Bio-inspired vision mimetics towards next generation collision avoidance automation

Xu, Gary J.W., Guo, Kun, Park, Seop Hyeong , Sun, Poly Z.H. and Song, Aiguo (2023) Bio-inspired vision mimetics towards next generation collision avoidance automation. The Innovation, 4 (1). ISSN 2666-6758

Full content URL: https://doi.org/10.1016/j.xinn.2022.100368

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Bio-inspired vision mimetics towards next generation collision avoidance automation
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Abstract

The current “deep learning + large-scale data + strong supervised labeling” technology framework of collision avoidance for ground robots and aerial drones is becoming saturated. Its development gradually faces challenges from real open-scene applications, including small data, weak annotation, and cross-scene. Inspired by the neural structure and processes underlying human cognition (e.g., human visual, auditory, and tactile systems) and the knowledge learned from daily driving tasks, such as, a high-level cognitive system is developed for integrating collision sensing and collision avoidance. This bio-inspired cognitive approach takes the advantages of good robustness, high self-adaptability, and low computation consumption in practical driving scenes.

Subjects:C Biological Sciences > C830 Experimental Psychology
Divisions:College of Social Science > School of Psychology
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ID Code:53112
Deposited On:24 Jan 2023 16:46

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