{"id":49565250,"url":"https://github.com/aaronjs99/squat-plan","last_synced_at":"2026-05-03T11:13:17.352Z","repository":{"id":207509921,"uuid":"555052452","full_name":"aaronjs99/squat-plan","owner":"aaronjs99","description":"SQuAT Plan: Smooth Quadrotor Agile Trajectory Planning","archived":false,"fork":false,"pushed_at":"2025-07-16T00:16:37.000Z","size":1457,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-09-08T22:25:26.063Z","etag":null,"topics":["kinematics","model-predictive-control","motion-planning","optimal-control","python","robot-simulation","robotics","trajectory-planning"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/aaronjs99.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2022-10-20T21:39:33.000Z","updated_at":"2025-08-20T11:57:37.000Z","dependencies_parsed_at":"2023-11-16T07:26:50.666Z","dependency_job_id":"2367f177-5c7c-4345-8523-1fbf75d7041d","html_url":"https://github.com/aaronjs99/squat-plan","commit_stats":null,"previous_names":["aaronjohnsabu1999/squat-plan","aaronjs99/squat-plan"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/aaronjs99/squat-plan","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronjs99%2Fsquat-plan","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronjs99%2Fsquat-plan/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronjs99%2Fsquat-plan/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronjs99%2Fsquat-plan/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aaronjs99","download_url":"https://codeload.github.com/aaronjs99/squat-plan/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aaronjs99%2Fsquat-plan/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32566493,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-03T06:36:36.687Z","status":"ssl_error","status_checked_at":"2026-05-03T06:36:09.306Z","response_time":103,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["kinematics","model-predictive-control","motion-planning","optimal-control","python","robot-simulation","robotics","trajectory-planning"],"created_at":"2026-05-03T11:13:16.683Z","updated_at":"2026-05-03T11:13:17.347Z","avatar_url":"https://github.com/aaronjs99.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SQuAT Plan: Smooth Quadrotor Agile Trajectory Planning\n![Python](https://img.shields.io/badge/python-3.9+-blue?logo=python)\n![License](https://img.shields.io/badge/license-MIT-green)\n![Build](https://img.shields.io/badge/build-passing-brightgreen)\n![Platform](https://img.shields.io/badge/platform-WSL--Debian%20%7C%20ROS-lightgrey)\n\n**SQuAT Plan** is a Python-based framework for agile trajectory planning of quadrotors navigating through complex environments. It integrates nonlinear optimization (via GEKKO), obstacle avoidance, and both 3D and ROS-based visualizations.\n\n## Project Structure\n\n```\nsquat-plan/\n├── run.py                          # Unified entry point\n├── pyproject.toml                  # Modern build system config\n├── src/\n│   └── squatplan/\n│       ├── __init__.py\n│       ├── main.py                 # Core simulation runner\n│       ├── trajopt.py              # Trajectory optimization logic\n│       ├── plotter.py              # Matplotlib-based plotting\n│       ├── quaternion.py           # Quaternion math utils\n│       ├── forester.py             # Obstacle generation\n│       └── sphere_example_rviz.py  # ROS RViz marker publishing\n├── squat.rviz                      # RViz display config\n├── LICENSE\n├── README.md\n└── presentation.pdf                # MAE 271D presentation\n```\n\n## Features\n\n- **Trajectory optimization** using GEKKO with full or simplified dynamics\n- **Obstacle avoidance** using geometric constraints\n- **Quaternion-based orientation modeling**\n- **3D visualizations** via Matplotlib and RViz\n- **Synthetic forest generation** for randomized path planning scenarios\n\n## Getting Started\n\n### Dependencies\n\nClone the repo and install in editable mode:\n\n```bash\ngit clone https://github.com/aaronjohnsabu1999/squat-plan.git\ncd squat-plan\npython3 -m venv .venv\nsource venv/bin/activate\npip install -e .[dev]\n```\n\nInstall ROS dependencies if on Linux or a WSL:\n\n```bash\nsudo apt install ros-${ROS_DISTRO}-rospy \\\n                 ros-${ROS_DISTRO}-geometry-msgs \\\n                 ros-${ROS_DISTRO}-visualization-msgs\n```\n\n### Run Simulation\n\n```bash\npython run.py\n```\n\nTo launch RViz in parallel:\n\n```bash\nroscore\n# Then in another terminal:\npython src/squatplan/sphere_example_rviz.py\n```\n\n## Output Example\n\n- **Trajectory** and **state evolution** plots (position, velocity, quaternion, thrust, moments)\n- **3D environment** with spherical/cylindrical obstacles and path trajectory\n\n## Project Context\n\n\u003e Developed as a final project for MAE 271D — *Control and Trajectory Planning for Autonomous Aerial Systems* at UCLA.\n\n**Contributors:**\n\n- Aaron John Sabu  \n- Ryan Nemiroff  \n- Brett T. Lopez *(Instructor)*\n\nContact: `{aaronjs, ryguyn, btlopez}@ucla.edu`\n\n## License\n\nMIT License © 2025  \nUniversity of California, Los Angeles","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faaronjs99%2Fsquat-plan","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faaronjs99%2Fsquat-plan","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faaronjs99%2Fsquat-plan/lists"}