Hydrodynamic-aware simulation tool improves robot sampling accuracy in water
H-SPAR: Hydrodynamic-aware Simulation for Particle Transport and Autonomous Robots
Robotics
Summary
Robots sampling water environments must deal with moving currents that affect both how particles move and how the robots travel. The authors created H-SPAR, a simulation that combines water flow, particle movement, and robot control in one system. This helps show how water currents impact robot paths and sampling results together. Their tests reveal that planning robot paths using current information helps, but real execution differs because currents change over time. Also, the way robots sweep through areas affects how well they collect particles.
What this means in practice
- •For marine robotics developers: Run realistic tests of water current effects on autonomous boat path planning and sampling in a single integrated simulation.
- •For environmental monitoring teams: Optimize water quality sampling missions by simulating particle transport and robot coverage interaction under realistic currents.
Authors
Navid Zarrabi, Nariman Yousefi, Sajad Saeedi
Abstract
Environmental robotic sampling requires considering the dual influence of water currents on robotic motion and particle transport. Existing marine robotics simulators generally model flow, autonomy, and sampling targets separately, limiting joint evaluation of mission cost and sampling performance. H-SPAR integrates spatially and temporally varying velocity fields, Lagrangian particle transport, probabilistic sampling, and ROS 2/Gazebo-based uncrewed surface vehicle (USV) autonomy. In this work, shared precomputed flow fields drive particle advection and current-induced forces during closed-loop vehicle execution. Path-planning experiments show that the existing current-aware planner SVF-RRT* achieves 69.4% lower upstream cost than conventional RRT* at the planning level, but this reduction falls to 41.7% during execution under time-varying currents, reflecting temporal flow variation, vehicle motion constraints, and path deviation omitted during planning. Coverage experiments show that sweep orientation changes the particle-sampling rate by up to 22.2% under the complete H-SPAR configuration. These findings highlight the importance of evaluating planning, vehicle execution, particle transport, and sampling together under consistent hydrodynamic conditions. The project webpage is available at https://sites.google.com/view/h-spar, and the open-source code is available on GitHub at https://github.com/naviiidz/h-spar-sim.