{"id":21936836,"url":"https://github.com/p16i/particle-filter","last_synced_at":"2025-04-22T12:06:26.412Z","repository":{"id":40986207,"uuid":"138799104","full_name":"p16i/particle-filter","owner":"p16i","description":null,"archived":false,"fork":false,"pushed_at":"2023-07-06T21:23:37.000Z","size":68617,"stargazers_count":11,"open_issues_count":2,"forks_count":4,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-04-09T14:57:15.848Z","etag":null,"topics":["particle-filter","simulation"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/p16i.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2018-06-26T22:10:44.000Z","updated_at":"2024-04-09T14:57:15.849Z","dependencies_parsed_at":"2022-09-12T01:41:43.470Z","dependency_job_id":null,"html_url":"https://github.com/p16i/particle-filter","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/p16i%2Fparticle-filter","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/p16i%2Fparticle-filter/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/p16i%2Fparticle-filter/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/p16i%2Fparticle-filter/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/p16i","download_url":"https://codeload.github.com/p16i/particle-filter/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":227017747,"owners_count":17717797,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["particle-filter","simulation"],"created_at":"2024-11-29T01:16:32.878Z","updated_at":"2024-11-29T01:16:33.652Z","avatar_url":"https://github.com/p16i.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Monte Carlo Particle Filter for Localization\n\n Particle Filter Algorithm is a nonparametric implementation of\n the Bayes Filter to approximate state, for example of a robot moving in a maze.\n \n The idea is to represent the posterior belief by a finite number of random variables (particles).\n  The algorithm is repeatedly resampling those particles based on likelihood derived from a measurement model.\n\nThis project is a examination project for SS18 [Monte Carlo Methods in Artificial Intelligence and Machine Learning](https://www.ki.tu-berlin.de/menue/lehre/sommersemster_2018/) course taught by Prof. Dr. Manfred Opper and Theo Galy-Fajou, at TU Berlin.\n\n[[Presentation]](https://docs.google.com/presentation/d/1YpLM_q6YCEqP6g9y3OdV3z-X419Sa1krqwrsSDCFI6g)\n\n## Setup\n```\npip install -r requirements.txt\n```\n\n## Usage\n```\n\u003e python particle-filter.py\n\nOptions\n    - scene :  [scene-1, scene-2, scene-1-kidnapping, scene-2-kidnapping, scene-8.12]\n    - no_particles : number of particles, for example 100.\n    - total_frames :  total time step to run the simulation, it's useful for debugging.\n    - show_particles : a boolean option whether to show the particles.\n    - no_random_particles: number of random particles introduced to the system, required for kidnapping scenes.\n    - save : a boolean option whether to see the simulartor live or save the result as a video.\n    - frame_interval : time interval for each frame, default is 50s.\n```\n\n### Example\n```\npython particle-filter.py --scene scene-1 --no-particles 100 --save\n```\n\n![](https://i.imgur.com/RxP35Wa.png)\n![](https://i.imgur.com/smYPY13.gif)\n\n\n## Members\nAnders Dahl Hjort, Luis Dreisbach, and Pattarawat Chormai\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fp16i%2Fparticle-filter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fp16i%2Fparticle-filter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fp16i%2Fparticle-filter/lists"}