{"id":"W4376254807","doi":"10.1139/tcsme-2022-0134","title":"Simulation and experiment on obstacle avoidance control of concrete pump truck boom based on improved danger field and gradient projection method","year":2023,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Boom; Obstacle avoidance; Smoothness; Smoothing; Obstacle; Control theory (sociology); Transformation (genetics); Computer science; Task (project management); Projection (relational algebra); Engineering; Control (management); Mobile robot; Robot; Artificial intelligence; Mathematics; Algorithm; Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002887473,0.00009320185,0.0001425418,0.0000590445,0.0001263637,0.00001698693,0.0001309082,0.00008012527,7.553597e-7],"category_scores_gemma":[0.00007237091,0.00008337272,0.0001274969,0.0002054318,0.00001319874,0.00005924768,0.000004495315,0.0001240106,9.562572e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020451,"about_ca_system_score_gemma":0.00005845232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019007,"about_ca_topic_score_gemma":0.00007799044,"domain_scores_codex":[0.9993471,0.000020149,0.0001540152,0.0001887124,0.0001153213,0.0001747263],"domain_scores_gemma":[0.9990106,0.0006053358,0.00004870223,0.0002053235,0.00003407743,0.00009596157],"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":[0.00001221068,0.000004574468,0.00000152925,0.00005433523,0.00004238858,2.058855e-7,0.0005155553,0.9795601,0.01439106,0.001329162,0.000007558209,0.004081286],"study_design_scores_gemma":[0.0005024646,0.0001996034,0.00005604092,0.00004896961,0.00001888879,6.84056e-7,0.00003162252,0.9660987,0.03286145,0.00005305198,0.00005230318,0.00007618252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006165076,0.00001495665,0.9924183,0.0006709311,0.0002434736,0.0004057691,0.00003062962,0.00004805046,0.000002777171],"genre_scores_gemma":[0.8937575,0.00000127685,0.1060139,0.0001395324,0.0000114637,0.00005134855,0.000001010929,0.000009294328,0.00001475794],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8875924,"threshold_uncertainty_score":0.3399841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01724368056647497,"score_gpt":0.2562533278509839,"score_spread":0.239009647284509,"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."}}