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Talk-23: Obstacle Avoidance for Autonomous Surface Vehicles Using the MOOS-IvP Platform

Allisa Dalpe, May-Win Thein, Alexander Cook, Alexander Roemer, and Steven Hurley, University of New Hampshire

Current work involves integrating global and local path planning methods to create a reliable and robust autonomous system using MOOS-IvP as the main software platform. This navigational development will be used for the future plans of this project: expanding to a network of surface and underwater vehicles working collaboratively to complete a seafloor- mapping mission. Other goals include keeping the system low-cost and maximizing modularity. This modularity will help facilitate expansion to multiple vehicles. Here, the system can be transferred to or reproduced for additional vehicles with minimal internal adjustments (i.e., to take into account the size, type, and motor configuration of the vessel). Modular components are divided according to the following three tasks: information gathering, data processing, and command execution.

The experimental platform, ASV4, consists of an 8 ft. rigid inflatable boat maintained by the University of New Hampshire undergraduate ASV team. Experimental testing is performed in a lake environment in addition to testing facilities at UNH (engineering tank and wave/tow tank).

Implemented global navigation methods will use a path planning algorithm such as A star (A*), Rapidly Exploring Random Tree (RRT), and Probabilistic Roadmap (PRM), or a combination thereof. Local (i.e., reactive) obstacle avoidance will use a Scanse Sweep Lidar. This sensor is a new and relatively low cost Lidar with a range of 40m. MOOS-IvP features and additional IvP behavior development will be explored to find an effective strategy for meshing the global and local methods to work cohesively and without interruption. Testing of the Scanse Sweep Lidar will also be performed to determine applicability and practicality for the proposed mission tasks. Additional sensors for navigational purposes and information gathering include a Global Positioning System (GPS) and an Inertial Measurement Unit (IMU). Sensor data is then processed by a Raspberri Pi with MOOS-IvP.

The vehicle’s electronics are housed in a watertight box, and MOOS-IvP is run on a laptop. A MOOSapp will be used to interface between MOOS-IvP and an Arduino. The application subscribes to the MOOSDB for desired speed, heading, rudder, thrust and obstacleinformation, and then sends the information to the Ardiuno via serial. The Arduino utilizes this information to execute the decisions made by the helm to control the vehicle’s speed and heading.

Categories:

  • ASVs
  • Obstacle Avoidance