Low-Level Active Visual Navigation: Increasing Robustness of Vision-Based Localization Using Potential Fields

• Published in: IEEE robotics and automation letters Vol. 3; no. 3; pp. 2079 - 2086
• Main Authors: Rodrigues, Romulo T., Basiri, Meysam, Aguiar, A. Pedro, Miraldo, Pedro
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-07-2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aerial systems; Algorithms; Cameras; Computer simulation; Constraint modelling; Feature extraction; Localization; Mapping; Navigation; perception and autonomy; Potential energy; Potential fields; Robots; sensor-based control; Simultaneous localization and mapping; Uncertainty; Visual odometry; visual-based navigation; Visualization
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2018.2809628

This letter proposes a low-level visual navigation algorithm to improve visual localization of a mobile robot. The algorithm, based on artificial potential fields, associates each feature in the current image frame with an attractive or neutral potential energy, with the objective of generating a control action that drives the vehicle towards the goal, while still favoring feature rich areas within a local scope, thus improving the localization performance. One key property of the proposed method is that it does not rely on mapping, and therefore it is a lightweight solution that can be deployed on miniaturized aerial robots, in which memory and computational power are major constraints. Simulations and real experimental results using a mini quadrotor equipped with a downward looking camera demonstrate that the proposed method can effectively drive the vehicle to a designated goal through a path that prevents localization failure.