{"id":"W2954788441","doi":"10.3390/s19132993","title":"Safe and Robust Mobile Robot Navigation in Uneven Indoor Environments","year":2019,"lang":"en","type":"article","venue":"Sensors","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Chinese University of Hong Kong","keywords":"Odometry; Mobile robot; Artificial intelligence; Mobile robot navigation; Simultaneous localization and mapping; Computer vision; Robot; Computer science; Modular design; Robot control","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001824028,0.00060091,0.0005091,0.0003584612,0.0003555157,0.0005248542,0.0004754129,0.0004343689,0.0005213671],"category_scores_gemma":[0.0006291359,0.0002470131,0.0002701408,0.0003660268,0.000433342,0.0008136588,0.0008568926,0.0003257189,0.0005727605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001566447,"about_ca_system_score_gemma":0.0005007025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002228235,"about_ca_topic_score_gemma":0.003042337,"domain_scores_codex":[0.9997799,0.0000279991,0.00001021291,0.00005485408,0.00009182257,0.00003530315],"domain_scores_gemma":[0.9997841,0.00003794064,0.00005340012,0.00005640569,0.00005179163,0.00001638942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000181223,0.00005107549,0.005610999,0.000300464,0.0001004401,0.001065818,0.0003524559,0.3479619,0.2102517,0.004883009,0.002764883,0.426476],"study_design_scores_gemma":[0.00002449083,0.0002129435,0.00742841,0.00004964236,0.00005317844,0.0008248972,0.000337189,0.9268138,0.0446359,0.007433221,0.01212412,0.00006214824],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07020048,0.0005187296,0.9255778,0.00007092766,0.00004350063,0.00002790982,0.00006598997,0.002033638,0.001461],"genre_scores_gemma":[0.7684374,0.0006607336,0.2285788,0.00006165163,0.00002869469,0.00007206528,0.000254499,0.0001227264,0.001783552],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002228235,"threshold_uncertainty_score":0.004430592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004719171267021721,"score_gpt":0.1759552480532869,"score_spread":0.1712360767862652,"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."}}