Stanford-AUV/RoboSub
Nov 2024 – Jun 2025
8 Months active
Languages Used
DockerfileMarkdownPythonShellArduinoC++CMakeURDF
Technical Skills
3D GeometryComputer VisionData VisualizationDepth EstimationDocumentationMatplotlib
Scott Hickmann
PROFILE
Scott Hickmann
Scott Hickmann developed and maintained the Stanford-AUV/RoboSub codebase over eight months, delivering features that advanced perception, control, and autonomy for underwater robotics. He built and integrated modules for 2D/3D object detection, IMU-DVL sensor fusion, and joystick-based manual control, using Python, ROS 2, and Bash scripting. His work included robust data logging, hardware integration with Arduino, and migration of inter-process communication to NATS for lower latency. Scott improved simulation realism, automated build and deployment workflows, and enhanced documentation for onboarding and troubleshooting. The depth and breadth of his contributions enabled reliable field operations, faster iteration, and maintainable, production-ready systems.
Overall Statistics
Feature vs Bugs
90%Features
Repository Contributions
52Total
Bugs
3
Commits
52
Features
26
Lines of code
11,495
Activity Months8
Your Network
3 peopleShared Repositories
3
Work History
June 2025
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for Stanford-AUV/RoboSub: Delivered critical features and bug fixes that enhance data collection reliability, ROS package management, and remote GUI usability. The work reinforces business value by improving operational readiness and reducing setup friction for field experiments.
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for Stanford-AUV/RoboSub: Delivered critical features and bug fixes that enhance data collection reliability, ROS package management, and remote GUI usability. The work reinforces business value by improving operational readiness and reducing setup friction for field experiments.
June 2025
May 2025
18 Commits • 8 Features
May 1, 2025Month: 2025-05 — RoboSub delivered core operator and perception features, stability enhancements, and developer-experience improvements. Highlights include lighting control integration with brightness tuning, live camera streaming with dual-camera visualization, and a joystick-based velocity control path with manual override. Inter-process communication was migrated from WebSockets to NATS in Docker/local environments, reducing latency and simplifying deployments. Sensor accuracy and safety were improved through IMU calibration enhancements and orientation control tuning (PID) along with adjusted thruster limits. Additional progress includes pool test data and navigation threshold tuning, and development-environment fixes for Mac devcontainers, XQuartz, and Docker-based Python tooling. A cleanup/refactor of camera/IMU modules addressed unused scripts and optimized node handling for better reliability.
May 2025
18 Commits • 8 Features
May 1, 2025Month: 2025-05 — RoboSub delivered core operator and perception features, stability enhancements, and developer-experience improvements. Highlights include lighting control integration with brightness tuning, live camera streaming with dual-camera visualization, and a joystick-based velocity control path with manual override. Inter-process communication was migrated from WebSockets to NATS in Docker/local environments, reducing latency and simplifying deployments. Sensor accuracy and safety were improved through IMU calibration enhancements and orientation control tuning (PID) along with adjusted thruster limits. Additional progress includes pool test data and navigation threshold tuning, and development-environment fixes for Mac devcontainers, XQuartz, and Docker-based Python tooling. A cleanup/refactor of camera/IMU modules addressed unused scripts and optimized node handling for better reliability.
April 2025
6 Commits • 4 Features
Apr 1, 2025April 2025 RoboSub monthly summary focusing on delivering robust sensing, control, and simulation improvements. Key work included DVL data processing and visualization with port autodetection and publishing, along with improved Arduino response parsing and logging of DVL connection failures to enhance robustness. IMU integration and 3D orientation visualization tooling were added for validation of orientation data. Multi-waypoint control was refactored to support following multiple waypoints with cross-platform compatibility (Mac), improved PID tuning, and a new visual PID logger. Perception module install path issues were fixed via setup.cfg corrections to ensure reliable builds. AUV hydrodynamics was tuned for more realistic simulation behavior. These efforts improve mission reliability, debugging efficiency, platform parity, and the realism of simulation models, driving safer operations and faster iteration cycles.
6 Commits • 4 Features
Apr 1, 2025April 2025 RoboSub monthly summary focusing on delivering robust sensing, control, and simulation improvements. Key work included DVL data processing and visualization with port autodetection and publishing, along with improved Arduino response parsing and logging of DVL connection failures to enhance robustness. IMU integration and 3D orientation visualization tooling were added for validation of orientation data. Multi-waypoint control was refactored to support following multiple waypoints with cross-platform compatibility (Mac), improved PID tuning, and a new visual PID logger. Perception module install path issues were fixed via setup.cfg corrections to ensure reliable builds. AUV hydrodynamics was tuned for more realistic simulation behavior. These efforts improve mission reliability, debugging efficiency, platform parity, and the realism of simulation models, driving safer operations and faster iteration cycles.
April 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for Stanford-AUV/RoboSub: Focused on enhancing localization reliability and maintainability. Delivered a ROS 2 IMU-DVL synchronization node to align IMU and DVL data for accurate localization, along with plotting utilities for sensor data and localization trajectories. Refactored sensor data handling with configuration updates to enable these features, improving configurability and data integrity. Key work includes localization tuning (commit d3c49837e067e2439118f6ffb2387e8c798134ab).
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for Stanford-AUV/RoboSub: Focused on enhancing localization reliability and maintainability. Delivered a ROS 2 IMU-DVL synchronization node to align IMU and DVL data for accurate localization, along with plotting utilities for sensor data and localization trajectories. Refactored sensor data handling with configuration updates to enable these features, improving configurability and data integrity. Key work includes localization tuning (commit d3c49837e067e2439118f6ffb2387e8c798134ab).
February 2025
14 Commits • 4 Features
Feb 1, 2025February 2025 quarterly/monthly summary for Stanford-AUV/RoboSub focused on delivering end-to-end autonomy improvements, stabilizing operations, and enabling faster iteration through automation. Key outcomes include (1) DVL integration with autodetection, port management, velocity data handling, and a ROS bridge, with velocity transformation matrices applied to ensure accurate DVL measurements; (2) manual control enhancements and thruster configuration updates, including new thruster mappings, adjusted serial ports, and a formal manual control script with documentation; (3) robust sensor data collection from the Teensy, introduction of sensor data messages, and improved PWM control using real-time voltage readings; (4) perception pipeline enhancements with data logging, centralized launch and logging UI, and automated build/runtime scripts for ports and the DepthAI pipeline; and (5) a consolidated build/deploy workflow for reproducibility and rapid experimentation. Overall, these efforts improved data fidelity, control stability, and operational efficiency, enabling safer autonomous operation and faster business value realization.
14 Commits • 4 Features
Feb 1, 2025February 2025 quarterly/monthly summary for Stanford-AUV/RoboSub focused on delivering end-to-end autonomy improvements, stabilizing operations, and enabling faster iteration through automation. Key outcomes include (1) DVL integration with autodetection, port management, velocity data handling, and a ROS bridge, with velocity transformation matrices applied to ensure accurate DVL measurements; (2) manual control enhancements and thruster configuration updates, including new thruster mappings, adjusted serial ports, and a formal manual control script with documentation; (3) robust sensor data collection from the Teensy, introduction of sensor data messages, and improved PWM control using real-time voltage readings; (4) perception pipeline enhancements with data logging, centralized launch and logging UI, and automated build/runtime scripts for ports and the DepthAI pipeline; and (5) a consolidated build/deploy workflow for reproducibility and rapid experimentation. Overall, these efforts improved data fidelity, control stability, and operational efficiency, enabling safer autonomous operation and faster business value realization.
February 2025
January 2025
5 Commits • 4 Features
Jan 1, 2025In January 2025, RoboSub delivered key features, infrastructure enhancements, and documentation that improve operator control, hardware integration, and cross-architecture deployment. The work focuses on manual control capabilities, a modernized development environment, Arduino hardware integration, and sensor onboarding support, with measurable business impact in development speed and deployment readiness.
January 2025
5 Commits • 4 Features
Jan 1, 2025In January 2025, RoboSub delivered key features, infrastructure enhancements, and documentation that improve operator control, hardware integration, and cross-architecture deployment. The work focuses on manual control capabilities, a modernized development environment, Arduino hardware integration, and sensor onboarding support, with measurable business impact in development speed and deployment readiness.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for Stanford-AUV/RoboSub: Documentation-focused improvement addressing Qt platform plugin xcb errors; introduced a dedicated README FAQ with remediation steps and reorganized the 'Out of storage' guidance under the new section. No code changes this month; emphasizes reduced support time, improved onboarding, and reliability.
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for Stanford-AUV/RoboSub: Documentation-focused improvement addressing Qt platform plugin xcb errors; introduced a dedicated README FAQ with remediation steps and reorganized the 'Out of storage' guidance under the new section. No code changes this month; emphasizes reduced support time, improved onboarding, and reliability.
December 2024
November 2024
4 Commits • 2 Features
Nov 1, 2024November 2024 performance summary for Stanford-AUV/RoboSub. Key features delivered include RoboSub Perception System (2D and 3D object detection) with YOLO-based detection, depth estimation, and oriented bounding box visualization for 3D point clouds using PCA. Documentation and maintainability improvements encompassed refactoring of submodule management, ThrustGenerator clarifications, enhanced docstrings and type hints, and updated README guidance for handling storage-related issues. Minor bug fixes and stability improvements targeted at deployment readiness: added storage handling guidance and streamlining development by removing outdated tooling constraints. Overall impact emphasizes improved perception capabilities for autonomous navigation, enhanced code quality and maintainability, and faster iteration cycles. Technologies/skills demonstrated include computer vision (2D/3D detection, depth estimation, PCA-based oriented bounding boxes, YOLO), software engineering (refactoring, type hints, docstrings, modularization), and deployment readiness (storage guidance).
November 2024
4 Commits • 2 Features
Nov 1, 2024November 2024 performance summary for Stanford-AUV/RoboSub. Key features delivered include RoboSub Perception System (2D and 3D object detection) with YOLO-based detection, depth estimation, and oriented bounding box visualization for 3D point clouds using PCA. Documentation and maintainability improvements encompassed refactoring of submodule management, ThrustGenerator clarifications, enhanced docstrings and type hints, and updated README guidance for handling storage-related issues. Minor bug fixes and stability improvements targeted at deployment readiness: added storage handling guidance and streamlining development by removing outdated tooling constraints. Overall impact emphasizes improved perception capabilities for autonomous navigation, enhanced code quality and maintainability, and faster iteration cycles. Technologies/skills demonstrated include computer vision (2D/3D detection, depth estimation, PCA-based oriented bounding boxes, YOLO), software engineering (refactoring, type hints, docstrings, modularization), and deployment readiness (storage guidance).
Activity
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Quality Metrics
Correctness82.8%
Maintainability84.2%
Architecture80.4%
Performance73.4%
AI Usage22.0%
Skills & Technologies
Programming Languages
ArduinoBashC++CMakeDockerfileMarkdownPythonShellURDFYAML
Technical Skills
3D GeometryBashBuild ConfigurationBuild SystemCMakeCommand Line InterfaceComputer VisionConfiguration ManagementControl SystemsCoordinate TransformationsData LoggingData ProcessingData SynchronizationData VisualizationDepth Estimation
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