmentioning

confidence: 99%

Agile Reactive Navigation for A Non-Holonomic Mobile Robot Using A Pixel Processor Array

Liu

Bose

Greatwood

et al. 2020

Preprint

View full text Add to dashboard Cite

This paper presents an agile reactive navigation strategy for driving a non-holonomic ground vehicle around a preset course of gates in a cluttered environment using a low-cost processor array sensor. This enables machine vision tasks to be performed directly upon the sensor's image plane, rather than using a separate general-purpose computer. We demonstrate a small ground vehicle running through or avoiding multiple gates at high speed using minimal computational resources. To achieve this, target tracking algorithms are developed for the Pixel Processing Array and captured images are then processed directly on the vision sensor acquiring target information for controlling the ground vehicle. The algorithm can run at up to 2000 fps outdoors and 200fps at indoor illumination levels. Conducting image processing at the sensor level avoids the bottleneck of image transfer encountered in conventional sensors. The real-time performance of on-board image processing and robustness is validated through experiments. Experimental results demonstrate that the algorithm's ability to enable a ground vehicle to navigate at an average speed of 2.20 m/s for passing through multiple gates and 3.88 m/s for a 'slalom' task in an environment featuring significant visual clutter.

show abstract