{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,3,14]],"date-time":"2023-03-14T07:54:39Z","timestamp":1678780479210},"reference-count":17,"publisher":"Cambridge University Press (CUP)","issue":"3","license":[{"start":{"date-parts":[[2006,5,1]],"date-time":"2006-05-01T00:00:00Z","timestamp":1146441600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotica"],"published-print":{"date-parts":[[2006,5]]},"abstract":"<jats:title>SUMMARY<\/jats:title><jats:p>Due to its inherent advantages such as reasoning in the format of heuristic rules based on human experience and less stringent requirement on environmental description, fuzzy logic is a promising tool for the robot motion planning in 3-dimensional dynamic environment. In general, in the Cartesian space, the variables used in characterizing the motion of a mobile robot, such as position, velocity, and force relative to other objects or coordinate frames, contain both the magnitude and the pointing information. In previous studies, the fuzzy reasoning on the pointing information was often developed based on the decomposition of the pointing vector followed by conventional fuzzy logic technique on individual vector components. Consequently, when multiple pointing variables are involved, the number of fuzzy variables that need to be considered simultaneously becomes large and the rule base may become very complex, which diminishes the advantages of the fuzzy reasoning approach. In this research, we tackle this issue by implementing a new fuzzy reasoning approach based on <jats:italic>vector-format fuzzy variables<\/jats:italic>. To achieve this, a set of new membership functions is defined for the vector-format fuzzy variables, followed by the establishment of a series of new vector-based fuzzification, fuzzy inference, and defuzzification procedures. By treating the multidimensional variables as unitary linguistic variables, the number of fuzzy variables in the fuzzy propositions and therefore the scale of the rule base can be reduced considerably. As an application example, the proposed new fuzzy reasoning approach for motion planning is applied to an Underwater Robotics Vehicle (URV) operating in an oceanic environment, where the pointing of the goal and the pointing vectors of the obstacles are treated as vector-type fuzzy variables, which leads to a compact and significantly simplified rule base. The motion planner can successfully guide the URV to move in the complicated dynamic environ-ment in a real-time fashion, which clearly demonstrates the effectiveness and robustness of the new fuzzy logic approach.<\/jats:p>","DOI":"10.1017\/s0263574706003122","type":"journal-article","created":{"date-parts":[[2006,11,20]],"date-time":"2006-11-20T11:18:29Z","timestamp":1164021509000},"page":"325-339","source":"Crossref","is-referenced-by-count":1,"title":["A vector-format fuzzy logic approach for online robot motion planning in 3D space and its application to underwater robotic vehicle"],"prefix":"10.1017","volume":"25","author":[{"given":"X. J.","family":"Wu","sequence":"first","affiliation":[]},{"given":"J.","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Q.","family":"Li","sequence":"additional","affiliation":[]},{"given":"K. H.","family":"Heng","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2006,5,1]]},"reference":[{"key":"S0263574706003122_N103B1","volume-title":"Modeling and Control for the Improvement of Operator's Dexterity in the Operation of an Underwater Vehicle","author":"Cheng","year":"2000"},{"key":"S0263574706003122_N1015A","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-1835-2_14"},{"key":"S0263574706003122_N102C3","doi-asserted-by":"publisher","DOI":"10.1080\/00207179108934205"},{"key":"S0263574706003122_N10132","doi-asserted-by":"publisher","DOI":"10.1109\/TRA.2002.1019461"},{"key":"S0263574706003122_N101B1","doi-asserted-by":"publisher","DOI":"10.1109\/100.774928"},{"key":"S0263574706003122_N10396","volume-title":"Guidance and Control of Ocean Vehicles","author":"Fossen","year":"1994"},{"key":"S0263574706003122_N10328","unstructured":"12. Grumm D. , \u201cOptimizing Functions Using ASCFIT,\u201d available at: http:\/\/www.adass.org\/adass\/proceedings\/adass98\/grummdm\/."},{"key":"S0263574706003122_N10182","doi-asserted-by":"publisher","DOI":"10.1109\/70.954761"},{"key":"S0263574706003122_N101E7","doi-asserted-by":"crossref","unstructured":"5. Sng H. L. , Gupta G. S. and Messom G. H. , \u201cStrategy for Collaboration in Robot Soccer,\u201d The First IEEE International Workshop on Electronic Design, Test and Applications (DELTA'02), New Zealand 2002 p. 347.","DOI":"10.1109\/DELTA.2002.994644"},{"key":"S0263574706003122_N1020B","doi-asserted-by":"publisher","DOI":"10.1109\/48.922788"},{"key":"S0263574706003122_N10241","doi-asserted-by":"publisher","DOI":"10.1177\/027836498600500404"},{"key":"S0263574706003122_N10269","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4613-8997-2_14"},{"key":"S0263574706003122_N1029B","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2006.878978"},{"key":"S0263574706003122_N1033B","volume-title":"Fuzzy Logic, Intelligence, Control and Information","author":"Yen","year":"1999"},{"key":"S0263574706003122_N1035D","unstructured":"14. Koh T. H. , Lau M. W. S. , Low E. , Seet G. , Swei S. and Cheng P. L. , \u201cPreliminary Studies of the Modeling and Control of a Twin-Barrel Underactuated Underwater Robotic Vehicle,\u201d 7th International Conference on Control, Automation, Robotics and Vision, Singapore 2002."},{"key":"S0263574706003122_N103CC","volume-title":"Virtual Reality Toolbox User's Guide","author":"Mathworks","year":"2002"},{"key":"S0263574706003122_N102F2","first-page":"647","volume-title":"5th International Workshop on Advanced Motion Control (AMC'98)","author":"Llata","year":"1998"}],"container-title":["Robotica"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0263574706003122","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,3]],"date-time":"2019-04-03T18:53:13Z","timestamp":1554317593000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0263574706003122\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,5]]},"references-count":17,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2006,5]]}},"alternative-id":["S0263574706003122"],"URL":"https:\/\/doi.org\/10.1017\/s0263574706003122","relation":{},"ISSN":["0263-5747","1469-8668"],"issn-type":[{"value":"0263-5747","type":"print"},{"value":"1469-8668","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006,5]]}}}