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Keane Haesle

PROFILE

Keane Haesle

Worked on the Stanford-AUV/RoboSub repository to deliver six core features focused on sensor fusion, localization, and control for autonomous underwater robotics. Developed a new ROS2-based controller node in Python and C++, integrating thruster configuration and extended Kalman filtering for improved navigation. Overhauled the localization system by refining EKF node management and parameterization, streamlining sensor data integration from IMU and odometry sources. Established a reproducible development environment using Docker, enabling GPU-accelerated AI tasks with CUDA and PyTorch on Jetson hardware. Enhanced perception capabilities by incorporating YOLOv8 object detection assets, supporting robust onboard data recording and facilitating rapid iteration in simulation and deployment.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

10Total
Bugs
0
Commits
10
Features
6
Lines of code
231,193
Activity Months1

Work History

February 2026

10 Commits • 6 Features

Feb 1, 2026

February 2026 (2026-02) monthly summary for Stanford-AUV/RoboSub. The work focused on delivering core sensor fusion improvements, streamlining localization, advancing the ROS2 control stack, and establishing a robust, reproducible development environment. These efforts enable more reliable navigation, faster iteration, and better onboard perception.

Activity

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Quality Metrics

Correctness84.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage38.0%

Skills & Technologies

Programming Languages

BashDockerfileJSONPythonYAML

Technical Skills

C++CUDAContainerizationDevOpsDockerEmbedded SystemsKalman filteringMachine LearningPyTorchPythonROSROS2configuration managementcontainerizationcontrol systems

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

Stanford-AUV/RoboSub

Feb 2026 Feb 2026
1 Month active

Languages Used

BashDockerfileJSONPythonYAML

Technical Skills

C++CUDAContainerizationDevOpsDockerEmbedded Systems