LEARNING
A Robot Obstacle Avoidance Method Using Merged CNN Framework
Nai-Hsiang Chang, Yi-Hsing Chien, Hsin‐Han Chiang, Wei‐Yen Wang, Chen‐Chien Hsu
- Year
- 2019
- Citations
- 8
Abstract
In this paper, a merged convolution neural network (CNN) framework is proposed to automatically avoid obstacles. Although there are many methods for avoiding obstacles, previous methods mostly contain high energy-consuming and high cost. This paper aims to realize an image-based method with a monocular webcam. The experimental results illustrate that the proposed method can effectively avoid obstacles in mobile robot navigation.
Keywords
Computer scienceArtificial intelligenceObstacle avoidanceComputer visionConvolutional neural networkMobile robotConvolution (computer science)ObstacleRobotMonocular vision
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