title: An optical flow-based integrated navigation system inspired by insect vision.
abstract: Some insects use optic flow (OF) to perform their navigational tasks perfectly. Learning from insects' OF navigation strategies, this article proposes a bio-inspired integrated navigation system based on OF. The integrated navigation system is composed of an OF navigation system (OFNS) and an OF aided navigation system (OFAN). The OFNS uses a simple OF method to measure motion at each step along a path. The position information is then obtained by path integration. However, path integration leads to cumulative position errors which increase rapidly with time. To overcome this problem, the OFAN is employed to assist the OFNS in estimating and correcting these cumulative errors. The OFAN adopts an OF-based Kalman filter (KF) to continuously estimate the position errors. Moreover, based on the OF technique used in the OFNS, we develop a new OF method employed by the OFAN to generate the measurement input of the OF-based KF. As a result, both the OFNS and the OFAN in our integrated navigation system are derived from the same OF method so that they share input signals and some operations. The proposed integrated navigation system can provide accurate position information without interference from cumulative errors yet doing so with low computational effort. Simulations and comparisons have demonstrated its efficiency.
authors: National Key Laboratory of Science & Technology on multi-spectral information processing, Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, 430074, People's Republic of China.
authors: Chao
authors: C
authors: Pan
authors: He
authors: H
authors: Deng
authors: Xiao Fang
authors: XF
authors: Yin
authors: Jian Guo
authors: JG
authors: Liu
mesh_terms: D000818:Animals; D007313:Insecta / Q000502:physiology*; D016571:Neural Networks, Computer; D057849:Optic Flow / Q000502:physiology*; D012371:Robotics / Q000295:instrumentation*