{"id":"W4389428615","doi":"10.1109/tmech.2023.3336060","title":"A Unified Foot–Terrain Interaction Model for Legged Robots Contacting With Diverse Terrains","year":2023,"lang":"en","type":"article","venue":"IEEE/ASME Transactions on Mechatronics","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Heilongjiang Province; National Natural Science Foundation of China","keywords":"Terrain; Robot; Slip (aerodynamics); Sink (geography); Geology; Computer science; Simulation; Legged robot; Artificial intelligence; Engineering; Aerospace engineering; Geography","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":[0.0001708218,0.0007512574,0.0007666131,0.0006573137,0.0006553765,0.000936298,0.001699619,0.001130498,0.002216312],"category_scores_gemma":[0.0003988141,0.0004394494,0.0007362489,0.000542836,0.0005789897,0.001191966,0.00113426,0.000648886,0.0005825387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004894529,"about_ca_system_score_gemma":0.0005837666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01052106,"about_ca_topic_score_gemma":0.006482131,"domain_scores_codex":[0.9997891,0.00002387195,0.00001466723,0.00005841563,0.00007926409,0.00003471587],"domain_scores_gemma":[0.9998606,0.00002631307,0.00003352957,0.00001859073,0.00004527272,0.0000155993],"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":[0.0000410376,0.00003474025,0.001125777,0.00007309049,0.00002784757,0.0002753439,0.0001626851,0.9671918,0.007461019,0.007559409,0.0006831902,0.01536406],"study_design_scores_gemma":[0.000002715408,0.0000131516,0.0001630582,0.0000028077,0.000005272174,0.00001600471,0.00001362733,0.9986105,0.0001492037,0.0006146342,0.0004046494,0.000004340132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0315231,0.0003108982,0.959655,0.0001361449,0.00006071817,0.00004774035,0.0001189292,0.0003349831,0.007812445],"genre_scores_gemma":[0.9541494,0.0005189908,0.03539542,0.00009655852,0.00004678585,0.0002230913,0.0002844239,0.00007142459,0.009213897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01052106,"threshold_uncertainty_score":0.02091962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03192365585964269,"score_gpt":0.2525680041792649,"score_spread":0.2206443483196222,"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."}}