
Joline developed core AI modules for the LiU-SeeGoals/controller repository, focusing on robot soccer planning and defensive behavior. She implemented a neural network-based goal prediction system integrated with a planning engine to generate action sequences such as move, pass, shoot, and dribble, validated within a zone-based simulation environment. In addition, she designed and integrated a modular goalie AI, supporting both fast and scenario-based decision architectures, and updated the demo executable for end-to-end validation. Using Python and Go, Joline applied deep learning, reinforcement learning, and robotics expertise to establish robust, extensible foundations for autonomous decision-making and iterative performance improvement.

January 2025: Implemented Robot Soccer Goalie Behavior with AI integration across both fast brain and scenario slow brain architectures; updated the demo executable to invoke the goalie function, enabling end-to-end validation of defensive AI. This work establishes a foundation for more sophisticated goalie strategies and demonstrates modular AI components across the LiU-SeeGoals/controller repo.
January 2025: Implemented Robot Soccer Goalie Behavior with AI integration across both fast brain and scenario slow brain architectures; updated the demo executable to invoke the goalie function, enabling end-to-end validation of defensive AI. This work establishes a foundation for more sophisticated goalie strategies and demonstrates modular AI components across the LiU-SeeGoals/controller repo.
December 2024: Delivered the Robot Soccer Planning Module with Neural Network Goal Prediction and Action Planning in LiU-SeeGoals/controller. Implemented a neural network goal predictor and integrated it with a planning engine to generate action sequences (move, pass, shoot, dribble) within a zone-based field, validated via a simulation environment. The initial planner commit 3bfb2d58f0db2f8e33b572e9735cd081ebdb4765 establishes an end-to-end decision loop and lays the foundation for future training and evaluation. This work enhances autonomous decision-making and sets the stage for performance measurement and iterative improvement.
December 2024: Delivered the Robot Soccer Planning Module with Neural Network Goal Prediction and Action Planning in LiU-SeeGoals/controller. Implemented a neural network goal predictor and integrated it with a planning engine to generate action sequences (move, pass, shoot, dribble) within a zone-based field, validated via a simulation environment. The initial planner commit 3bfb2d58f0db2f8e33b572e9735cd081ebdb4765 establishes an end-to-end decision loop and lays the foundation for future training and evaluation. This work enhances autonomous decision-making and sets the stage for performance measurement and iterative improvement.
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