{"id":"W2077643920","doi":"10.1504/ijma.2013.058347","title":"Energy efficient complete coverage of mapped areas by single and multiple robots","year":2013,"lang":"en","type":"article","venue":"International Journal of Mechatronics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Terrain; Robot; Computer science; Energy consumption; Motion planning; Energy (signal processing); Point (geometry); Function (biology); Path (computing); Real-time computing; Power consumption; Work (physics); Power (physics); Simulation; Artificial intelligence; Engineering; Electrical engineering; Geography; Mathematics; Cartography; Computer network; Mechanical engineering","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":[0.0003357372,0.0004766694,0.0005914039,0.0003317473,0.0004261729,0.0005074711,0.0007368606,0.0005098945,0.001840781],"category_scores_gemma":[0.001284842,0.0003692282,0.0003766407,0.0004418144,0.0003759502,0.0009752617,0.001705908,0.000355009,0.0003645963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000253104,"about_ca_system_score_gemma":0.0005614571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001814105,"about_ca_topic_score_gemma":0.003635225,"domain_scores_codex":[0.999723,0.00005423965,0.00001148125,0.00006389902,0.00009980148,0.00004763617],"domain_scores_gemma":[0.9995162,0.0001951865,0.00006148058,0.000135501,0.00005136062,0.00004020165],"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":[0.0003321289,0.0000845274,0.001931842,0.0001234334,0.00006306158,0.0003519788,0.000370457,0.7391896,0.05801258,0.004388245,0.001184179,0.1939679],"study_design_scores_gemma":[0.00002260025,0.0001533394,0.001383959,0.000008185682,0.00001408802,0.0001993635,0.0001171825,0.9816664,0.01033935,0.004300072,0.001781778,0.0000137211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2513819,0.0001712589,0.7433316,0.00009956431,0.00001131715,0.00006525186,0.00008322758,0.0008880826,0.003967799],"genre_scores_gemma":[0.8379579,0.00006880367,0.1591406,0.00001958774,0.000007504663,0.00009389157,0.000105416,0.00007173533,0.002534614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001840781,"threshold_uncertainty_score":0.006157994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009034909910062809,"score_gpt":0.2097991601590891,"score_spread":0.2007642502490262,"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."}}