{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ai-imu-dead-reckoning","title":"AI-IMU Dead-Reckoning","arxiv_id":"1904.06064","date":"2019-04-12","proceeding":null,"authors":["Martin Brossard","Axel Barrau","Silvère Bonnabel"],"abstract":"In this paper we propose a novel accurate method for dead-reckoning of\nwheeled vehicles based only on an Inertial Measurement Unit (IMU). In the\ncontext of intelligent vehicles, robust and accurate dead-reckoning based on\nthe IMU may prove useful to correlate feeds from imaging sensors, to safely\nnavigate through obstructions, or for safe emergency stops in the extreme case\nof exteroceptive sensors failure. The key components of the method are the\nKalman filter and the use of deep neural networks to dynamically adapt the\nnoise parameters of the filter. The method is tested on the KITTI odometry\ndataset, and our dead-reckoning inertial method based only on the IMU\naccurately estimates 3D position, velocity, orientation of the vehicle and\nself-calibrates the IMU biases. We achieve on average a 1.10% translational\nerror and the algorithm competes with top-ranked methods which, by contrast,\nuse LiDAR or stereo vision. We make our implementation open-source at:\nhttps://github.com/mbrossar/ai-imu-dr","url_abs":"http://arxiv.org/abs/1904.06064v1","url_pdf":"http://arxiv.org/pdf/1904.06064v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"ai-imu-dead-reckoning","repo_url":"https://github.com/mbrossar/ai-imu-dr","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"ai-imu-dead-reckoning","repo_url":"https://github.com/mbrossar/RINS-W","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"dead-reckoning-prediction","task_name":"Dead-Reckoning Prediction"},{"task_slug":"navigate","task_name":"Navigate"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1904.06064","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}