{"id":"W1629403029","doi":"10.1109/iros.1996.571077","title":"A vision based online motion planning of robot manipulators","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science; Motion planning; Obstacle avoidance; Robot; Obstacle; Redundancy (engineering); Mobile robot","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":[0.0003044191,0.0005083968,0.0004757377,0.0002813106,0.0003480237,0.0004921225,0.0008122211,0.0006896821,0.002153342],"category_scores_gemma":[0.0006480146,0.0003502843,0.0003045372,0.0001804821,0.0005089598,0.000642166,0.0005719422,0.0006477306,0.0006204755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003082422,"about_ca_system_score_gemma":0.0008834637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001987487,"about_ca_topic_score_gemma":0.00202078,"domain_scores_codex":[0.9996836,0.00005327436,0.00001387655,0.00008469442,0.0001353009,0.00002937453],"domain_scores_gemma":[0.9998136,0.000057182,0.00002851898,0.00003308273,0.00005003175,0.0000175787],"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":[0.0002713284,0.0001633994,0.0003597727,0.0001437374,0.00003389218,0.0002908939,0.0001955909,0.3571011,0.1176211,0.01610835,0.003019777,0.5046911],"study_design_scores_gemma":[0.0000462191,0.0002113664,0.000221479,0.00001410172,0.00001026087,0.00009878909,0.00001394565,0.9707655,0.01983555,0.003404538,0.005356744,0.00002138089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00572491,0.00008337244,0.9915966,0.00003893021,0.00002171371,0.00003003518,0.00001672188,0.00114301,0.001344757],"genre_scores_gemma":[0.3400351,0.0002022088,0.6545949,0.00007958031,0.00004589339,0.0001978193,0.0001225826,0.000120055,0.004601797],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002153342,"threshold_uncertainty_score":0.007203639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.029213267756839,"score_gpt":0.2304480113754072,"score_spread":0.2012347436185682,"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."}}