{"id":"W4200160064","doi":"10.1109/ecice52819.2021.9645621","title":"Omnidirectional Platform for Autonomous Mobile Industrial Robot","year":2021,"lang":"en","type":"article","venue":"2021 IEEE 3rd Eurasia Conference on IOT, Communication and Engineering (ECICE)","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Holonomic; Mobile robot; Omnidirectional antenna; Robot; Kinematics; Computer vision; Computer science; Omnidirectional camera; Robot kinematics; Controller (irrigation); Artificial intelligence; Obstacle; Mobile manipulator; Robot control; Simulation; Antenna (radio)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001617917,0.0002419063,0.0002640098,0.0001231901,0.0001590995,0.0001685885,0.0001974482,0.0002008816,0.0001441626],"category_scores_gemma":[0.00007119052,0.0002795556,0.00007517826,0.0002359815,0.00003074612,0.0001126525,0.00003331294,0.0003557717,0.00002058967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001071319,"about_ca_system_score_gemma":0.00008099106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001325961,"about_ca_topic_score_gemma":0.00002199603,"domain_scores_codex":[0.9989519,0.00002914684,0.0003533387,0.000244265,0.0001565577,0.0002648045],"domain_scores_gemma":[0.9989283,0.0002199307,0.00005002294,0.0005010773,0.0001699742,0.0001306863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002213113,0.00006283976,0.0000524893,0.00007261548,0.00008457956,0.000003269399,0.0003030629,0.949288,0.01397481,0.01083829,0.001441974,0.02385595],"study_design_scores_gemma":[0.0008288219,0.00007124797,0.0003872635,0.0001436809,0.00003152041,0.00001738716,0.0001731364,0.957992,0.009233821,0.0001300547,0.03059736,0.0003937049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3624945,0.003201203,0.603696,0.001751425,0.005630083,0.002039365,0.0002171672,0.001822655,0.01914761],"genre_scores_gemma":[0.9905028,0.001210167,0.007217474,0.00005858836,0.0002082342,0.0001157604,0.0002394725,0.00006032456,0.0003871621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6280083,"threshold_uncertainty_score":0.9999657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04540549640295716,"score_gpt":0.2454638710136388,"score_spread":0.2000583746106816,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}