Janét J.AREN-CHYUAN LUOKay, Michael G.Michael G.Kay2020-06-162020-06-16199421530858https://scholars.lib.ntu.edu.tw/handle/123456789/502571https://www.scopus.com/inward/record.uri?eid=2-s2.0-0002208077&doi=10.1109%2fIROS.1994.407421&partnerID=40&md5=16a470329039f34e28bfc115821be158A motion planning and self-referencing approach has been developed, simulated and applied to an actual robot. Although there are several novelties to these approaches, the fact that both are based on traversability vectors (t-vectors) is one aspect of this research that is unique. Through their application it has been found that t-vectors enhance the detection of path obstructions and geometric beacons and expedite the identification of features that are visible (or hearable) to sensors in both static and dynamic environments. T-vectors also reduce the data size and complexity of standard V-graphs and variations thereof. This paper provides the t-vector models step-by-step so that the reader will be able to apply them to mobile robot motion planning and self-referencing. © 1994 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.[SDGs]SDG11Mobile robots; Motion planning; Robot programming; Autonomous Mobile Robot; Data complexity; Data size; Mobile robot motion-planning; Motion-planning; Self-referencing; Static and dynamic environments; Traversability; Vector-modeling; Vectorsconference paper10.1109/IROS.1994.4074212-s2.0-0002208077https://doi.org/10.1109/IROS.1994.407421