{"id":"W4390448179","doi":"10.1177/02783649231216499","title":"Energy-optimal trajectories for skid-steer rovers","year":2023,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Turning radius; Trajectory; Skid (aerodynamics); Motion planning; Control theory (sociology); Path (computing); Energy (signal processing); Parameterized complexity; Energy consumption; Work (physics); Optimal control; Pontryagin's minimum principle; Mathematics; Mathematical optimization; Engineering; Computer science; Aerospace engineering; Robot; Algorithm; Physics; Artificial intelligence; Control (management)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003230041,0.0004957195,0.000451953,0.0008725471,0.0005041773,0.0005346962,0.0004288345,0.0006020691,0.002798444],"category_scores_gemma":[0.00115595,0.0003693244,0.0005603536,0.0005230839,0.000645005,0.0009469065,0.0007160051,0.0004843523,0.0003039553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000945478,"about_ca_system_score_gemma":0.0006236843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00274316,"about_ca_topic_score_gemma":0.002656383,"domain_scores_codex":[0.9998597,0.00003249386,0.000009765119,0.0000253351,0.00004378289,0.00002893116],"domain_scores_gemma":[0.9998056,0.0000811298,0.00004526695,0.00001561593,0.00003649108,0.00001588828],"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":[0.00005420523,0.00003271437,0.0008702883,0.00006243292,0.00001561447,0.0001035462,0.0001245804,0.8975248,0.002358598,0.0832364,0.0006487055,0.01496822],"study_design_scores_gemma":[0.00001148542,0.00005679768,0.00047774,0.00002437118,0.000006094156,0.00004358028,0.00009978386,0.9322744,0.001103345,0.06429914,0.001590406,0.00001285899],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3301796,0.0004787127,0.6483637,0.0003233691,0.00002905045,0.0001042168,0.0004240937,0.0002588253,0.01983842],"genre_scores_gemma":[0.8535125,0.0004420532,0.1397335,0.00004781072,0.00001026474,0.0001520584,0.0006885959,0.0001116258,0.005301621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002798444,"threshold_uncertainty_score":0.009361684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1127325068172133,"score_gpt":0.4007802269203994,"score_spread":0.2880477201031861,"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."}}