High-Fidelity Autonomous Surface Vehicle Simulator for the Maritime RobotX Challenge

This paper presents a high-fidelity autonomous surface vehicle (ASV) and an above-water environment simulator developed for, and used by, the Queensland University of Technology (QUT) team at the 2016 Maritime RobotX Challenge. This simulator was developed to address a gap in an existing robotic marine vehicle simulation software by producing high-fidelity sensor data from a realistic operating environment and simulating ASV motion dynamics as a direct interface for hardware-in-the-loop simulation. The key functions required for the simulator to be an effective model of the QUT ASV included a high-fidelity camera, LiDAR (Velodyne HDL-32E), Inertial Measurement Unit (IMU), and GPS sensor simulation, as well as buoyancy and physics simulation for vehicle motion and control performance in a spatiotemporally varying modeled sea state. Another key feature of the simulator was the provision to directly interface the Robotic Operating System (ROS) to publish and subscribe to sensor topics (in real time) and allow hardware-in-the-loop simulation of the ASV systems for algorithm development. The fidelity and performance of the simulator was benchmarked against the existing best available alternative simulator, V-Rep, with results shown to demonstrate that the autonomous marine surface vessel simulator achieved improved computational performance and sensor fidelity when simulating above surface marine environments.