Skip to content
View yuwei-wu's full-sized avatar
🫐
Look for areas or problems that are being ignored.
🫐
Look for areas or problems that are being ignored.
215 followers · 108 following

Achievements

Achievement: Pull Sharkx2Achievement: YOLOAchievement: StarstruckAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull Sharkx2Achievement: YOLOAchievement: StarstruckAchievement: Arctic Code Vault Contributor

Highlights

  • Pro

Organizations

@ZJU-FAST-Lab

Block or report yuwei-wu

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
yuwei-wu/README.md

Hi, welcome to my git! 🪴

  • I'm a Ph.D. student at Upenn ESE, working on motion planning, with the supervision of Professor Vijay Kumar.
  • My research interests are:
    • (Multi-agent) Task and motion planning
    • (Learning-enabled) Trajectory generation and optimization
    • Aerial robot applications (exploration, tracking, navigation)
  • I welcome collaboration if:
    • You are interested in exploring research topics, particularly in planning.
    • You are a Penn student looking to pursue an independent study or thesis under my guidance.

Open-Source

I am passionate about open sourcing to benefit the entire robotics community.

under construction (in this order I will work on it)

  • kr_opt_sfc: A tool to find optimal convex cover to approximate collision-free space
  • kr_param_yaw: A trajectory optimization method with global yaw parameterization

1. Motion planning

  • AllocNet: A lightweight learning-based trajectory optimization framework.
  • forces_resilient_planner: A systematic framework for local planning under external disturbance.

2. Environment representation

3. Simulation and benchmarks

  • kr_mp_design: A guidance for the design and evaluation of motion planners for quadrotors
  • kr_param_map: A parameterized map generator for planning evaluations and benchmarking

4. More collaboration works

  • SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain
  • DZone_Tracking: A risk-aware multi-agent target tracking framework with sensing and communication danger zones
  • resilient-target-tracking: A resilient and adaptive multi-robot target tracking framework with sensing and communication danger zones
  • drl_lc_exploration: A multi-agent cooperative exploration in sparse landmark complex environments

GitHub Streak

Pinned Loading

  1. KumarRobotics/AllocNet KumarRobotics/AllocNet Public

    A lightweight learning-based trajectory optimization framework.

    C++ 56 6

  2. ZJU-FAST-Lab/forces_resilient_planner ZJU-FAST-Lab/forces_resilient_planner Public

    External Forces Resilient Safe Motion Planning for Quadrotor

    C 47 13

  3. RoboPhD RoboPhD Public

    Some records and notes of weekly arXiv papers, GRASP seminars, and resources

    125 14

  4. KumarRobotics/kr_mp_design KumarRobotics/kr_mp_design Public

    A guidance for the design and evaluation of motion planners for quadrotors in Environments with Varying Complexities

    35 3

  5. KumarRobotics/kr_param_map KumarRobotics/kr_param_map Public

    A parameterized map generator for planning evaluations and benchmarking

    C++ 13 4

  6. Motion-Planning-for-Lynx Motion-Planning-for-Lynx Public

    This is a path planning simulation for Lynx Robot arm based on Gazebo and ROS Control

    Python 18 2