PurdueLunabotics/purdue_lunabotics
Nov 2024 – May 2025
6 Months active
Languages Used
C++CMakePythonShellXMLYAMLRvizROS
Technical Skills
Autonomous NavigationC++CMakeComputer VisionConfigurationConfiguration Files
Pranav Chitiveli
PROFILE
Pranav Chitiveli
Pranav Chitive developed and enhanced autonomous robotics capabilities for the PurdueLunabotics/purdue_lunabotics repository, focusing on navigation, perception, and system reliability. He implemented point-to-point navigation using Python and ROS, integrating PID control for precise path following and refactoring the logic into a modular state machine. Pranav improved perception by adding LiDAR and AprilTag localization, optimizing TF2 handling, and enabling dynamic pose averaging for robust sensor fusion. His work included launch configuration overhauls, simulation validation, and codebase cleanup, resulting in safer autonomous workflows and streamlined deployment. Throughout, he demonstrated depth in C++, ROS, and control systems, addressing both feature development and stability.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
19Total
Bugs
2
Commits
19
Features
6
Lines of code
16,636
Activity Months6
Your Network
113 people
Work History
May 2025
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on PurdueLunabotics/purdue_lunabotics. This period centered on stabilizing and preparing for future DStar work by refining the mining arena integration and cleaning the codebase to reduce noise and build risk.
1 Commits • 1 Features
May 1, 2025Concise monthly summary for 2025-05 focusing on PurdueLunabotics/purdue_lunabotics. This period centered on stabilizing and preparing for future DStar work by refining the mining arena integration and cleaning the codebase to reduce noise and build risk.
May 2025
April 2025
5 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for PurdueLunabotics/purdue_lunabotics: Implemented a launch configuration overhaul and Apriltag localization enhancements to improve robot startup reliability, perception robustness, and runtime efficiency. Focused on separating computer and robot startup nodes, optimizing TF handling, and enabling pose publishing with dynamic averaging controls for Apriltag localization. These changes reduce startup failures, streamline node orchestration, and enable safer, more accurate autonomous operation.
April 2025
5 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for PurdueLunabotics/purdue_lunabotics: Implemented a launch configuration overhaul and Apriltag localization enhancements to improve robot startup reliability, perception robustness, and runtime efficiency. Focused on separating computer and robot startup nodes, optimizing TF handling, and enabling pose publishing with dynamic averaging controls for Apriltag localization. These changes reduce startup failures, streamline node orchestration, and enable safer, more accurate autonomous operation.
February 2025
1 Commits
Feb 1, 2025February 2025: PurdueLunabotics/purdue_lunabotics — Focused on stabilizing robot navigation through a state-machine refactor. The work reorganized point-to-point navigation into a state-driven flow with explicit movement and target acquisition states, added error calculations, and clarified transitions to improve modularity and maintainability. The refactor exposed instability in the navigation loop, and the system is currently broken and requires stabilization, tests, and a clear rollback strategy. Documented findings and a broader plan for next steps.
1 Commits
Feb 1, 2025February 2025: PurdueLunabotics/purdue_lunabotics — Focused on stabilizing robot navigation through a state-machine refactor. The work reorganized point-to-point navigation into a state-driven flow with explicit movement and target acquisition states, added error calculations, and clarified transitions to improve modularity and maintainability. The refactor exposed instability in the navigation loop, and the system is currently broken and requires stabilization, tests, and a clear rollback strategy. Documented findings and a broader plan for next steps.
February 2025
January 2025
7 Commits • 1 Features
Jan 1, 2025January 2025 highlights for PurdueLunabotics/purdue_lunabotics. Focused on improving autonomy and reliability of the point-to-point navigation system. Key feature delivered: robust point-to-point navigation with a new navigation script, PID controller enhancements, configurable limits and tolerances, improved pose/velocity estimation, visualization markers, enhanced path handling, and path simplification to deliver more reliable user-facing autonomous navigation. Work also included simulation validation and deployment-readiness improvements (robot.launch updates). Major bugs fixed: fixed a critical bug causing robot teleportation during navigation and stabilized point-to-point operation for dummy targets; ongoing integration work with D* path planning. Technologies/skills demonstrated: ROS-based navigation stack, PID tuning, scripting, visualization, path planning, simulation, and ROS launch workflow. Overall impact: increased reliability and safety of autonomous navigation, enabling safer missions with less operator intervention; lays groundwork for advanced path planning and scalable autonomy. Business value: higher mission success rate, reduced downtime, improved operator confidence.
January 2025
7 Commits • 1 Features
Jan 1, 2025January 2025 highlights for PurdueLunabotics/purdue_lunabotics. Focused on improving autonomy and reliability of the point-to-point navigation system. Key feature delivered: robust point-to-point navigation with a new navigation script, PID controller enhancements, configurable limits and tolerances, improved pose/velocity estimation, visualization markers, enhanced path handling, and path simplification to deliver more reliable user-facing autonomous navigation. Work also included simulation validation and deployment-readiness improvements (robot.launch updates). Major bugs fixed: fixed a critical bug causing robot teleportation during navigation and stabilized point-to-point operation for dummy targets; ongoing integration work with D* path planning. Technologies/skills demonstrated: ROS-based navigation stack, PID tuning, scripting, visualization, path planning, simulation, and ROS launch workflow. Overall impact: increased reliability and safety of autonomous navigation, enabling safer missions with less operator intervention; lays groundwork for advanced path planning and scalable autonomy. Business value: higher mission success rate, reduced downtime, improved operator confidence.
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024 – PurdueLunabotics/purdue_lunabotics: Delivered the Point-to-Point (PtP) Robot Navigation Controller feature with Python control logic and integration into the simulation launch workflow. The PtP controller uses PID control for linear and angular velocity to follow specified paths, enabling autonomous path execution in simulation. No explicit major bug fixes for this repo were documented in the provided data; however, early commits show active testing and stabilization efforts around PtP behavior, signaling ongoing robustness improvements. Overall impact includes enhanced navigation autonomy, reduced manual intervention, and faster mission throughput in the simulation environment. Technologies demonstrated include Python scripting for control logic, PID-based control strategies, and seamless integration with the simulation/launch framework, reflecting progress in autonomous capabilities and software integration.
2 Commits • 1 Features
Dec 1, 2024December 2024 – PurdueLunabotics/purdue_lunabotics: Delivered the Point-to-Point (PtP) Robot Navigation Controller feature with Python control logic and integration into the simulation launch workflow. The PtP controller uses PID control for linear and angular velocity to follow specified paths, enabling autonomous path execution in simulation. No explicit major bug fixes for this repo were documented in the provided data; however, early commits show active testing and stabilization efforts around PtP behavior, signaling ongoing robustness improvements. Overall impact includes enhanced navigation autonomy, reduced manual intervention, and faster mission throughput in the simulation environment. Technologies demonstrated include Python scripting for control logic, PID-based control strategies, and seamless integration with the simulation/launch framework, reflecting progress in autonomous capabilities and software integration.
December 2024
November 2024
3 Commits • 1 Features
Nov 1, 2024Monthly summary for 2024-11 (PurdueLunabotics/purdue_lunabotics): The month focused on delivering autonomous capabilities with LiDAR perception enhancements, stabilizing deployment, and strengthening real-robot and simulation integration. Highlights include advanced autonomous functionality across navigation, excavation, deposition, and sensor integration, with LiDAR perception support and updated launch/config for both real robot and simulation environments. A stable baseline was restored by reverting unstable installation Script and behavior control changes, ensuring predictable operation. Business value was delivered through safer autonomous workflows, improved perception reliability, and readiness for continued sensor fusion development across platforms.
November 2024
3 Commits • 1 Features
Nov 1, 2024Monthly summary for 2024-11 (PurdueLunabotics/purdue_lunabotics): The month focused on delivering autonomous capabilities with LiDAR perception enhancements, stabilizing deployment, and strengthening real-robot and simulation integration. Highlights include advanced autonomous functionality across navigation, excavation, deposition, and sensor integration, with LiDAR perception support and updated launch/config for both real robot and simulation environments. A stable baseline was restored by reverting unstable installation Script and behavior control changes, ensuring predictable operation. Business value was delivered through safer autonomous workflows, improved perception reliability, and readiness for continued sensor fusion development across platforms.
Activity
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Quality Metrics
Correctness80.0%
Maintainability81.0%
Architecture79.0%
Performance74.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CMakePythonROSRvizShellXMLYAML
Technical Skills
AprilTag DetectionAutonomous NavigationC++CMakeComputer VisionConfigurationConfiguration FilesControl SystemsGazeboLaunch FilesLocalizationNavigationNumPyPID ControlPath Planning
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