This folder contains scripts for evaluating theseus's components. These scripts should be run from the root folder of the repository. The following scripts are available, with reference to corresponding figure in our white paper:

• vectorization_ablation.sh: Runs pose graph optimization with synthetic data with or without cost function vectorization (Fig. 1).
• pose_graph_synthetic.sh: Same as above, but can change linear solver and problem size (Fig. 2).
• pose_graph_cube.sh: Same as above, but using the cube data for Ceres comparison (Fig. 3).
• backward_modes_tactile.sh: Runs tactile state estimation with different backward modes (Fig. 4).
• autodiff_cost_function_ablation.sh: Runs homography estimation with different autograd modes.

Some other relevant files to look at:

• Pose Graph Optimization:

  • examples/pose_graph/pose_graph_{cube/synthetic}.py: Puts together optimization layer and implements outer loop.

• Tactile State Estimation:

  • theseus/utils/examples/tactile_pose_estimation/trainer.py: Main outer learning loop.
  • theseus/utils/examples/tactile_pose_estimation/pose_estimator.py: Puts together the optimization layer.

• Bundle Adjustment:

  • examples/bundle_adjustment.py: Puts together optimization layer and implements outer loop.

• Motion Planning:

  • theseus/utils/examples/motion_planning/motion_planner.py: Puts together optimization layer.
  • examples/motion_planning_2d.py: Implements outer loop.

• Homography Estimation:

  • examples/homography_estimation.py: Puts together optimization layer and implements outer loop.