Learning and detecting abnormal speed of marine robots

Abstract

This article presents anomaly detection algorithms for marine robots based on their trajectories under the influence of unknown ocean flow. A learning algorithm identifies the flow field and estimates the through-water speed of a marine robot. By comparing the through-water speed with a nominal speed range, the algorithm is able to detect anomalies causing unusual speed changes. The identified ocean flow field is used to eliminate false alarms, where an abnormal trajectory may be caused by unexpected flow. The convergence of the algorithms is justified through the theory of adaptive control. The proposed strategy is robust to speed constraints and inaccurate flow modeling. Experimental results are collected on an indoor testbed formed by the Georgia Tech Miniature Autonomous Blimp and Georgia Tech Wind Measuring Robot, while simulation study is performed for ocean flow field. Data collected in both studies confirm the effectiveness of the algorithms in identifying the through-water speed and the detection of speed anomalies while avoiding false alarms.

Laplacian regularized motion tomography for underwater vehicle flow mapping with sporadic localization measurements

“…However, the data resolution matrix so defined is singular. Hence, in view of the MT flow update equation (11), we define the data resolution matrix for MT as…”

“…Orthogonal decomposition technique has been applied in [7] to compute flow model parameters, with the help from dynamic mode decomposition and the Koopman operator representation [8,9]. [10,11] develops a data assimilation scheme that adaptively constructs the basis functions from the Eulerian flow field prediction model. Parameters of the basis functions are then estimated from an adaptive learning algorithm.…”

Bounded Cost Path Planning for Underwater Vehicles Assisted by a Time-Invariant Partitioned Flow Field Model

“…The term e x − z is the controlled Lagrangian Localization error (CLLE, Cho and Zhang, 2016;Cho et al, 2021), which describes how much the actual trajectory deviates from the estimated trajectory. A learning algorithm will then compute β(t), ξ(t), V L (t) so that the CLLE can be reduced.…”

A micro quadruped crawling robot manufactured from PLA material

“…With the development of science and technology, robots are widely used in production and life. Robots can replace people to complete some dangerous and difficult tasks, such as underwater detection, outdoor inspection, laser welding and so on [1][2][3], and greatly improving production efficiency. Bionic robot is a hot topic in the field of robotics.…”