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Multi-stage deep learning perception system for mobile robots
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DOI：10.3233/ICA-200640.png)
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摘要
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This paper presents a novel multi-stage perception system for collision avoidance in mobile robots. In the here considered scenario, a mobile robot stands in a workspace with a set of potential targets to reach or interact with. When a human partner appears gesturing to the target, the robot must plan a collision-free trajectory to reach the goal. To solve this problem, a full-perception system composed of consecutive convolutional neural networks in parallel and processing stages is proposed for generating a collision-free trajectory according to the desired goal. This system is evaluated at each step in real environments and through several performance tests, proving to be a robust and fast system suitable for real-time applications.
Keyword:
Deep learning
machine learning
obstacle detection
computer vision
path planning
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I
IF:
5.3
论文数:
491
被引数:
735
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