{"id":"W2067611664","doi":"10.4236/ojop.2013.23010","title":"Human-Robot Collaborative Planning for Navigation Based on Optimal Control Theory","year":2013,"lang":"en","type":"article","venue":"Open Journal of Optimization","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Architecture; Computer science; Control (management); Obstacle avoidance; Plan (archaeology); Obstacle; Process (computing); Motion planning; Control engineering; Robot; Set (abstract data type); Mode (computer interface); Human–computer interaction; Telerobotics; Trajectory; Human–robot interaction; Artificial intelligence; Mobile robot; 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":[0.001243591,0.0001426162,0.0002682334,0.0001599586,0.000256643,0.0007182598,0.0009523449,0.00006927415,0.00003160032],"category_scores_gemma":[0.0002043991,0.0001218251,0.00005767259,0.0003070403,0.00002943411,0.001710547,0.00004882902,0.0001535937,0.000006691935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008087571,"about_ca_system_score_gemma":0.0001936371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002504032,"about_ca_topic_score_gemma":1.291938e-8,"domain_scores_codex":[0.9985915,0.0002483054,0.0004665429,0.0001982454,0.0003031824,0.0001922644],"domain_scores_gemma":[0.9976224,0.000353014,0.0007501105,0.0002241678,0.000948101,0.00010223],"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":[0.00005719642,0.00006022305,0.0000552605,0.000004740532,0.0000260181,0.00001120461,0.0003559167,0.9954134,0.0002066352,0.001520329,0.0008445493,0.001444562],"study_design_scores_gemma":[0.00247076,0.0008330826,0.0003654902,0.0002124497,0.00001904123,0.00002104038,0.0001104645,0.9946575,0.0004153214,0.0007227728,0.00002937089,0.0001427313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006005029,0.0000286593,0.9969019,0.0006494146,0.0003063022,0.0007797734,0.000003478211,0.00001945523,0.0007105104],"genre_scores_gemma":[0.1729033,5.463489e-7,0.8264921,0.0003502962,0.00009050337,0.00004163797,0.00001237208,0.00001390643,0.00009541607],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1723028,"threshold_uncertainty_score":0.6926196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02390240390056353,"score_gpt":0.3129645144843042,"score_spread":0.2890621105837407,"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."}}