{"id":"W4414346042","doi":"10.1115/1.4069825","title":"Dynamics, Analysis, and Experiments of Obstacle Negotiation for Wheeled Mobile Robots","year":2025,"lang":"en","type":"article","venue":"Journal of Computational and Nonlinear Dynamics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Obstacle; Robot; Mobile robot; Moment (physics); Trajectory; Accelerometer; Work (physics); Energy (signal processing); Test suite; Humanoid 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":[0.0003939949,0.0002456944,0.0002998747,0.0003475371,0.0003614401,0.0002414122,0.0003147148,0.0003188784,0.0007954657],"category_scores_gemma":[0.0008733019,0.0001984777,0.0001769931,0.0001503273,0.000475176,0.0002921355,0.0004507371,0.0002313725,0.00009139432],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000325918,"about_ca_system_score_gemma":0.0002516022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002303036,"about_ca_topic_score_gemma":0.001954264,"domain_scores_codex":[0.9998484,0.00003418117,0.000007812826,0.00001552383,0.00005818718,0.00003592399],"domain_scores_gemma":[0.9995317,0.0002200483,0.00008081117,0.00005352576,0.00006903693,0.00004497823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001181525,0.0004984589,0.01163033,0.0002705145,0.00009242324,0.0007886169,0.0007957977,0.7476282,0.2068754,0.004757925,0.0004413368,0.02503945],"study_design_scores_gemma":[0.0000222295,0.0005372663,0.004167436,0.000006412827,0.000006910661,0.00002577797,0.0001253166,0.9792716,0.01510919,0.000522249,0.0001935582,0.00001204191],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898528,0.00001880402,0.009284861,0.00001524799,0.000004742198,0.00002901667,0.00001976144,0.00005379118,0.0007210306],"genre_scores_gemma":[0.9986634,0.000006180846,0.001121684,0.000001226491,3.044937e-7,0.000009928434,0.000008896023,0.000001523583,0.0001867477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002303036,"threshold_uncertainty_score":0.004579306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00805641358555623,"score_gpt":0.2875379015035849,"score_spread":0.2794814879180286,"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."}}