StanfordVL/OmniGibson
Jan 2026 – Feb 2026
2 Months active
Languages Used
PythonbashBash
Technical Skills
Bash ScriptingDependency ManagementDevOpsPythonPython programmingcomputer vision
kmy17518
PROFILE
Kmy17518
Kmy17518 contributed to the StanfordVL/OmniGibson repository by improving installation reliability and user experience for teleoperation and data recording workflows. They addressed dependency conflicts in JoyLo installations by introducing a constraints-based approach using Bash scripting and Python, ensuring compatibility across OmniGibson and Isaac Sim environments. Their work included enhancing teleoperation input handling with better tensor processing and key-release tracking, resulting in smoother camera control. Additionally, they implemented robustness checks for trajectory recording to prevent crashes from insufficient data. By refining dependency management and streamlining installation scripts, Kmy17518 enabled more stable development cycles and faster onboarding for robotics and simulation teams.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
3
Lines of code
90
Activity Months2
Your Network
1045 peopleWork History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026: Delivered installation dependency management enhancements for JoyLo within OmniGibson to improve reliability and onboarding. Implemented an explicit numpy<2 constraint in joylo/setup.py and streamlined installation by removing unnecessary constraints in setup.sh. These changes reduce install-time failures and improve environment reproducibility, supporting faster onboarding and more stable developer workflows. Commit reference: 00c4229d1e563ed8c58edf3a2f92a3f28657961e.
1 Commits • 1 Features
Feb 1, 2026February 2026: Delivered installation dependency management enhancements for JoyLo within OmniGibson to improve reliability and onboarding. Implemented an explicit numpy<2 constraint in joylo/setup.py and streamlined installation by removing unnecessary constraints in setup.sh. These changes reduce install-time failures and improve environment reproducibility, supporting faster onboarding and more stable developer workflows. Commit reference: 00c4229d1e563ed8c58edf3a2f92a3f28657961e.
February 2026
January 2026
5 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for StanfordVL/OmniGibson: Delivered reliability and UX improvements across installation, teleoperation, and data recording workflows. Implemented a constraints-based approach for JoyLo installations to pin maximum dependencies and prevent conflicts across OmniGibson and Isaac Sim, using a temporary constraints file to avoid clashes. Enhanced teleoperation input handling with improved tensor processing for camera movement and more accurate key-release tracking, resulting in smoother operator experience. Introduced a robustness check for trajectory recording requiring a minimum of three waypoints, preventing crashes due to insufficient data. These changes improve cross-environment compatibility, operational stability, and data integrity, enabling more dependable simulations and faster iteration cycles across teams.
January 2026
5 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for StanfordVL/OmniGibson: Delivered reliability and UX improvements across installation, teleoperation, and data recording workflows. Implemented a constraints-based approach for JoyLo installations to pin maximum dependencies and prevent conflicts across OmniGibson and Isaac Sim, using a temporary constraints file to avoid clashes. Enhanced teleoperation input handling with improved tensor processing for camera movement and more accurate key-release tracking, resulting in smoother operator experience. Introduced a robustness check for trajectory recording requiring a minimum of three waypoints, preventing crashes due to insufficient data. These changes improve cross-environment compatibility, operational stability, and data integrity, enabling more dependable simulations and faster iteration cycles across teams.
Activity
Loading activity data...
Quality Metrics
Correctness96.6%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashPythonbash
Technical Skills
Bash ScriptingDependency ManagementDevOpsPythonPython programmingbash scriptingcomputer visiondependency managementevent handlinggame developmentpackage managementroboticsshell scriptingteleoperation
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline