{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T04:19:23Z","timestamp":1777522763256,"version":"3.51.4"},"reference-count":44,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2016,1,14]],"date-time":"2016-01-14T00:00:00Z","timestamp":1452729600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Adaptive Behavior"],"published-print":{"date-parts":[[2016,2]]},"abstract":"<jats:p>This paper presents an adaptive-step-control (ASC) strategy for autonomous chemical plume tracking (CPT) in both 2D and 3D spaces. The aim of CPT is tracking a target chemical flow back to its source and declaring its location. While the majority of related works are based on wheeled robots in 2D, the rapid development of rotorcrafts makes 3D plume tracking possible. Hence, in this paper, we first discuss the generalized form of moth-inspired CPT work flow, then extend the orthodox moth-inspired CPT from 2D to 3D. More importantly, we also propose an ASC strategy to deal with the \u201cpassing-by\u201d problem and to gain better control performance. Simulation results are given to demonstrate that ASC can solve the inflexibility caused by \u201chard\u201d step length in diffusive airflow, because it can autonomously adjust the step lengths of the robot according to the status of the environment, enabling our robot to stride confidently in the low chemical concentration areas and focus on highly suspicious areas.<\/jats:p>","DOI":"10.1177\/1059712315623998","type":"journal-article","created":{"date-parts":[[2016,1,15]],"date-time":"2016-01-15T07:40:34Z","timestamp":1452843634000},"page":"52-65","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":21,"title":["3D Moth-inspired chemical plume tracking and adaptive step control strategy"],"prefix":"10.1177","volume":"24","author":[{"given":"Bo","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongbo","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Automation Tianjin University, Tianjin 300072, P. R. China; Department of Computer and Electrical Engineering and Computer Science, California State University, Bakersfield, CA 93311, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuchun","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, P. R. 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