Multiboat Trajectory Optimization

shapeshifting branch

Trajectory Planning for the Shapeshifting of Autonomous Surface Vessels

Gheneti, Banti; Park, Shinkyu; Kelly, Ryan; Meyers, Drew; Leoni, Pietro; Ratti, Carlo; Rus, Daniela L

• c-space computation for a vessel made of rectangles moving around another vessel made of rectangles, using shapely
• trajectory optimization algorithm for solving collision free trajectories to shapeshift in the c-space, using pydrake
• also includes features in the master branch described below

presented at the International Symposium on Multi-Robot and Multi-Agent Systems (IEEE-MRS 2019)

• demo video
• paper link

master branch

Multiboat minimum makespan formation planning in three stages.

• Goal assignment with the Hungarian algorithm with initial state to goal high order norm costs
• Linear and shape-based interpolation for trajectory initialization
• Direct transcription trajectory optimization using pydrake with SNOPT SQP solver

Final project for 6.832 - Underactuated Robotics

See Youtube for an explanation video.

Contents

• .py files include code for the above 3 stages, as well as for producing visualizations
• final_project_visualizations.ipynb contains code for running experiments on the .py files and saving them to /results
• final_project_visualizations.experiments for viewing result files as tables, displaying and saving boat animations, and plotting various graphs.
• /results contains experiment results
• /animations contains various experiment animations
• /icp contains the iterative closest point (ICP) implementation obtained from @ClayFlanigan.

Dependencies

• Main dependency is drake
• Install other python dependencies with pip install sklearn tabular