{"id":"W2155878205","doi":"10.1109/robot.1994.351147","title":"A simple method for the collision avoidance of telerobotic manipulators","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Collision avoidance; Moore–Penrose pseudoinverse; Simple (philosophy); Obstacle avoidance; Gravitational singularity; Computer science; Control theory (sociology); Artificial intelligence; Collision; Robot; Mathematics; Mobile robot; 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":[0.0002854727,0.0007273486,0.0005120062,0.0008893136,0.0005822045,0.0005378925,0.001154661,0.0009797516,0.007539598],"category_scores_gemma":[0.001077586,0.0004123997,0.0005775234,0.0004324779,0.000665103,0.0008556413,0.00110469,0.001308608,0.002183426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003224335,"about_ca_system_score_gemma":0.0006237342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007413692,"about_ca_topic_score_gemma":0.001115376,"domain_scores_codex":[0.9995083,0.00006140104,0.00001723036,0.00007006657,0.0003247554,0.00001814224],"domain_scores_gemma":[0.9997718,0.00007939677,0.00001946823,0.00004659828,0.00006351082,0.00001922986],"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":[0.0000931152,0.00008743369,0.0002938802,0.0005372131,0.00008358326,0.000330573,0.0003515606,0.07292739,0.09139987,0.1602571,0.009468453,0.6641698],"study_design_scores_gemma":[0.000175384,0.0002428941,0.0006519385,0.0001406124,0.00005130916,0.001262466,0.00007494958,0.6519576,0.04021199,0.1257173,0.1793656,0.0001480184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006198016,0.0001373016,0.9980685,0.00003074922,0.00005392967,0.00002938017,0.0000125492,0.0002138677,0.0008340167],"genre_scores_gemma":[0.02668741,0.0003176202,0.9664283,0.00006029911,0.00004944211,0.0002230262,0.0000589492,0.0001611796,0.006013751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007539598,"threshold_uncertainty_score":0.02522248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05188850541686858,"score_gpt":0.2967432493454329,"score_spread":0.2448547439285643,"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."}}