{"id":"W3212961470","doi":"10.1109/cyber53097.2021.9588273","title":"Obstacle Avoidance of Multiple Manipulators Based on 3D Artificial Potential Field Method","year":2021,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Shenzhen Research and Development Program","keywords":"Collision avoidance; Obstacle avoidance; Potential field; Obstacle; Trajectory; Computer science; Field (mathematics); Control theory (sociology); Manipulator (device); Collision; Motion planning; Robot manipulator; Artificial intelligence; Robot; Control engineering; Engineering; Mathematics; Mobile robot; Physics; Control (management)","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":[0.0002909953,0.0004056939,0.0005286895,0.0005781364,0.0003848301,0.0003449148,0.0007026075,0.0005015781,0.0007584865],"category_scores_gemma":[0.0004567931,0.0002420043,0.0005233051,0.0003408886,0.0003844713,0.0007277449,0.0006740797,0.0004032872,0.0001559657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003285172,"about_ca_system_score_gemma":0.0004938318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001557595,"about_ca_topic_score_gemma":0.0007294787,"domain_scores_codex":[0.999767,0.00005370118,0.00001091095,0.00002884215,0.0001221513,0.00001734225],"domain_scores_gemma":[0.9998127,0.00007344563,0.00002933352,0.00001332797,0.00005340063,0.00001791331],"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":[0.0001116921,0.00004130614,0.001011457,0.0001444057,0.00006506914,0.000308862,0.0001873645,0.7600407,0.04458741,0.03243179,0.001049862,0.1600202],"study_design_scores_gemma":[0.000008483749,0.00003625936,0.0001936147,0.000005326277,0.000004793616,0.00008037444,0.000008205802,0.9937204,0.001692919,0.003012373,0.001223176,0.00001413212],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01509564,0.000205786,0.9826472,0.00006739152,0.00002888677,0.00002039299,0.000008436131,0.0001585984,0.001767687],"genre_scores_gemma":[0.6225684,0.0004823397,0.3734365,0.00007912309,0.00003188805,0.0001887544,0.00005753896,0.00005024547,0.003105112],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001557595,"threshold_uncertainty_score":0.003097057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02612058505895915,"score_gpt":0.2795752603222532,"score_spread":0.2534546752632941,"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."}}