Underwater Multi-Robot Simulation and Motion Planning in Angler

TL;DR

The paper addresses the need for realistic, scalable simulation of underwater multi-robot systems to curb hardware deployment costs. It presents an Angler extension that enables simultaneous multi-robot simulation with non-conflicting channels among Gazebo, ArduSub SITL, and MAVROS, plus a ROS 2-based JointTrajectory planning interface, OMPL integration, collision avoidance via Pinocchio, and an environment-generation tool. A benchmarking framework is provided to evaluate planning algorithms under static and dynamic obstacles with real-time feedback, supporting online replanning. Collectively, the work enables rapid development, testing, and benchmarking of underwater multi-robot motion planning in dynamic environments, paving the way for future cooperative tasks and learning-based methods.

Abstract

Deploying multi-robot systems in underwater environments is expensive and lengthy; testing algorithms and software in simulation improves development by decoupling software and hardware. However, this requires a simulation framework that closely resembles the real-world. Angler is an open-source framework that simulates low-level communication protocols for an onboard autopilot, such as ArduSub, providing a framework that is close to reality, but unfortunately lacking support for simulating multiple robots. We present an extension to Angler that supports multi-robot simulation and motion planning. Our extension has a modular architecture that creates non-conflicting communication channels between Gazebo, ArduSub Software-in-the-Loop (SITL), and MAVROS to operate multiple robots simultaneously in the same environment. Our multi-robot motion planning module interfaces with cascaded controllers via a JointTrajectory controller in ROS~2. We also provide an integration with the Open Motion Planning Library (OMPL), a collision avoidance module, and tools for procedural environment generation. Our work enables the development and benchmarking of underwater multi-robot motion planning in dynamic environments.

Figures (5)

• Figure 1: A scene in Angler showcasing our multi-robot extension, which simulates a team of robots influenced by ocean currents. These robots are tasked with autonomously navigating around obstacles in a collaborative exploration mission. Our multi-robot extension to Angler establishes conflict-free interfaces between Gazebo, ArduSub SITL, and MAVROS, enabling coordinated or individual control of each robot. Additionally, we provide tools for integrating controllers with the motion planning through OMPL and for generating environments that include both static and dynamic obstacles.
• Figure 2: The existing software architecture for simulation in Angler.
• Figure 3: Software architecture illustrating our extension of Angler (\ref{['figure:angler_arch']}) to enable multi-robot simulation.
• Figure 4: Software architecture for multi-robot motion planning.
• Figure 5: A scene in Angler showcasing online and offline motion planning in presence of static and dynamic obstacles for two robots. $T= 0, 1$, and $2$ represents three distinct timesteps.