Coverage Path Planning With Track Spacing Adaptation for Autonomous Underwater Vehicles

Abstract

In this paper we address the mine countermeasures (MCM) search problem for an autonomous underwater vehicle (AUV) surveying the seabed using a side-looking sonar. We propose a coverage path planning method that adapts the AUV track spacing with the objective of collecting better data. We achieve this by shifting the coverage overlap at the tail of the sensor range where the lowest data quality is expected. To assess the algorithm, we collected data from three at-sea experiments. The adaptive survey allowed the AUV to recover from a situation where the sensor range was overestimated and resulted in reducing area coverage gaps. In another experiment, the adaptive survey showed a 4.2% improvement in data quality for nearly 30% of the 'worst' data.

A Framework for Coverage Path Planning Optimization Based on Point Cloud for Structural Inspection

“…A gain is added to the cover fitness to identify how far it is from the 90-degree angle. Equation (11) shows the Gaussian function of the intersection gain. The goal is a Gaussian that ranges from 60 to 120 degrees, with a unit value of 90 degrees: With this fitness configuration, the search for better parameters can use any metaheuristic algorithm.…”

“…Thus, the development of several algorithms allowed the application in these kinds of processes [ 8 , 9 , 10 ]. For example, there are several applications, such as underwater inspection [ 11 ] and aerospace [ 12 ] tasks.…”

Active Multi-Object Exploration and Recognition via Tactile Whiskers

“…To sample using an optimal strategy with a reduced number of probes, motion planners for information acquisition have been previously proposed. This is part of a research theme referred to as Informative Path Planning (IPP) [9], [38], [39]. Among IPP approaches developed for tactile sensors, a commonly used approach is to explore uncertain regions using discrete sampling.…”

MPPTM: A Bio-Inspired Approach for Online Path Planning and High-Accuracy Tracking of UAVs

“…Park et al proposed a distributed approach combing alternating direction method of multipliers (ADMM) to nonmyopic path planning for multi-target tracking, but it can not avoid obstacles in the environment (Park et al, 2019). Yordanova et al proposed a path planning and tracking method for the area coverage of autonomous underwater vehicles, but in essence, the method is still only for the 2-D environment without obstacles (Yordanova and Gips, 2020). Penin et al proposed a visionbased path planning and target tracking method for UAVs (Penin et al, 2018).…”

“…Compared with these studies (Penin et al, 2018;Park et al, 2019;Yordanova and Gips, 2020;Yu et al, 2020), there are few studies for online path planning and tracking of MRS. During online path planning and tracking of MRS, the proposed model needs to plan the trajectories easy to track in real-time, which deals with dynamic environments and accidents, such as robot fault, moving obstacles, and so on. Online path planning and tracking need to solve the following three problems.…”