LiU-SeeGoals/controller
Nov 2024 – Dec 2024
2 Months active
Languages Used
Go
Technical Skills
AI DevelopmentGame DevelopmentRoboticsAICode StandardizationDebugging
Jamie Mersh
PROFILE
Jamie Mersh
Developed and enhanced autonomous robot navigation in the LiU-SeeGoals/controller repository by implementing the MoveToBall AI feature using Go. Focused on enabling robots to reliably approach the ball and adapt to changing game states, the work included scenario-based testing and the introduction of a FAILED state to improve failure diagnosis. Subsequent efforts centered on increasing reliability through runtime handling, ball proximity detection, and data structure consistency, supported by debugging instrumentation and a refactor to the info package. Emphasized code standardization, robust testing, and maintainability, resulting in more dependable ball-tracking behavior and streamlined iteration within robotics simulation environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
2
Lines of code
164
Activity Months2
Your Network
26 peopleSame Organization
@student.liu.se14
Shared Repositories
12
Rasmus WallinMember
agneshillMember
AntonMember
Arturas AleksandrausMember
Arturas AleksandrausMember
Daniel PurgalMember
jakobMember
jakos322Member
JolineMember
Work History
December 2024
4 Commits • 1 Features
Dec 1, 2024In 2024-12, LiU-SeeGoals/controller delivered key reliability and testing improvements for the MoveToBall AI scenario. The work focused on runtime handling, ball proximity detection, and data structure consistency, with debugging instrumentation and test adjustments. A refactor to use the info package for internal data structures improved maintainability and debuggability. The result is more robust autonomous ball-tracking behavior in simulation, reduced flaky behavior, and faster iteration cycles.
4 Commits • 1 Features
Dec 1, 2024In 2024-12, LiU-SeeGoals/controller delivered key reliability and testing improvements for the MoveToBall AI scenario. The work focused on runtime handling, ball proximity detection, and data structure consistency, with debugging instrumentation and test adjustments. A refactor to use the info package for internal data structures improved maintainability and debuggability. The result is more robust autonomous ball-tracking behavior in simulation, reduced flaky behavior, and faster iteration cycles.
December 2024
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 delivered a pivotal MoveToBall AI navigation capability in LiU-SeeGoals/controller, enabling robots to reliably move toward the ball and respond to different game states. A scenario-based test suite was added to validate MoveToBall behavior across various states, including a dedicated FAILED state to surface and diagnose navigation failures. There were no major bug fixes documented for this module this month. Overall, the work advances autonomous control quality, improves testing discipline, and strengthens the product's competitive edge in real-time play.
November 2024
1 Commits • 1 Features
Nov 1, 2024November 2024 delivered a pivotal MoveToBall AI navigation capability in LiU-SeeGoals/controller, enabling robots to reliably move toward the ball and respond to different game states. A scenario-based test suite was added to validate MoveToBall behavior across various states, including a dedicated FAILED state to surface and diagnose navigation failures. There were no major bug fixes documented for this module this month. Overall, the work advances autonomous control quality, improves testing discipline, and strengthens the product's competitive edge in real-time play.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture72.0%
Performance72.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Go
Technical Skills
AIAI DevelopmentCode StandardizationDebuggingGame DevelopmentPackage ManagementRefactoringRoboticsRobotics SimulationTesting
Repositories Contributed To
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