{"id":"W2161024278","doi":"10.1109/robot.1996.503818","title":"Octree-based hierarchical distance maps for collision detection","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Octree; Computer science; Collision detection; Artificial intelligence; Representation (politics); Computer vision; Collision; Voxel; Graphics; Computer graphics (images); Distance transform; Data structure; Path (computing); Pattern recognition (psychology); Image (mathematics)","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":[0.0001763493,0.0001031632,0.0001101642,0.00007498589,0.0001566631,0.00009676495,0.0004278932,0.00006044981,0.00001231735],"category_scores_gemma":[0.00008883088,0.00008972259,0.00005870206,0.0002988597,0.00002920149,0.000178963,0.00003957471,0.00009117224,0.00006512184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005280581,"about_ca_system_score_gemma":0.00001349976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008028125,"about_ca_topic_score_gemma":0.000003606139,"domain_scores_codex":[0.9989683,0.0000376127,0.00016052,0.0003470616,0.0002251142,0.0002613631],"domain_scores_gemma":[0.9991506,0.0002640865,0.00004519432,0.0003962386,0.00005172604,0.00009217155],"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":[0.00009271273,0.000708772,0.001091845,0.000103692,0.0000383916,0.00009194351,0.0007313413,0.05583382,0.004652726,0.05702628,0.04787898,0.8317495],"study_design_scores_gemma":[0.0004640197,0.0001498782,0.0003579943,0.00001293266,0.000002189366,0.000006378438,0.000002155896,0.98452,0.00535509,0.001319098,0.00768079,0.0001294978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006517944,0.00003990877,0.9956293,0.001204278,0.0004337935,0.0002157762,0.000004710658,0.0003083665,0.001512067],"genre_scores_gemma":[0.2975591,0.000001456068,0.7004919,0.0003785044,0.00008178231,0.00004696991,0.000003269516,0.000008577526,0.001428432],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9286861,"threshold_uncertainty_score":0.3658781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02637928404298091,"score_gpt":0.2391463177306457,"score_spread":0.2127670336876648,"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."}}