EPFLXplore/ERC_HD
Dec 2024 – Apr 2025
2 Months active
Languages Used
C++PythonYAML
Technical Skills
Control SystemsEmbedded SystemsFinite State MachinesGamepad Input HandlingKinematicsMotion Planning
Jeffrey
PROFILE
Jeffrey
Jeffrey Yu contributed to the EPFLXplore/ERC_HD repository by developing and refining motion control, kinematics, and manipulation features for robotics applications. Over two months, he enhanced trajectory planning and servo control using C++ and Python, integrating torque sensor input and compliant motion to improve control fidelity and safety. He introduced gamepad-based sensor simulation and preserved legacy inverse kinematics logic for future extensibility. In April, Jeffrey expanded MoveIt-based perception and manipulation by adding lidar and gripper objects, and implemented a sand-digging task executor with tool handling. His work demonstrated depth in ROS, motion planning, and embedded systems, enabling safer, more precise robotic workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
6
Lines of code
1,005
Activity Months2
Your Network
122 peopleWork History
April 2025
8 Commits • 3 Features
Apr 1, 2025April 2025 — EPFLXplore/ERC_HD: Delivered three integrated features focusing on precision IK, perception/manipulation, and sand-task automation. No major bugs fixed this month; path-constraint issues are being tracked for future fixes. Overall impact: enhanced manipulation accuracy, richer planning with lidar/clam objects, and robust sand-handling workflows that enable more reliable demonstrations and potential field deployments. Key technologies demonstrated include transform-based finger-type corrections, fingertip rotations in IK, MoveIt object integration (lidar/clam), trajectory planning refinements for sand objects, and tool pickup/drop pipelines.
8 Commits • 3 Features
Apr 1, 2025April 2025 — EPFLXplore/ERC_HD: Delivered three integrated features focusing on precision IK, perception/manipulation, and sand-task automation. No major bugs fixed this month; path-constraint issues are being tracked for future fixes. Overall impact: enhanced manipulation accuracy, richer planning with lidar/clam objects, and robust sand-handling workflows that enable more reliable demonstrations and potential field deployments. Key technologies demonstrated include transform-based finger-type corrections, fingertip rotations in IK, MoveIt object integration (lidar/clam), trajectory planning refinements for sand objects, and tool pickup/drop pipelines.
April 2025
December 2024
5 Commits • 3 Features
Dec 1, 2024During December 2024, EPFLXplore/ERC_HD delivered substantial stability, safety, and testability gains across motion control and kinematics. Key progress includes: refined trajectory planner usage and servo planning with directional torque sensor; robust torque sensor input binding; enabled compliant motion; updated EtherCAT motor control configurations; introduced gamepad-based torque sensor for testing while preserving legacy IK logic; and safety hardening by disabling motor nodes in the launch file to prevent unintended launches. These changes reduce drift, improve control fidelity, facilitate safer testing, and establish a foundation for future IK enhancements.
December 2024
5 Commits • 3 Features
Dec 1, 2024During December 2024, EPFLXplore/ERC_HD delivered substantial stability, safety, and testability gains across motion control and kinematics. Key progress includes: refined trajectory planner usage and servo planning with directional torque sensor; robust torque sensor input binding; enabled compliant motion; updated EtherCAT motor control configurations; introduced gamepad-based torque sensor for testing while preserving legacy IK logic; and safety hardening by disabling motor nodes in the launch file to prevent unintended launches. These changes reduce drift, improve control fidelity, facilitate safer testing, and establish a foundation for future IK enhancements.
Activity
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Quality Metrics
Correctness77.0%
Maintainability81.6%
Architecture73.8%
Performance67.8%
AI Usage21.6%
Skills & Technologies
Programming Languages
C++PythonYAML
Technical Skills
C++C++ DevelopmentControl SystemsEmbedded SystemsFinite State MachinesGamepad Input HandlingInverse KinematicsKinematicsMotion PlanningMoveItPythonPython DevelopmentPython ScriptingROSROS 2
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