{"id":"W4399435899","doi":"10.1007/s10846-024-02117-z","title":"Humanoid Robot Motion Planning Approaches: a Survey","year":2024,"lang":"en","type":"article","venue":"Journal of Intelligent & Robotic Systems","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Humanoid robot; Inverse kinematics; Computer science; Robustness (evolution); Kinematics; Robot; Focus (optics); Motion planning; Motion (physics); Artificial intelligence; Task (project management); Human–computer interaction; Control engineering; Simulation; Engineering; Systems engineering","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":[0.001438734,0.0002490547,0.0005093236,0.0003980293,0.00005136474,0.0003367933,0.0002768472,0.0001288269,0.00005051381],"category_scores_gemma":[0.00007168518,0.0002015855,0.0002415207,0.0003246855,0.00002466728,0.0002626593,0.00001742297,0.0004430451,0.0001470522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002738496,"about_ca_system_score_gemma":0.00005797498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002175694,"about_ca_topic_score_gemma":0.000003308833,"domain_scores_codex":[0.9978324,0.0001893689,0.001073418,0.0001658904,0.0004352824,0.000303655],"domain_scores_gemma":[0.9991123,0.0002260449,0.0001498752,0.0002028077,0.0001391849,0.0001697629],"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":[0.00001028123,0.00003661002,0.0005680471,0.0003289609,0.0003212265,0.00008528466,0.0006415909,0.9914892,0.0002352545,0.0005620818,0.002241889,0.003479574],"study_design_scores_gemma":[0.0002336179,0.0001263298,0.002257327,0.001229746,0.00009862058,0.000681971,0.0008262345,0.9926991,0.0003010761,0.00005996475,0.001210726,0.0002752256],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005046046,0.01742028,0.96824,0.00005851545,0.007492945,0.0002452732,0.000002152278,0.0001823812,0.001312357],"genre_scores_gemma":[0.9979792,0.000118912,0.0003978069,0.00001239313,0.000835754,0.000008283692,0.000006630852,0.00006034106,0.0005807097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9929331,"threshold_uncertainty_score":0.8220417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08538529527000055,"score_gpt":0.2632976995305166,"score_spread":0.1779124042605161,"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."}}