{"id":"W2079846333","doi":"10.1115/detc2008-49630","title":"Design and Control of an Omnibot Autonomous Vehicle","year":2008,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"University of Ontario Institute of Technology","keywords":"Obstacle; Controller (irrigation); Obstacle avoidance; Computer science; Mobile robot; Collision avoidance; Path (computing); Control system; Collision; Routing (electronic design automation); Control engineering; Robot; Real-time computing; Engineering; Embedded system; Artificial intelligence","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":[0.0002071113,0.0003567757,0.0002577601,0.0001602754,0.00030662,0.0005807885,0.0005002381,0.0003398779,0.001019628],"category_scores_gemma":[0.0002155678,0.0001973981,0.0001607804,0.000115178,0.0003284568,0.000197286,0.0003821833,0.0003022,0.0003403304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002774757,"about_ca_system_score_gemma":0.0007678281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001947291,"about_ca_topic_score_gemma":0.001891348,"domain_scores_codex":[0.9998506,0.00001425536,0.00000520399,0.00002140404,0.00008862231,0.0000197542],"domain_scores_gemma":[0.9999064,0.0000117918,0.00001798789,0.000004141702,0.00004352199,0.00001612476],"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":[0.0002556515,0.00009403638,0.001541702,0.0005624749,0.00007458901,0.0007434642,0.0003362276,0.5739204,0.1665432,0.05007097,0.003341337,0.2025159],"study_design_scores_gemma":[0.00008587977,0.0005958197,0.0008710022,0.00003662896,0.00003575989,0.000229849,0.00005809043,0.941291,0.01537472,0.004667965,0.03672555,0.00002775438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0198252,0.0003317093,0.9706308,0.0001112034,0.000109602,0.0001190867,0.00003976097,0.0004753102,0.008357203],"genre_scores_gemma":[0.7898076,0.0007028375,0.1936095,0.0001460167,0.00006816153,0.000443184,0.000118036,0.00006376432,0.01504096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001947291,"threshold_uncertainty_score":0.003871918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836167015394085,"score_gpt":0.2361724119427288,"score_spread":0.2078107417887879,"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."}}