{"id":25081098,"url":"https://github.com/odegnome/dcode","last_synced_at":"2026-02-08T16:02:10.394Z","repository":{"id":274014836,"uuid":"441522747","full_name":"odegnome/dcode","owner":"odegnome","description":"Implementation of Deep Reinforcement Learning for Collision Prevention in Quadrotor","archived":false,"fork":false,"pushed_at":"2025-01-24T10:20:24.000Z","size":5400,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-06-07T05:07:13.224Z","etag":null,"topics":["autonomous-agents","autonomous-quadcoptor","dissertation-project","machine-learning","python3","quadrotor","reinforcement-learning"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/odegnome.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-12-24T17:34:39.000Z","updated_at":"2025-01-24T10:20:28.000Z","dependencies_parsed_at":null,"dependency_job_id":"f66da0d7-6a43-4376-a246-5553b138b734","html_url":"https://github.com/odegnome/dcode","commit_stats":null,"previous_names":["odegnome/dcode"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/odegnome/dcode","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/odegnome%2Fdcode","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/odegnome%2Fdcode/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/odegnome%2Fdcode/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/odegnome%2Fdcode/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/odegnome","download_url":"https://codeload.github.com/odegnome/dcode/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/odegnome%2Fdcode/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29236125,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-08T14:18:14.570Z","status":"ssl_error","status_checked_at":"2026-02-08T14:18:14.071Z","response_time":57,"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":["autonomous-agents","autonomous-quadcoptor","dissertation-project","machine-learning","python3","quadrotor","reinforcement-learning"],"created_at":"2025-02-07T04:36:41.064Z","updated_at":"2026-02-08T16:02:10.377Z","avatar_url":"https://github.com/odegnome.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Implementation of Deep Reinforcement Learning for Collision Prevention in Quadrotor\n\nIn this project, DRL was used to train an autonomous quadrotor to be able to fly in a\nclosed space, eg, a room. However, the trained policy did not perform well but the reasoning\nis already mentioned in the dissertation report. Moreover, as a follow up, I used preimplemented\nalgorithms, in case my implementation was wrong, and also changed the reward mechanism. This\nchanged the performance of the quadrotor, as it was able to sustain a flight within the\nconstrained space, without colliding. The code is yet to be uploaded, but will update here.\n\nThis repo contains code and dissertation report from my Master's course. Code relevant\nto training the policy and testing the performance has been added, but some irrelevant\npart has been omitted. However, should someone feel that the code in incomplete, please\nraise an [Issue](https://github.com/odegnome/dcode/issues) and I'll see what I can do.\n\nThe dissertation report should also be available in the same repo.\n\nGood luck.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fodegnome%2Fdcode","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fodegnome%2Fdcode","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fodegnome%2Fdcode/lists"}