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it runs in sim but the robots are undergoing brownian motion
…oller for opponents for testing
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* Implemented a flag to add Gaussian noise in rsim. Added another more hackish implementation for comparison. * Cleaned up implementation, removed hackish alternative * Working on adding noise to each component independently * Completed implementation of noise addition * Addressed comments on PR, got orientation to work * Addressed comments in PR, added vanishing, added support for ball * Minor linting * Moved utility functions for adding Gaussian noise from classes representing balls/robots to the SSLStdenv class. Learned about this best practice in this week's lecture * Turned off a flag used for testing --------- Co-authored-by: Joel <42647510+energy-in-joles@users.noreply.github.com>
* Fix: fix the goalkeeper and defencer * fix: the robot will not move if it block the ball * Fix: the robot will not move if it block the path * Update utama_core/skills/src/defend_parameter.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Fix goalkeeper defender position logic for left goal defense (#104) * Initial plan * Fix defender position logic for left/right goal defense Co-authored-by: NingchuanIC <212761386+NingchuanIC@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: NingchuanIC <212761386+NingchuanIC@users.noreply.github.com> * Fix side-aware defender position check in goalkeeper logic (#105) * Initial plan * Fix: Make defender position check side-aware Co-authored-by: NingchuanIC <212761386+NingchuanIC@users.noreply.github.com> --------- Co-authored-by: NingchuanIC <212761386+NingchuanIC@users.noreply.github.com> --------- Co-authored-by: NingchuanIC <212761386+NingchuanIC@users.noreply.github.com> Co-authored-by: Fred Huang <60901360+fred-huang122@users.noreply.github.com>
* Added extracted vision data with varying degrees of vanishing and noise * Attempt to store past raw game frames; starting work on test cases * added Andrew's filter * Integrated filters into position refiner * bad example test * Refined filter weights, added vision data for testing * Updated test data * Noise now added manually, updated test data * Amended test cases to address CI failure due to changes to PositionRefiner's constructor * Refinements to filters based on empirical data * Added some references for building tests * First pass unit tests * Some issues with unit tests. Working on fix * Added live testing utilities, conducted analytics for filters, refactored classes, added new datasets * Finalised analysis of filters, unit tests are working, added more live testing utilities * Deleted redundant files * Minor refinements to the live testing utilities * fixed formatting issues * Commented out utilities for testing and exporting data * Analysed vanishing problem, created sample datasets * Position refiner now has access to the last game frame and command map. Imputing feature is coming along , but there are unexplained spikes that are preventing it from working properly * Fixed issues, now imputes correctly based on last gameframe * Completed work on vanishing * Incorporated some suggestions from copilot regardign style * Addressed comments on PR * Removed redundant utility function * Factored out static method into global utility * cleanup * Added back error handling for imports when run from Jupyter * Renamed datasets to include the control mode, filtering only turned on during run mode together with vanishing * Fixed bug in tests due to renaming of files * Created working Kalman filter. Working on analytics * Working on analytics * Implemented a flag to add Gaussian noise in rsim. Added another more hackish implementation for comparison. * Analysing Kalman filter performance; need to merge new rsim utilities first * Cleaned up implementation, removed hackish alternative * Working on adding noise to each component independently * Completed implementation of noise addition * Addressed comments on PR, got orientation to work * Performed benchmarking on kalman filters * Performed benchmarking on kalman filters * More benchmarking * Kalman filter performance validated * Kalman filters now handle vanishing * Removed non-performing implementations * Rejigged analytics for Kalman filter * Addressed comments in PR, added vanishing, added support for ball * Minor linting * Merge branch 'feature/rsim_noise' into feature/kalman * Added filter for ball, added support for orientation * Now able to run analytics for orientation * Moved utility functions for adding Gaussian noise from classes representing balls/robots to the SSLStdenv class. Learned about this best practice in this week's lecture * Turned off a flag used for testing * Minor bug fix * Analysing data for orientation, plus some minor fixes * Completed work with Kalman filters, will now work on PR * Removed some redundant files * Renamed folder to ease merging with testing * Renamed folder to ease merging with testing * Cleanup, getting ready for PR * Small fix to satisfy linter * Final cleanup after reviewing PR diff * Improved filter docs * add docstring to math_utils.py * remove unused get_displacement_vector * remove unused import * [chore] formatting * chore: formatting * fix matrix inversion numerical instability and formatting of class name * remove improper static method use * improper use of tuple[float] type hint and mix bug referencing self.covariance_mat_xy instead of self.covariance_mat in KalmanFilterBall * removed references of .cmd_map not used position.py * fix test failure * Made non-global constant variable lower-cased * Using matrix transpose attribute instead of function call * update test cases * Removed redundant last_game_frame attribute * separate my and opp refiners * update running attribute for opposite refiner too * Minor formatting and naming changes to Kalman filter * fix incorrect assumption about robot id numbering in position refiner tests * corrected direct imputation of None values into vision data. Fix bug causing test fail * improve reset functionaity of position refiner * Fixed bugs introduced when removing assumption about numbering * fix dictionary logic in position refiner * update optional typing for KalmanFilterBall filter * fix typing in KalmanFilterBall * fix point cycle strat * Fixed issues in test due to filters no longer having ids, and now taking Robot instead of Dict[Int, Robot] * Kalman filter now has id attribute * label vision data using kalman id instead of last frame id * add comment about treating substitution as vanishing * remove unncessary imports * add authors --------- Co-authored-by: Fred Huang <fredhuang122106@gmail.com> Co-authored-by: Joel <nzmjoel@gmail.com>
* Added extracted vision data with varying degrees of vanishing and noise * Attempt to store past raw game frames; starting work on test cases * added Andrew's filter * Integrated filters into position refiner * bad example test * Refined filter weights, added vision data for testing * Updated test data * Noise now added manually, updated test data * Amended test cases to address CI failure due to changes to PositionRefiner's constructor * Refinements to filters based on empirical data * Added some references for building tests * First pass unit tests * Some issues with unit tests. Working on fix * Added live testing utilities, conducted analytics for filters, refactored classes, added new datasets * Finalised analysis of filters, unit tests are working, added more live testing utilities * Deleted redundant files * Minor refinements to the live testing utilities * fixed formatting issues * Commented out utilities for testing and exporting data * Addressed comments on PR * Removed redundant utility function * cleanup * Added back error handling for imports when run from Jupyter * Moved unused testing/debugging utilities to a separate text file, turned off filtering by default with a flag to PositionRefiner * Further cleanup * Removed all testing utilities, will create a testing branch * Cleaned up test suite * Removed data analysis * Removed data analysis * Removed data analysis * Final cleanup * revert position_refiner_integration_test * update test * fixes and formatting * remove unncessary comments * update readme --------- Co-authored-by: Fred Huang <fredhuang122106@gmail.com> Co-authored-by: Joel <nzmjoel@gmail.com>
This reverts commit ba83a96.
…bstacle is calculated.
energy-in-joles
approved these changes
Apr 9, 2026
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New motion planning algorithm inspired by the fast-path-planning algorithm described here.