{"id":"W3000338907","doi":"10.1007/s10514-019-09897-6","title":"Joint optimization based on direct sparse stereo visual-inertial odometry","year":2020,"lang":"en","type":"article","venue":"Autonomous Robots","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Artificial intelligence; Computer science; Computer vision; Odometry; Inertial measurement unit; Robustness (evolution); Stereo camera; Visual odometry; Bundle adjustment; Simultaneous localization and mapping; Pixel; Image (mathematics); Robot; Mobile robot","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":[0.0000737414,0.000240227,0.000274041,0.0001463753,0.00006933549,0.0000782979,0.0001028051,0.0001192297,0.0002235168],"category_scores_gemma":[0.00007031044,0.0002502877,0.00009083751,0.0003917161,0.00001892553,0.00009563811,0.00001907702,0.0001490607,0.0001449615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001116772,"about_ca_system_score_gemma":0.00003480608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001063004,"about_ca_topic_score_gemma":0.000001865523,"domain_scores_codex":[0.9988409,0.00004353462,0.0003324825,0.0002925708,0.0002114272,0.0002791198],"domain_scores_gemma":[0.9994684,0.00004588299,0.00005127781,0.0002075688,0.00004429452,0.0001826149],"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":[0.00002030024,0.00004512999,0.00009319568,0.00004448955,0.00001997383,0.00001453481,0.00006619785,0.9952652,0.001764228,0.00004321206,0.0008982596,0.001725317],"study_design_scores_gemma":[0.0005307037,0.0001729047,0.0002513859,0.0000277142,0.00002312095,8.05277e-7,0.000007840476,0.9901118,0.007891065,0.000002119082,0.0006946116,0.0002859197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006716906,0.0000589613,0.9808331,0.0006414539,0.0005227085,0.000300631,0.00001099164,0.0009269831,0.009988301],"genre_scores_gemma":[0.9900925,0.0000144128,0.008241856,0.001138608,0.0002354602,0.00001076009,0.000116144,0.00008855236,0.00006166415],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9833756,"threshold_uncertainty_score":0.9999949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02150829217883478,"score_gpt":0.2123589575417816,"score_spread":0.1908506653629468,"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."}}