[1]XIN Jing,DU Kenan,Wang Yuanyuan,et al.Single frame image slope detection algorithm for mobile robots based on transfer learning[J].CAAI Transactions on Intelligent Systems,2021,16(1):81-91.[doi:10.11992/tis.202009009]
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Single frame image slope detection algorithm for mobile robots based on transfer learning

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 16 Number of periods: 2021 1 Page number: 81-91 Column: 学术论文—智能系统 Public date: 2021-01-05
Title:
Single frame image slope detection algorithm for mobile robots based on transfer learning
Author(s):
XIN Jing;  DU Kenan;  Wang Yuanyuan;  LIU Ding
School of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China
Keywords:
unknown environment; mobile robot; slope detection; outdoor; single image; depth estimation; transfer learning; deep convolutional network
CLC:
TP391
DOI:
10.11992/tis.202009009
Abstract:
To meet the requirement of slope perception accuracy for stable uphill control of mobile robots in an unknown environment, a single frame image slope detection algorithm for mobile robots is proposed in this paper based on transfer learning. First, the deep convolutional neural field-fully connected superpixel-pooling network (DCNF-FCSP) is trained using a standard indoor image dataset, and the depth estimation network model of indoor single frame images is obtained. Second, the network parameters of the first five image feature extraction layers in the DCNF-FCSP model are transferred to the outdoor image depth estimation network. Then, the network parameters of the image feature extraction part in the outdoor image depth estimation network are fixed, and the network parameters of the remaining five layers are trained using the outdoor image dataset; thus the outdoor single frame image depth estimation network is obtained. Finally, it is applied to the slope detection of a mobile robot, and the slope angle is estimated according to the single frame slope image. The depth estimation and slope detection experiments on a standard dataset and in actual scenes show that the proposed algorithm can estimate the accurate slope angle according to only a single frame slope RGB image captured by the vehicle-mounted camera of a mobile robot. The proposed algorithm meets the requirements of the slope perception accuracy of a mobile robot in an unknown environment.
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Last Update: 2021-02-25

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