{"id":"W2163003390","doi":"10.1177/0278364908096316","title":"3D Perception and Environment Map Generation for Humanoid Robot Navigation","year":2008,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of British Columbia","keywords":"Computer vision; Artificial intelligence; Computer science; Humanoid robot; Segmentation; Occupancy grid mapping; Robot; Stereopsis; Noise (video); Mobile robot","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002205733,0.000452329,0.000341454,0.0005989852,0.0002368917,0.0004056013,0.0005130079,0.0004092402,0.002216797],"category_scores_gemma":[0.000955498,0.0003615178,0.0004102407,0.0004928863,0.0003540909,0.0004967168,0.0008189587,0.0002918204,0.0008958691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002340684,"about_ca_system_score_gemma":0.0004448135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003326414,"about_ca_topic_score_gemma":0.003840212,"domain_scores_codex":[0.9998149,0.00004140757,0.000006758684,0.00004589708,0.00007311683,0.00001799532],"domain_scores_gemma":[0.9997739,0.00007413083,0.00002190357,0.00005474375,0.00005488809,0.00002038341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003913551,0.00008336481,0.002275805,0.0002291146,0.00006367301,0.0005038062,0.0009621328,0.1276357,0.1128774,0.007445138,0.005785409,0.7417471],"study_design_scores_gemma":[0.0000390351,0.0001207087,0.003273888,0.00002798522,0.00002862572,0.0004225383,0.0002094679,0.930917,0.04494447,0.01033113,0.009628022,0.00005712439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0112911,0.00005055906,0.9857309,0.00002627925,0.0000115038,0.00002147447,0.00008990944,0.002244465,0.0005338095],"genre_scores_gemma":[0.2994031,0.0001035293,0.6987835,0.00004678216,0.00001205505,0.0001154115,0.0003667342,0.0002675218,0.0009014618],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003326414,"threshold_uncertainty_score":0.007415891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09760256191343164,"score_gpt":0.3254271614327084,"score_spread":0.2278245995192768,"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."}}