A furcated visual collision avoidance system for an autonomous micro robot
dc.contributor.author | Isakhani, Hamid | |
dc.contributor.author | Aouf, Nabil | |
dc.contributor.author | Kechagias-Stamatis, Odysseas | |
dc.contributor.author | Whidborne, James F. | |
dc.date.accessioned | 2018-10-19T12:44:45Z | |
dc.date.available | 2018-10-19T12:44:45Z | |
dc.date.issued | 2018-07-23 | |
dc.description.abstract | This paper proposes a secondary reactive collision avoidance system for micro class of robots based on a novel approach known as the Furcated Luminance-Difference Processing (FLDP) inspired by the Lobula Giant Movement Detector, a wide-field visual neuron located in the lobula layer of a locust nervous system. This paper addresses some of the major collision avoidance challenges; obstacle proximity & direction estimation, and operation in GPS-denied environment with irregular lighting. Additionally, it has proven effective in detecting edges independent of background color, size, and contour. The FLDP executes a series of image enhancement and edge detection algorithms to estimate collision threat-level which further determines whether or not the robot’s field of view must be dissected where each section’s response is compared against the others to generate a simple collision-free maneuver. Ultimately, the computation load and the performance of the model is assessed against an eclectic set of off-line as well as real-time real-world collision scenarios validating the proposed model’s asserted capability to avoid obstacles at more than 670 mm prior to collision, moving at 1.2 ms¯¹ with a successful avoidance rate of 90% processing at 120 Hz on a simple single core microcontroller, sufficient to conclude the system’s feasibility for real-time real-world applications that possess fail-safe collision avoidance system. | en_UK |
dc.identifier.citation | Isakhani H, Aouf N, Kechagias-Stamatis O, Whidborne J. (2020) A furcated visual collision avoidance system for an autonomous micro robot. IEEE Transactions on Cognitive and Developmental Systems, Volume 12, March 2020, pp. 1-11 | en_UK |
dc.identifier.cris | 21745606 | |
dc.identifier.issn | 2379-8920 | |
dc.identifier.uri | https://doi.org/10.1109/TCDS.2018.2858742 | |
dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/13550 | |
dc.language.iso | en | en_UK |
dc.publisher | IEEE | en_UK |
dc.rights | Attribution-NonCommercial 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
dc.subject | Autonomous robots | en_UK |
dc.subject | biologically-inspired | en_UK |
dc.subject | furcated luminance-difference processing (FLDP) | en_UK |
dc.subject | direction and proximity estimation | en_UK |
dc.title | A furcated visual collision avoidance system for an autonomous micro robot | en_UK |
dc.type | Article | en_UK |
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