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Indexed by:期刊论文

Date of Publication:2021-01-10

Journal:JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS

Volume:100

Issue:3-4

Page Number:765-775

ISSN No.:0921-0296

Key Words:Relocalization; 2D LiDAR sensor; CNN; Robot pose; Kidnapped robot problem

Abstract:We present a deep-learning-based strategy that only uses a 2D LiDAR sensor to solve the kidnapped robot problem in similar indoor environments. First, we converted a set of 2D laser data into an RGB-image and an occupancy grid map and stacked them into a multi-channel image. Then, a neural network structure with five convolutional layers and four fully connected layers was designed to regress the 3-DOF robot pose. Finally, the network was trained using multi-channel images as input. We also improved the network structure to identify the scene where the robot is localized. Extensive experiments have been conducted in practice with a real mobile robot, verifying the effectiveness of the proposed strategy. Our network can obtain approximately 2m and 5(circle)accuracy indoors, and the scene classification accuracy of our network reaches up to 98%.