{"id":"W4392825097","doi":"10.48550/arxiv.2403.08614","title":"Real-Time Sensor-Based Feedback Control for Obstacle Avoidance in Unknown Environments","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Obstacle avoidance; Obstacle; Control (management); Collision avoidance; Computer science; Feedback control; Control theory (sociology); Real-time computing; Control engineering; Artificial intelligence; Engineering; Computer security; Political science; Robot; Mobile robot","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008936355,0.0002797519,0.0003406709,0.0002185645,0.00003628739,0.00002155407,0.0002991214,0.0004457668,0.00005186542],"category_scores_gemma":[0.00001498478,0.0003577586,0.0001503786,0.0002134075,0.00006903395,0.00004954976,0.0001404818,0.0005028629,0.0003738963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004078166,"about_ca_system_score_gemma":0.00003933327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000327905,"about_ca_topic_score_gemma":0.00002312783,"domain_scores_codex":[0.9988812,0.00002709735,0.0001796731,0.0005394057,0.00004370618,0.0003289529],"domain_scores_gemma":[0.9992965,0.00009624742,0.00006481785,0.0004636554,0.0000150835,0.00006367876],"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":[0.00003504786,0.00003781767,0.001357749,0.0002241869,0.00008641788,0.00008742715,0.00003637498,0.9881102,0.004955093,0.004284795,0.0006277688,0.0001570607],"study_design_scores_gemma":[0.001802718,0.00004392276,0.001077269,0.0001785139,0.0001199386,6.824327e-7,0.00006526471,0.9797903,0.00309617,0.01033625,0.002954553,0.0005344631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9426472,0.0001153031,0.05387998,0.0001571765,0.0003545397,0.0007049195,0.000187154,0.0006777685,0.001276006],"genre_scores_gemma":[0.9949107,0.0001773034,0.000333271,0.00002873477,0.00004046534,0.000007865133,0.00004997445,0.00005976051,0.004391944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05354671,"threshold_uncertainty_score":0.9998875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966196137822479,"score_gpt":0.1618318977880549,"score_spread":0.1421699364098301,"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."}}