Development of a Perception System for an Autonomous Surface Vehicle using Monocular Camera, LIDAR, and Marine RADAR
T. M. Clunie, Michael DeFilippo, Michael Sacarny, Paul Robinette
Abstract
This paper describes a set of software modules and algorithms for maritime object detection and tracking. The approach described here is designed to work in conjunction with various sensors from a maritime surface vessel (e.g. marine RADAR, LIDAR, camera). The described system identifies obstacles from the input sensors, estimates their state, and fuses the obstacle data into a consolidated report. The system is verified using experiments conducted on a live system and successfully demonstrates the ability to detect and track obstacles up to 450m away while operating at 7 fps. The software is open source and available at https://github.com/uml-marine-robotics/asv_perception.
Topics & Concepts
LidarComputer visionArtificial intelligenceComputer scienceObstacleSoftwareRadarRadar imagingUnmanned surface vehicleSynthetic aperture radarTracking systemObject detectionRoboticsMonocularReal-time computingRemote sensingRobotEngineeringGeologyMarine engineeringGeographyKalman filterPattern recognition (psychology)TelecommunicationsProgramming languageArchaeologyMaritime Navigation and SafetyRobotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor Networks