Three Landmark Optimization Strategies for Mobile Robot Visual Homing

• Main Authors: Xun Ji, Qidan Zhu, Junda Ma, Peng Lu, Tianhao Yan
• Format: Article
• Language: English
• Published: MDPI AG 2018-09-01
• Series: Sensors
• Subjects: mobile robot navigation; visual homing; panoramic vision; scale-invariant feature transform
• Online Access: http://www.mdpi.com/1424-8220/18/10/3180

Visual homing is an attractive autonomous mobile robot navigation technique, which only uses vision sensors to guide the robot to the specified target location. Landmark is the only input form of the visual homing approaches, which is usually represented by scale-invariant features. However, the landmark distribution has a great impact on the homing performance of the robot, as irregularly distributed landmarks will significantly reduce the navigation precision. In this paper, we propose three strategies to solve this problem. We use scale-invariant feature transform (SIFT) features as natural landmarks, and the proposed strategies can optimize the landmark distribution without over-eliminating landmarks or increasing calculation amount. Experiments on both panoramic image databases and a real mobile robot have verified the effectiveness and feasibility of the proposed strategies.