Underwater vehicle obstacle avoidance and path planning using a multi-beam forward looking sonar

Abstract

This paper describes a new framework for segmentation of sonar images, tracking of underwater objects and motion estimation. This framework is applied to the design of an obstacle avoidance and path planning system for underwater vehicles based on a multi-beam forward looking sonar sensor. The real-time data flow (acoustic images) at the input of the system is first segmented and relevant features are extracted. We also take advantage of the real-time data stream to track the obstacles in following frames to obtain their dynamic characteristics. This allows us to optimize the preprocessing phases in segmenting only the relevant part of the images. Once the static (size and shape) as well as dynamic characteristics (velocity, acceleration, …) of the obstacles have been computed, we create a representation of the vehicle's workspace based on these features. This representation uses constructive solid geometry (CSG) to create a convex set of obstacles defining the workspace. The tracking takes also into account obstacles which are no longer in the field of view of the sonar in the path planning phase. A well-proven nonlinear search (sequential quadratic programming) is then employed, where obstacles are expressed as constraints in the search space. This approach is less affected by local minima than classical methods using potential fields. The proposed system is not only capable of obstacle avoidance but also of path planning in complex environments which include fast moving obstacles. Results obtained on real sonar data are shown and discussed. Possible applications to sonar servoing and real-time motion estimation are also discussed.

Obstacle detection and avoidance for an Autonomous Surface Vehicle using a profiling sonar

“…For AUVs, obstacle avoidance is mainly performed using a forward looking sonar [11]. The problem can be solved in a similar way for a surface vehicle but there are some important differences.…”

Real Time Underwater Obstacle Avoidance and Path Re-planning Using Simulated Multi-beam Forward Looking Sonar Images for Autonomous Surface Vehicle

“…9(a) (sonar scanned downward; range of sonar: 10 m). A common segmentation for sonar image consists of filtering and thresholding [14].The filtering is in charge of the Imagenex TM DeltaT sonar; in this sonar, there are various filter settings could be used that depend on the bottom type or in the water column, e.g. rocks, wrecks, fish schools, piers.…”

“…With the recent underwater technologies of reliable, most obstacle avoidance platform used a high solution multi-beam FLS, particularly in [14] that describes a framework for segmentation of sonar images, tracking of underwater objects. This framework is still applied to the design of obstacle avoidance and path planning system for underwater vehicles based on a multi-beam FLS.…”

Performance evaluation in obstacle avoidance

“…Ultrasonic sensors are also used in the work from Petillot et al (2001), sonar is used to detect and track underwater obstacles. Uncertainties in the measurements are taken into account using a Kalman filter.…”