{"id":"W2095888684","doi":"10.1109/iros.1991.174507","title":"Avoidance of unknown obstacles using proximity fields","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Obstacle avoidance; Computer science; Scheme (mathematics); Collision avoidance; Computer vision; Artificial intelligence; Object (grammar); Point (geometry); Simple (philosophy); Obstacle; Manipulator (device); Robot; Real-time computing; Mobile robot; Mathematics; Computer security; Geography; Collision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001282677,0.00008203454,0.0001304904,0.00004842457,0.00005450278,0.00003219384,0.0005316049,0.00005222113,0.00003468474],"category_scores_gemma":[0.00005798332,0.00007144301,0.0000372887,0.0002525208,0.00003698004,0.0003393831,0.0001241182,0.00009330479,0.0000226692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001671438,"about_ca_system_score_gemma":0.00001456531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004224734,"about_ca_topic_score_gemma":0.000001676096,"domain_scores_codex":[0.9991822,0.0000353152,0.0001812638,0.0002148192,0.000195516,0.0001909476],"domain_scores_gemma":[0.9993114,0.00007867468,0.00007493696,0.0004307059,0.00005478732,0.00004951786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000120249,0.001662056,0.03149242,0.0004601393,0.0002086099,0.0003792879,0.01989859,0.1706042,0.02208327,0.2801115,0.0149535,0.4581344],"study_design_scores_gemma":[0.0001088706,0.00003091827,0.0009501057,0.00002631105,0.000002292348,0.0000166933,0.000009285482,0.9921955,0.005491529,0.0008342629,0.0002286887,0.0001054699],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03488874,0.0001703358,0.9572362,0.0002626205,0.0002386994,0.00007128143,4.966275e-7,0.0001215832,0.007010018],"genre_scores_gemma":[0.4664912,0.000004166342,0.5325688,0.00009328464,0.00002357409,0.000001120747,9.973682e-8,0.000003035749,0.0008147052],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8215914,"threshold_uncertainty_score":0.2913361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06199547389133598,"score_gpt":0.2546869440497919,"score_spread":0.1926914701584559,"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."}}