{"id":"W3138591890","doi":"10.3389/frobt.2021.624333","title":"Efficient Coverage Path Planning for Mobile Disinfecting Robots Using Graph-Based Representation of Environment","year":2021,"lang":"en","type":"article","venue":"Frontiers in Robotics and AI","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Computer science; Motion planning; Path (computing); Mobile robot; Graph; Robot; Representation (politics); Task (project management); Any-angle path planning; Real-time computing; Artificial intelligence; Computer network; Theoretical computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001528698,0.0008350493,0.0004023055,0.0006592787,0.000327353,0.0003750902,0.0006789293,0.0006329631,0.001475871],"category_scores_gemma":[0.0006572119,0.0003523084,0.0005283139,0.0005594128,0.0004339704,0.0007215714,0.000615222,0.0005017673,0.000210118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005551759,"about_ca_system_score_gemma":0.0008643047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008626176,"about_ca_topic_score_gemma":0.009606916,"domain_scores_codex":[0.9998348,0.00004127198,0.00000572964,0.00004910208,0.00004594344,0.00002317136],"domain_scores_gemma":[0.999762,0.0001444335,0.00003191167,0.00001829195,0.00003077931,0.00001261574],"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":[0.00004917508,0.00002768122,0.0002321849,0.00006296243,0.00001459377,0.0000932125,0.00006983732,0.9541563,0.006540041,0.002497373,0.0005532376,0.03570338],"study_design_scores_gemma":[0.000005648169,0.00002972234,0.0001236265,0.000003661857,0.000004739939,0.00002491467,0.00002119372,0.995787,0.00138104,0.001992269,0.0006214101,0.000004878867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03432298,0.000151072,0.9627864,0.00009079332,0.00001190981,0.00007641381,0.0001238621,0.0006939615,0.001742614],"genre_scores_gemma":[0.5156342,0.000320805,0.4807138,0.00004319013,0.000008918953,0.0002210421,0.0005602184,0.0001601896,0.002337661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008626176,"threshold_uncertainty_score":0.01715189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01990843410727768,"score_gpt":0.2719147420183601,"score_spread":0.2520063079110824,"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."}}