1st RAMI Cascade Campaign<\/h1>\nfor Aerial Robots<\/h2>\n
It is our pleasure to announce the first edition of METRICS RAMI competition for aerial robots, to be held in conjunction with IROS 2021 (September 27th \u2013 October 1st). This competition will take place fully virtually using data generated during previous RAMI campaigns<\/a>. The competition is open to everyone all around\u00a0the world and is led by CATEC (Advanced Center for Aerospace Technologies, Seville, Spain), one of the reference research centres in Europe devoted to aerial robotic technologies.<\/p>\n RAMI competition aims at addressing Inspection and Maintenance (I&M) tasks achieved by aerial and underwater robots, since they are involved in the most promising applications in this sector due to the risks and costs associated with works at height or underwater inspections performed by human operators. This competition will focus on aerial robots only, and the evaluation process will mainly involve tasks related to autonomous navigation and data acquisition for I&M purposes.<\/p>\n There will be two different challenges (Functionality Benchmarks or FBM), and both will be evaluated virtually using data generated by the competition organizers:<\/p>\n FBM1:<\/strong> precise navigation without GNSS, since I&M activities may take place in environments with poor GNSS coverage, or even indoors.<\/p>\n #timestamp tx ty tz qx qy qz qw<\/p>\n 1403636580.013555527 0.0125827899 -0.0015615102 -0.0401530091 -0.0513115190 0.8092916900\u00a00.0008562779 0.5851609600<\/p>\n<\/div>\n<\/div><\/div><\/div> FBM2:<\/strong> automatic detection of defects using advanced AI algorithms, which is important for inspectors when they face considerable amounts of data to review.<\/p>\n #image_name left top right bottom<\/p>\n frame0005.jpg 213 144 315 172<\/p>\n<\/div>\n<\/div><\/div><\/div> For more information about the evaluation please refer to RAMI's Evaluation Plan section 4.2.<\/p>\n <\/p>\n To ensure equal conditions for every team, a docker container will be provided with 3 rosbags with different sensors information, such as RealSenseD435 images, IMU measurements and the ground truth for FBM1; the defect dataset (training + evaluation data) for FBM2; a detailed description of how the results must be delivered and an example of participation for each Functionality Benchmark.<\/p>\n This participation example will contain a sample solution, its mandatory running script, and a sample result file.<\/p>\n Each team must install their own dependencies, their solutions with every single file needed to run them, and it must output the results into the indicated path with the format mentioned above. Then, this Docker images must be uploaded to run the competitor's solution with the new final evaluation data.<\/p>\n Regarding the offered image specs, the chosen OS is Ubuntu 18.04 Focal Fossa with ROS Melodic, CUDA 11-2, CUDNN8 and darknet installed, containing the aforementioned information. If plan to use Machine Learning algorithms taking advantage of CUDA's libraries, you must have at least a GeForce 400 Series Nvidia GPU to get nvidia-drivers<=460.32.03 working with the Docker image.<\/p>\n To encourage teams' participation, results of the challenges can be uploaded weekly during the last month of the validation stage. Those results will be evaluated and updated to an online scoreboard, where the current position of each team will be disposed.<\/p>\n The documents containing the detailed description of the 1st RAMI Cascade Campaig<\/a>n and the setup, basic usage of Docker, as well as hardware and software requirements<\/a>, are attached to the \"More Information\" box.<\/p>\n<\/div>\n<\/div><\/div><\/div> Update: Monday, October 4\u00a0<\/em><\/p>\n<\/div>\n<\/div><\/div><\/div>\n
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Final results<\/h3>\n
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\n IROS 2021 (FBM1 & FBM2)<\/strong><\/td>\n<\/tr>\n \n 1<\/td>\n The Italian Job<\/span><\/b><\/td>\n<\/tr>\n \n 2<\/td>\n CVAR-UPM<\/td>\n<\/tr>\n \n 3<\/td>\n Team XL<\/td>\n<\/tr>\n \n 4<\/td>\n RIL-IISC<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n FBM 1<\/strong><\/td>\n<\/tr>\n \n 1<\/td>\n The Italian Job<\/td>\n 0.762706 m<\/span><\/td>\n<\/tr>\n \n 2<\/td>\n CVAR-UPM<\/td>\n 3.156811 m<\/td>\n<\/tr>\n \n 3<\/td>\n RIL-IISC<\/td>\n 3.501756 m<\/td>\n<\/tr>\n \n 4<\/td>\n Team XL<\/td>\n 5.792044 m<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n\n
\n FBM 2<\/strong><\/td>\n<\/tr>\n \n 1<\/td>\n Team XL<\/td>\n 0.559524<\/span><\/td>\n<\/tr>\n \n 2<\/td>\n The Italian Job<\/td>\n 0.513158<\/td>\n<\/tr>\n \n 3<\/td>\n CVAR-UPM<\/td>\n 0.118812<\/td>\n<\/tr>\n \n 4<\/td>\n RIL-IISC<\/td>\n 0.081482<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n ![\"\"](\"https:\/\/metricsproject.eu\/wp-content\/uploads\/2021\/05\/dose-media-DiTiYQx0mh4-unsplash-1-scaled-e1620850937839.jpg\" "\\"Photo:")
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